Study on flexibility in the Dutch and NW European power market in 2020

Transcription

1 Study on flexibility in the Dutch and NW European power market in 2020 A REPORT PREPARED FOR ENERGIENED April 2010 Frontier Economics Ltd, London.

2

3 April 2010 Frontier Economics i Study on flexibility in the Dutch and NW European power market in 2020 Executive Summary 1 Additional case study: What would be the effect of the COBRA cable?... Error! Bookmark not defined. 2 Introduction 19 Scope of work...19 Organisation of report Our approach 23 Plant and load data for CWE area in Define and agree scenarios...25 Adaptation of CWE system dispatch model...25 Developments in other EU countries...27 Market dynamics Definition of scenarios 29 Wind generation capacity...29 Fuel prices...30 Load forecast...31 Reserve requirements...32 Evolution of the thermal plant park and supply curve...34 Interconnection capacity...38 Summary of scenarios System dispatch simulation for Results for the 6 and 12 GW scenarios...41 Sensitivities Answers to specific questions 67 Can the market handle the fluctuating supply of wind power?...67 What is the impact of wind on system marginal cost?...69 Contents

4 ii Frontier Economics April 2010 What is the role and importance of market integration?...73 Is CHP the perfect partner to wind production?...77 What are the implications for business cases?...78 Is there a need for storage? Market dynamics 81 Markets within the Netherlands...82 Integration of markets in the Netherlands with interconnected countries...84 Other relevant developments Conclusions 91 9 Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West Annexe 2: Data used in simulations Annexe 3: Experience in other EU countries with significant wind and CHP generation 123 Contents

5 April 2010 Frontier Economics iii Study on flexibility in the Dutch and NW European power market in 2020 Figure 1. Key measures for a successful market integration of wind power 3 Figure 2. Contribution of flexibility sources to adapt for higher wind infeed in the 12 GW scenario compared to the 6GW scenario 6 Figure 3. Supply curve 12 GW scenario NL; Figure 4. Monthly real system marginal costs for the 6 and 12 GW scenarios NL; Figure 5. Flexibility options and indicative ranking 12 Figure 6. Our approach 24 Figure 7. Projected cost of power generation from gas and coal, including CO2 prices, in /MWh NL Figure 8. Relationship between manual reserve requirements and wind generation capacity 33 Figure 9. Projected evolution of system adequacy in the Netherlands (12 GW case) 36 Figure 10. Supply curve 12 GW scenario NL; Figure 11. Energy balance in the 6 GW scenario Netherlands; Figure 12. Energy balance in the 12 GW scenario Netherlands; Figure 13. Production profile in a winter week for 6 GW scenario Netherlands; Figure 14. Production profile in a winter week for 12 GW scenario Netherlands; Figure 15. Production profile in a summer week for 6GW scenario Netherlands; Figure 16. Production profile in a summer week for 12 GW scenario Netherlands, Tables & Figures

6 iv Frontier Economics April 2010 Figure 17. Thermal production ordered by the residual load duration curve for 12 GW scenario Netherlands; Figure 18. Changes in system operating costs between the 6 to 12 GW scenarios Figure 19. Level of CO2 Emissions in the 6 and 12 GW case Figure 20. Gross exports from and imports in the 12 GW scenario Netherlands; Figure 21. Heat balance in the 12 GW scenario Netherlands; Figure 22. Net effects of 500 MW additional interconnector capacity on the energy balance Netherlands; Figure 23. Net effects of 500 MW additional interconnector capacity in TWh on net Netherlands imports/exports Figure 24. Net effect of a merit order switch (gas cheaper than coal) on the energy balance Netherlands; Figure 25. Net effect of a merit order switch (gas cheaper than coal) on carbon emissions Figure 26. Net effect of a reduction of IC capacity to Germany and its neighbours on the energy balance Netherlands; Figure 27. Net effect of a reduction of IC capacity to Germany and its neighbours on net imports/exports Figure 28. Net effect of a reduction of interconnector capacity to Germany and from Germany to CEE countries on variable generation costs Figure 29. Net effect of a reduction of interconnector capacity to Germany and from Germany to CEE countries on reserve prices Netherlands; Figure 30. Net effect of inflexible coal on the energy balance Netherlands; Figure 31. Net effect of inflexible coal on variable generation costs Figure 32. Net effect of higher reserve requirements on the energy balance Netherlands; Tables & Figures

7 April 2010 Frontier Economics v Figure 33. How the additional wind generation is absorbed impact of an additional 6 GW Netherlands; Figure 34. Monthly average system marginal cost for 6 and 12 GW wind scenarios baseload period Netherlands; Figure 35. Monthly average system marginal cost for 6 and 12 GW wind scenarios peak period Netherlands; Figure 36. Duration curve of system marginal costs with nominal APX prices in the 12 months to December 2009 superimposed Netherlands; Figure 37. Monthly volatility of real system marginal costs for the 6 and 12 GW scenarios Netherlands; Figure 38. Market coupling in 2020 price convergence between countries 74 Figure 39. System marginal in the 12 GW scenario across the CWE baseload Figure 40. Gross exports and imports by destination and origin in the 12 GW scenario Netherlands to/from other countries; Figure 41. Normalised standard deviation of wind generation forecast error 82 Figure 42. Timeline for different markets in the Netherlands at present 83 Figure 43. Model for cross-border intraday trading 87 Figure 44. Physical flexibility and how to make it accessible to the market 91 Figure 45. Importance of flexibility measures 93 Figure 46. Power plants in Denmark West in Figure 47. The Western Danish system international exchange capacities today 99 Figure 48. Overview nominal capacities of the power plant system in Denmark West in Figure 49. Assumed heat demand covered by district heating in total Denmark 101 Tables & Figures

8 vi Frontier Economics April 2010 Figure 50. Existing and new links around Denmark (brown field show links that are enhanced or new built) 102 Figure 51. Changes in plant dispatch and international exchange due to COBRA base case 103 Figure 52. Changes to international flows induced by COBRA - detailed 104 Figure 53. Seasonal average of hourly flows between Denamrk West and the Netherlands in the base case in Figure 54. Price effect of the COBRA cable in the base case with 12 GW of wind in the Netherlands 106 Figure 55. Effect of 12GW vs. 6 GW wind target on plant operation and exchanges with the COBRA cable 107 Figure 56. Effect of the COBRA cable in the curtailment scenario 108 Figure 57. Evolution of different generation technologies in the Netherlands (derated capacity) 110 Figure 58. Existing plants in the Netherlands 111 Figure 59. Existing plants in the Netherlands - continued 112 Figure 60. CHP plant capacity Netherlands; Figure 61. Installed capacities (derated), by technology in CWE in Figure 62. CHP and HOB capacity and heat demand assumptions by sector 118 Figure 63. Wind infeed assumptions for the Netherlands 120 Figure 64. Interconnection capacity assumptions for Figure 65. Production and consumption data for Denmark West in Figure 66. Frequency of different levels of wind production - Denmark 126 Figure 67. Histogram of residual demand - Denmark 127 Figure 68. Contribution of production and interchanges in July Denmark 127 Figure 69. Load and Residual Load Duration Curve - Denmark 128 Tables & Figures

9 April 2010 Frontier Economics vii Figure 70. Scatter plot of wind generation against net interchange with neighbours (imports are positive) - Denmark 129 Figure 71. Scatter plot of wind generation against Elspot price for DK- W 130 Figure 72. Intraday market volumes - Spain 133 Figure 73. Wind generation and market prices - Spain 134 Figure 74. Development of wind generation - Germany 135 Table 1. Imports from and exports to each CWE country and satellite Table 2. New thermal plant additions (non CHP) - Netherlands 113 Table 3. Plant retirements in Netherlands between 2009 and Table 4. New thermal plant additions (non CHP) - Netherlands 114 Table 5. Key plant characteristics used for conventional thermal plant 117 Table 6. Typical CHP Plant characteristics 119 Table 7. Basic facts about wind generation - Spain 132 Tables & Figures

10

11 April 2010 Frontier Economics 1 Executive Summary 1.1 There has been a debate in the Netherlands about the compatibility of new investment by individual utilities in the thermal plant park with Government policy to have 12 GW of on and offshore wind generation capacity installed by the year The key areas of concern are: whether sufficient flexibility will exist in the power system to permit uncertain, intermittent wind generation output to be accommodated; and whether the available sources of flexibility will be accessible by relevant market participants. In this context, EnergieNed asked Frontier Economics to carry out a study of the year 2020 for the Dutch and North West European power system. The requirement was to undertake quantitative modelling and qualitative analysis of the system in the year 2020 under a small number of scenarios in order to answer a series of specific questions. We were also asked to look at experience in Denmark and other countries with high wind and combined heat and power plant (CHP) penetration. The questions, and our answers to them, are presented in this summary. 1.2 In the following paragraphs we set out: a short list of key findings from our quantitative analysis of two primary scenarios one with 6 GW and one with 12 GW of wind generation capacity; the recommendations we derived from those findings; our answers to the specific questions we have been asked by EnergieNed; and a final wrap up of our conclusions derived from all of the work. 1.3 We also provide a short annex to the Executive Summary setting out the modelling approach. Key findings 1.4 From the quantitative modelling and qualitative analysis we find that: 12GW of wind can be accommodated Our modelling results indicate that the integration of 12 GW of wind power is feasible under the assumptions we have used, if the available flexibility in the Netherlands and interconnected countries is used optimally. This integration of 12 GW of wind capacity can happen along side the substantial growth in conventional Executive Summary

12 2 Frontier Economics April 2010 capacity and will make the Netherlands a net exporter of electricity within the CWE area. Even for the favourable wind year which was modelled we found virtually no wind curtailment under the assumption of perfect market integration and strong grids. However, the system will then be at the edge in terms of flexibility. An increase in demand for flexibility (e.g. higher reserve requirements) or a decrease in supply of flexibility (more must run generation, greater build of less flexible technologies, inefficient allocation of flexible resources) could quickly trigger significant wind curtailment, frustrating the policy aims of reducing carbon emissions by displacing generation from fossil fuels. Therefore, creating optimal flexibility conditions in the CWE market is crucial to integrate of the output from 12 GW of wind generation capacity. International power flows play a crucial role for integration Wind integration requires strong grids. International power exchanges between the CWE countries play a crucial role in managing variable and unpredictable wind infeeds in the Netherlands, both from a technical and from a market point of view - especially in times of low load and high wind in-feed. The integration of about 2/3 of the additional wind supply, when going from 6 to 12 GW, is facilitated by changes in import and export balances. This requires flexible and close-to-real-time access to (cross-border) transmission capacity. For our analysis we assumed that by 2020 national grids are strong enough to avoid internal grid congestions within the individual countries of the CWE area. 1 Conventional plants needed to provide flexibility Flexibility from conventional plants is also required to accommodate 12GW of volatile wind infeed. High wind production decreases utilisation rates for thermal power plants. However, due to its volatile character, wind can only substitute secured generation capacity to a limited extent so the thermal capacity is still essential for security of supply. Under the assumptions we have adopted, CHP plants could not efficiently provide significant additional flexibility to the system, even though many have variable heat to power ratios and could switch off power output and serve heat demand from heat only boiler (HOB). However, other sources of flexibility are available at lower cost to provide the additionally required flexibility. 1 Obstacles such as the bottlenecks which exist today (e g for the north-south and east-west transport within Germany) are assumed to be effectively removed. Currently, projects are underway or planned to remove such obstacles; the removal of these bottlenecks in the coming decade is crucial to make optimal use of the wider CWE market. Internal congestions will hamper the integration of wind, also in neighbouring countries. Executive Summary

13 April 2010 Frontier Economics 3 Market design should ensure access to flexibility source Integrating wind requires market rules that allow for an optimal use of projected interconnector capacity. As the contribution of wind grows, the integration of short term markets, such as intra-day or balancing power markets, across borders increases in importance. Recommendations for future system development 1.5 Our recommendations for future system development are: successful market integration of wind power will require that: physical flexibility is available in the system; and the flexibility is accessible to those who need it via efficient markets. 1.6 Figure 1 sets out the key measures that flow from these requirements. Figure 1. Key measures for a successful market integration of wind power We need to make sure that physical flexibility is in the system Thermal plants needed on system and able adjust their output AND make sure that this flexibility is accessible to those who need it! Liquid markets close to delivery (Intraday) CHP Plants need to become more flexible CWE market coupling allows for better interconnector usage Nuclear should be able provide manual reserve Harmonize day ahead markets with GB and Norway Interconnectors are important International balancing markets Source: Frontier 1.7 The main actions that are likely to increase flexibility in the system are: Allow for strong national and international grids this requires an adequate regulation of the networks as well as efficient approval procedures for planning and construction of new lines at national and cross border level; and Executive Summary

14 4 Frontier Economics April 2010 Efficient market designs Provide for efficient allocation of available flexibilities both within the Netherlands and in the neighbouring CWE countries. This includes an efficient integration of short term markets (day ahead, intraday, balancing) within the CWE; and close to real time gate closures to allow market players to react to latest information gains (e.g. better wind forecasts). Must run generation to be kept at low level Wind curtailment is most likely to occur during high wind and low demand hours. High volumes of inflexible must run generation (e.g. from heat driven CHP or from plants providing downward reserve to the TSO) will increase the chance of curtailment. Plants which have not been operated very flexibly in the past (e.g. nuclear, CHP) will need to contribute to flexibility in future. This may require greater incentives than in the past (e.g. low or negative prices at times of energy surplus). 1.8 From our analysis we rank the importance of actions to increase physical flexibility options as follows: ensure strong national and international grids; enhance flexibility of CHP and nuclear (to keep thermal must run low as low as possible); and harmonize market rules to allow for efficient access to flexibility within and outside the Netherlands. 1.9 Power storage is a further flexibility option under discussion. However, our calculations suggest that, under scenario assumptions, it would be little used. It is possible that it would gain in importance if required grid extensions were delayed. Questions and Answers 1.10 In the following section we present our answers to the specific questions put by EnergieNed. What is flexibility? 1.11 We consider flexibility to be the availability of resources, from the day ahead of delivery to the time of delivery, that can change their level of production or demand by defined amounts and sustain this position for a period of at least one hour in a reliable manner. Executive Summary

15 April 2010 Frontier Economics 5 Will the Dutch system be able to handle a fluctuating supply of significant amounts of wind power? 1.12 Under our assumptions, the CWE system has sufficient flexible resources to integrate the 12 GW of wind generation output, even with production at slightly higher than average levels. Under our base scenario 2 we observe only limited wind curtailment, even in low load hours, and no load shedding 3 ( uncovered electricity demand ). However, the sensitivity analysis indicates that the system is close to the edge ; an increase in the manual reserve requirement and stricter assumptions on plant flexibilities (minimum load conditions, ramping constraints to provide manual reserve) can lead to about 10% of wind generation being curtailed in the Netherlands in Although the simulation models wind as a free resource, for physical and economic reasons, curtialment is sometimes the best or the only solution (although wind curtailment would put to question whether it is economic to build wind capacity to a level of 12GW). For a sensitivity run we assumed higher reserve requirements to be provided from the generation side (2200MW rather than 1300MW) and less flexible hard coal plants. We then observed wind curtailment volumes to be necessary in the range of 4 TWh pa (this corresponds to about 20% of the additional wind infeed when moving from 6GW to 12 GW of wind capacity) The main sources of flexibility are: the ability to vary the level of interchange with interconnected countries, especially Germany and Belgium/France; and changing ouput from conventional coal-fired plant and CCGT plant Our analysis suggests that interchange with other countries within the CWE region is the key source of flexibility. The integration of about 2/3 of the additional wind supply when moving from 6 to 12 GW finds is accommodated by changes in imports and exports. Flexibility from conventional thermal plants provides the remaining third. The CWE market plays a crucial role in handling wind power in the Netherlands, especially in times of low load and high wind infeed Heat following CHP plants exhibit little response to the significant changes in residual demand (load less wind and other renewable energy generation) as their options to adapt are restricted by local heat demand. Uncoupling power and heat production is limited by technical (local heat capacities from HOBs) and economical constraints (higher efficiency losses). 2 For our quantitative analysis we always looked at the year 2020 applying a 6 GW wind scenario and a 12 GW wind case for the Netherlands for various scenarios. 3 As we assume perfect foresight and an adequate capacity balance in the model the only reason for load shedding could be steep ramping between consecutive hours due to very volatile wind in-feed. Executive Summary

16 6 Frontier Economics April Figure 2 shows how the 21 TWh of additional wind in-feed are accommodated into the Dutch power system. The extra wind leads to about 6.8 TWh higher exports; imports are reduced by 7.2 TWh. The output from conventional thermal generation decreases by about 7 TWh. Figure 2. Contribution of flexibility sources to adapt for higher wind in-feed in the 12 GW scenario compared to the 6GW scenario Difference in TWh/a Wind Exports Coal CCGT Imports Extra power prod from He at adjustme nts Flexibility s ource Source: Frontier 1.17 Our review of international experience also indicates that interchange with interconnected countries is a critical factor in successful integration of wind generation output elsewhere, for example in Denmark and Germany. What role do the CWE market and market coupling play? 1.18 For the reasons given above, market integration - not only coupling at the day ahead stage but also in subsequent hours down to the hour of delivery - plays a crucial role. This supports the idea of coupling the CWE day ahead markets, as envisioned by May 2010 and in due course moving to integrate shorter term markets such as the intraday and the balancing markets The Nordic area has already successfully integrated these different markets and we see no reason why it cannot be achieved in the CWE area by Data for the existing TLC area show a significant coupling with strong price convergence between countries The results also indicate that increases in interconnection capacity will be critical to wind integration. Flow-based coupling will help to make more effective use of the physical capacity which exists and there are a number of projects in hand or Executive Summary

17 April 2010 Frontier Economics 7 under study to increase both synchronous and HVDC interconnections. Interconnection allows each country to take advantage of the geographical dispersion of the wind resource to share the management of the fluctuations in any single country Note that our analysis assumes that there are no internal grid congestions within the individual countries of the CWE area in The bottlenecks which exist for the north-south and west-east transport within Germany (or in The Netherlands around Eemshaven and Maasvlakte) are assumed to be effectively removed by Currently, projects are underway or planned to remove such obstacles; their removal in the coming decade is crucial to make optimal use of the wider CWE market. Internal congestion will hamper the integration of wind substantially. What is the impact of fluctuating wind power on required reserve capacity? 1.22 Based on a review of studies in Germany 4 and the UK, it is clear that at some level of wind penetration additional manual or short-term operating reserve is needed. The precise level at which this requirement is triggered and the rate of increase of reserve required as wind capacity increases above this level is subject to some uncertainty. The assumptions we have adopted are an increase of reserve requirement by 1MW for every additional 10MW of wind capacity above 6 GW of wind generation capacity; however, we are aware that additional engineering studies are being done on this subject 5. The requirements are also sensitive to improvements in the ability to forecast wind generation output in the hours immediately preceding delivery and to the size and structure of the thermal power plant park (e.g. existence of large generation units or interconnector infeeds). What is the impact of fluctuating wind power on power prices? 1.23 The fact that wind generation is unreliable means that significant thermal capacity must be maintained on the system to provide security of supply. Wind generation output then shifts the supply curve, shown in Figure 2, to the right reducing price at which it intersects with demand. 4 Compare dena grid study (2005) 5 Additional studies have been carried out by Ummels (2009) or Holttinen et al (2007) Executive Summary

18 8 Frontier Economics April 2010 Figure 3. Supply curve 12 GW scenario NL; Min. load Max. load OCGT /MWh CHP Flex Nuclear New coal and IGCC CHP Inflex Greenhouse motor Old coal CCGT 20 0 Wind, Other Re Potential Range of Wind Input 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 MWe Source: Frontier Economics 1.24 Our model produces data on system marginal cost; this is a reasonable indicator of market price in a competitive market but includes no premium for scarcity which can arise if there is limited supply to meet demand in peak periods 6. The impact of increased wind on system marginal cost is clearly seen in the comparison between our 6 GW and 12 GW scenarios. The additional wind infeed lowers the average baseload price level by about 5 per MWh (Figure 3). In the 12 GW scenario, there are over 160 off-peak hours when the system marginal cost is zero. 7 There is also a marked increase in price volatility, especially in winter when moving from 6GW to 12 GW of wind capacity. 6 We agreed to base our analysis on cost based power prices using short run marginal generation costs as price estimator for wholesale power prices in For this system flexibility analysis, we agreed not to apply additional price mark ups in times with high demand and scarce power plant capacities in our modelling (e g mark ups based on long run marginal cost analysis for new entry) as this would have required additional assumptions on price building mechanisms. 7 The model also allows for negative prices, but as we assume that by 2020 wind can be curtailed without any penalty this is not likely to occur. Today negative prices can occur on day ahead markets due to regulatory rules (e. g. German TSOs are obliged to sell all wind energy on the spot market. Wind park operators feeding in under the German renewable act do not receive any incentives to curtail their in-feed.) Executive Summary

19 April 2010 Frontier Economics 9 Figure 4. Monthly real 8 system marginal costs for the 6 and 12 GW scenarios NL; Monthly average wholesale power price in /MWh NL - base - 6 GW NL - base - 12 GW 50 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Source: Frontier Economics Is there a reason for saying CHP is the perfect partner to wind generation? 1.25 Our view is that CHP is not incompatible with 12 GW of wind generation capacity, but it is far from being the perfect partner. When moving from 6 to 12 GW of wind capacity, CHP shows little change in its market position. This is due to the technological constraints inherent in this technology of needing to track heat demand, limited heat-only-boiler (HOB) capacity and the high cost of running CHP more flexibly which would require running it at part load 9 or ramping down electricity output entirely and serving heat load from HOBs A feature of a wind/chp system is that high wind in-feeds are mainly expected in winter times when CHP s also run at high capacity to produce heat and power, resulting at an excess of electricity being offered to the market (this holds even if we account for the fact that electricity demand in winter is also higher than in other seasons). The compatibility of CHP with wind shown in our analysis could 8 Concerning prices: As we depart from prices in the year 2009 and do not incorporate an inflation forecast, the prices can be interpreted as real prices in 2009 price levels. 9 We did not include heat buffers in greenhouses in our model but considered heat only boilers there as well. Executive Summary

20 10 Frontier Economics April 2010 change if the market share of CHP were to increase and CHP capacity were to remain as inflexible as it currently appears to be Since, under our assumptions, CHP plants show only very limited flexibility, the impact of extra wind on CHP fuel use or emissions is limited. In a standard CHP operation mode CHP plants show a very high overall fuel efficiency of around 90%). When power is not needed (e.g. due to high wind infeed) the CHP plants can either reduce both their power and heat output; or decouple heat and power output to keep heat delivery high while reducing the power delivery (by using a HOB or by changing power-toheat ratio, if this is technically possible) In both cases the benefit of combined heat and power production is lost (heat will be generated from a HOB with 90% efficiency, power will be produced at an efficiency level which is below modern conventional plants (CCGT 58%, coal 47%) In general a high heat output tends to increase the overall CHP plant efficiency, higher power output (leading to lower heat output) decreases its overall efficiency. However, local heat demand is restricted and thus restricts the potential adaptations in the operation mode of the CHP plants It is noteworthy that Denmark has done much to make its CHP park more flexible by requiring power exchange market participation of CHP. The introduction of electric boilers that allow CHP generation to be decreased while meeting heat demand from electricity in high wind periods with low load has been encouraged. However, the characteristic of CHP plants in Denmark and the Netherlands is different: While Danish CHP plants are mostly district heating plants coming with low steam temperatures the Dutch CHP plants are mostly industrial CHP plants with high temperature steam supply and only very limited heat store options To limit the probability of wind curtailment, CHP plants need to become flexible enough to contribute to manual reserve provision thus avoiding the need to start other thermal plants for this purpose. Is there a need for storage? 1.32 The Compressed Air Energy Storage (CAES) plant we have included in the two scenarios has a very low load factor. At this level of wind penetration and given our other assumptions (especially regarding the capital cost of storage plant we assume specific investment costs for a CAES plant of 610 per kw), storage does Executive Summary

21 April 2010 Frontier Economics 11 not appear to be needed 10. However, in a situation with significant local grid congestion (and constraints on extending the grid in time), power storage can become an option if it could benefit from extra grid related revenues from solving congestion or from avoiding grid related wind curtailment 11. When combined with wholesale power arbitrage and reserve power revenues, this could make individual storage projects more attractive if they are located at the right place within the grid. Conclusions from the questions and answers 1.33 Significant changes in the Dutch generation mix are expected in the next decade: there is likely to be a strong increase in new conventional generation alongside substantial volumes of additional wind power. Estimates show that these developments, to the extent envisioned in our scenarios, can take place simultaneously without any significant wind curtailment, even in low load hours. However, the system appears to be close to the edge. Therefore, creating optimal flexibility conditions in the CWE market is crucial to integrating wind power further The most important sources for flexibility are shown in Figure Please note that we used price estimators based on short run marginal costs for this study. This tends to underestimate peak prices and thus tends to underestimate the value of storage. We also used cost based prices for reserve capacity which also tend to be lower than ancillary service prices in reality. 11 Here also regulatory rules are important. Executive Summary

22 12 Frontier Economics April 2010 Figure 5. Flexibility options and indicative ranking Action points Importance Integration with CWE Increase usable exchange capacities Physical (international) interconnectors Strong internal grids (NL, DE) Efficient allocation of capacities close to delivery Very high Flexibilize conventional system Reduce must run Nukes and CHP contribute to ancillary services Flexibilize CHP plants Conventional coal needs to contribute High Storages Storages become attractive if points above are not used weak grids (extra revenues from grid congestion), high downward reserve prices Secondary Option DSM Demand side should contribute We account for 300 MW manual reserve from DSM, We did not model DSM but from our experience the practical potential is limited. Not analysed in detail here Source: Frontier 1.35 In this study we did not model demand side flexibility options. However, if end users are entitled to contribute to system flexibility, they will need adequate technical means and appropriate price signals (e.g. using smart metering and a innovative tariff structures) In addition, the flexibility that can be provided from renewable generation sources should be used. In terms of wind power this includes incentives for improved forecast quality and grid orientated location of wind plants (provide incentives to take into account potential grid extension costs when choosing the best wind sites). Wind should also be incentivized to provide ancillary services as far as they are technically able to do so 12. Other renewables which can be dispatched (biomass, geothermal) should receive price signals from the power market. However, those sources will not play a key role in the Netherlands in terms of generation quantities The challenge of wind integration lies in making the power system as flexible as possible. This needs to done in combination with market integration and optimal use of interconnection capacity to handle fluctuating wind power in the CWE electricity market (see Figure 2) Firstly, it is important that the cross border power exchange capacity is used optimally and is made available to market players. This includes, for example, a sound understanding of international load flows (requires high degree of 12 Providing downward reserve or reactive power from wind units can be valuable particularly in times where only a limited number of thermal plants is producing. Executive Summary

23 April 2010 Frontier Economics 13 coordination between TSOs) which may allow for more efficient grid utilisation than a standard approach assuming typical load situations. However, grid security requirements should, of course, always be taken into account International market integration will require policy backing so that those who need access to flexibility can obtain it from those who have more than they need. This can involve the following: new interconnection capacity projects based on regional planning and inter TSO co-operation, as envisaged in the third energy package (but only helpful if internal congestions is also resolved); the realisation of the planned day ahead coupled market in CWE and the introduction of flow based market coupling to make best use of existing interconnection capacity; the development of day ahead market coupling between the Netherlands and countries linked by HVDC links (GB and Norway) 13 ; the development of an integrated and continuous intra-day market to manage short term variations in intermittent output and pool flexibility sources in the CWE region (make flexibility sources available to the whole CWE market through improved usage of cross border capacity) 14 ; and the development of arrangements to permit international participation in balancing markets to help keep the costs of exposure to imbalances as low as possible Secondly, maximizing flexibility of conventional supply is required. A broad portfolio of technologies has to contribute to this: conventional thermal power plants (coal/gas) need to adapt to start/stop and partload operation; new nuclear generation can also contribute to system flexibility by providing tertiary reserve; and CHP plant will need to become more flexible by shifting heat production to alternative sources (e.g. heat-only-boilers, heat buffers) in order to decouple electricity output and heat demand to a greater extent than is now possible. 13 Only helpful if the HVDC links can change flows within their full technical capability. 14 If high volumes of wind capacity limit price convergence in the coupled day- ahead market, it may be necessary to review the proportion of cross-border capacity that is allocated through implicit auctions at the day ahead stage and that which is allocated on a monthly and annual basis. Executive Summary

24 14 Frontier Economics April We think that, for the most part, price incentives will be sufficient to achieve these changes but some measures may be needed to ensure that CHP plant participate in the market so that the owners can respond to these incentives. This includes also negative prices for hours when supply exceeds demand. Negative prices can be an important incentive for plant operators to adapt their production mode to low demand Market developments should be observed carefully to ensure that unintended effects from existing policy measures do not disturb an adequate capacity balance of the system A key point will be to address the problem of economic viability of new conventional generation which runs the risk of operating at low load factors due to the increase in wind capacity. To some extent, this can be addressed by building more peaking plant. However, under the prevailing market model in which both energy and capacity are remunerated through payments for energy production, plants need sufficient operating hours to receive their required revenues. Further research will be needed to analyze those effects and to develop an adequate incentive scheme (Could capacity markets be an option? Do ancillary service markets provide enough incentives? Or do wholesale prices already provide sufficient incentive for new investments?) 1.44 To sum up, with regard to the existence of flexible resources, we do not see any direct need for new policy measures in the Netherlands to mandate specific actions, with the possible exception of taking additional steps to encourage market participation by CHP plant. However, existing policies in support of stronger interconnection with neighbouring countries will need to be pursued strongly at national and regional level. Annex to the Executive Summary: Details on our modelling Approach General approach 1.45 We considered two basic scenarios: a base scenario with 12 GW of wind generation capacity, split 50:50 onshore and offshore; and a low wind 6 GW scenario (4 GW onshore and 2 GW offshore) in order to study the impact of a significant increment of wind capacity We used a system dispatch tool to simulate operation of the Dutch, German, Belgian and French power systems (the Central West Europe or CWE region) in We also took account of interconnection with satellite regions such as Scandinavia, Poland, Alpine countries and Spain, although these were not modelled in detail. The model uses a linear/mixed integer program solver to find Executive Summary

25 April 2010 Frontier Economics 15 the least cost dispatch of the system subject to a number of constraints. The focus of scenario definition was on fuel, carbon emissions and other variable costs of generation. We did not consider fixed operating and maintenance (O&M) or investment costs With help from EnergieNed and Nuon, we collected detailed data about the Dutch plant park, including conventional and CHP units. We identified those CHP plants which appeared to have flexible power to heat ratios and captured this flexibility in the logic of the dispatch tool. Each CHP plant was modelled to have some associated Heat Only Boiler (HOB) capacity that optionally can be used to cover parts of local heat demand We used a recent load forecast prepared by the Dutch transmission operator TenneT to the year 2016 and extrapolated it to The model optimises dispatch for the CWE region in one hour time steps, subject to interconnection capacity constraints, taking account of randomised wind generation output. In this sense the model has perfect foresight and assumed perfect market integration within the assumed cross border limits All modelling and analysis was carried out at constant 2009 prices. We did not consider the effect of inflation We separately gave consideration to the market dynamics required to ensure that the rights to the available flexibility could be reallocated efficiently to those needing flexibility from those with surplus flexibility. Assumptions on power plant system 1.52 We projected the non-wind plant park in the Netherlands on the following basis: we took data on the capacity and commissioning date of existing plants on the system; we projected plant retirement using standard lifetimes for different technologies; we added plants under construction at the expected commissioning date but assumed that by 2020 two of the coal plants would be deployed as IGCC, one with CCS; we added a nuclear plant of 1000 MW to reflect the impact of a possible extension of nuclear capacity; and we added a 100 MW Compressed Air Energy Storage (CAES) plant in order to evaluate to what extent it would be economic to operate We assessed the adequacy of the projected capacity using a UCTE type methodology that compared capacity after derating for outages and planned unavailability (90% of nameplate capacity for thermal plant and 10% for wind Executive Summary

26 16 Frontier Economics April 2010 plant) with forecast demand plus reserve requirements 15. On this basis the above projections imply a small surplus in capacity over what would be considered adequate by 2020 to meet demand and allow for sufficient flexible reserve capacity to ensure stable supply of electricity. Owing to the use of a 90% derating factor for wind generation and the assumption that 10% additional reserve is needed for wind capacity in excess of 6 GW, the plant park has the same level of adequacy under both scenarios Capacity development in the other countries in the CWE area was assumed similar for both scenarios and follows market estimates by Frontier based on national energy policies (in particular for renewables and nuclear), standard plant life times and filtered announcements of new built plants. The scenario includes further growth in wind in NW Europe (both onshore and offshore) as well as life-time extension of existing nuclear capacity in Germany and Belgium. Assumptions concerning CHP 1.55 We derive CHP capacities in 2020 by applying standard lifetimes for existing CHP plants and analysing new built capacities. Total CHP capacities are slightly lower than today. This is consistent with decreasing heat demand in the Netherlands as a result of improved energy efficiency We distinguish between flexible CHP plants with variable power-to-heat ratio and CHP plants with a fixed power-to-heat ratio. We assume typical heat demand profile for industrial CHP plants, district heating plants and greenhouse CHP. CHP plants can provide flexibility by decoupling power and heat demand using heat only boilers (HOBS); or changing the power-to-heat ratio (flexible CHP plants only). Details on assumptions for power plant parameters can be found in the annexes to the full report. Assumptions concerning reserve requirements (ancillary services) 1.57 Based on our understanding of current TenneT policies on reserve and thinking of how they might evolve, we assumed that with wind capacity of up to 6 GW the manual reserve requirement would be dictated by the largest single infeed that could be lost. For incremental wind generation above 6 GW, we assumed with reference to studies for Germany and the UK - that additional manual reserve 15 The derating methodology accounts for the fact that at time of highest annual demand not all installed plant capacity will be there to cover this peak demand. Some thermal plants will be unavailable due to revisions or outages. Generation source relying on volatile weather conditions like wind, solar radiation or water levels can not be accounted as guaranteed wind plants for example are derated down to 10% of installed capacity being accounted as guaranteed available. This methodology is in line with various system adequacy studies (e g the dena grid study calculated the capacity credit for wind to be around 5-15 %depending on wind penetration levels). Executive Summary

27 April 2010 Frontier Economics 17 equal to 10% of the additional wind capacity would be needed. This gave us a requirement for manual reserve to be provided by the power plant system of 1300MW by 2020 (compared to 700MW today) 16. Assumptions concerning the grid 1.58 Concerning the capacities available for physical power exchanges to and from the Netherlands by 2020 we assume for our base case that: the net transfer capacity between the Netherlands and Germany available to market players will be 3700MW. This means that existing lines can be used to a more efficient extent than today as bottlenecks close to the border will be removed and market design allows for a more efficient use; and a new link Wesel- Doetinchem will be available from 2013; the net transfer capacity between the Netherlands and Belgium available to market players will be 2300MW; and there will be no internal grid constraints within Germany or the Netherlands by Sensitivity runs In addition to both scenarios, we also analysed a number of sensitivity runs on the 12GW scenario to explore the impact of changing key variables. We looked at an increase in manual reserve requirements; less interconnector capacity with Germany and from Germany to the Alpine countries and to Eastern Europe; an increase in the interconnector capacity to France via Belgium; higher coal prices sufficient to make most combined cycle gas turbines (CCGT) plant a cheaper source of electricity in most months of the year; and a constraint that prevented coal-fired generation from operation below minimum stable generation i.e. no stops and starts. 16 For both cases we assume that demand side continues to contribute 300 MW of manual reserve to TenneT as it does today. Executive Summary

28 18 Frontier Economics April We derived fuel price assumptions from recent international projections of crude oil prices and typical relationships between oil, coal and gas prices.. Executive Summary

29 April 2010 Frontier Economics 19 2 Introduction 2.1 In the context of the adoption of the EU climate change package, the Dutch government is aiming at the introduction of some 12 GW of wind generation capacity by 2020 as a key measure towards meeting the requirement to have renewable energy in all sectors (electricity, heat and transport) equal to 14% of final energy consumption. The wind capacity will be located onshore and, increasingly, offshore. The plan implies a very rapid increase on the current installed capacity base of 2.1 GW in December While this policy has been in development, the power sector has attracted substantial new investment in thermal generation capacity, making it increasingly likely that the Netherlands will evolve from its current status as a net importer to a net exporter of energy. The projects that are under construction or proposed include new coal and gas fired plants and a new nuclear plant. These investments, when combined with the aim for wind generation capacity, would lead to a significant surplus in power generation capacity beyond what is needed to meet Dutch demand securely unless some of the investments are deferred or older plant retired before the end of their standard lives. 2.3 These developments have led to debate about the compatibility of the planned development of the thermal park, based on investment plans by individual utilities, with the policy decisions taken in relation to wind generation. The key areas of concern relate to: the issue of whether sufficient flexibility will exist in the power market to permit the intermittent and uncertain wind infeeds to be accommodated without load shedding or expensive wind curtailment; and what will be the impact on power prices and thus on the business cases for new investment. Scope of work 2.4 In order to gain more insight into these issues, EnergieNed, on behalf of its member firms, has appointed Frontier to carry out a study of the year 2020 in order to explore the ability of the Dutch and North West European power markets (corresponding to the region known as Central West Europe (CWE)) to handle fluctuating wind power and its implications. By simulating the operation of the power market in 2020 under a small number of scenarios, and conducting related analysis, the study is intended to answer the following questions: Introduction

30 20 Frontier Economics April 2010 What is flexibility can it be defined or quantified? Will the Dutch and/or CWE market be able to handle fluctuating supply of significant amounts of wind power through market dynamics? Which role do the CWE market and market coupling play? What will be the impact of fluctuating wind power on electricity prices in peak and off-peak hours? How might this affect the case for investing in new plants? What will be the impact of fluctuating wind power on required reserve capacity? Is there an impact on energy saving from CHP (negative or positive)? If so, can this be quantified? Is there any ground for arguments such as CHP as perfect partner, the need of storage, only IGCC in case of new coal? Are there any other policy relevant implications which have to be addressed? Is there a need for additional policy measures and which? 2.5 The modelling and analysis presented in this report attempts to answer all of these questions. 2.6 The terms of reference also asked us to review experience in other EU countries with high rates of wind integration and CHP, especially Denmark. We have in addition considered Spain and Germany. 2.7 The study is also closely related to two other, currently ongoing 17, studies which are being conducted in parallel. These are: the KEMA study of the need for Large Scale Energy Storage in the Netherlands; and the Ministry of Economic Affairs study on fuel mix in the generation sector by The study is also of interest to the Ministry of Environment which is responsible for meeting the 2020 objectives aimed at limiting climate change. 17 There is no full citation of this study available yet. Introduction

31 April 2010 Frontier Economics 21 Organisation of report 2.9 Following this introductory section our report is organised as follows: Chapter 3 sets out our understanding of the meaning of flexibility and the methodology we have adopted to assess whether it is adequate and to answer the questions raised above; Chapter 4 describes the construction of the scenarios that we have examined including the projections of fossil fuel prices; Chapter 5 provides an overview of the main results from the modelling work and describes the sensitivity cases we have analysed: Chapter 6 draws on the general results and more specific data to provide answers to the questions raised by EnergieNed; Chapter 7 discusses market dynamics and the measures needed to ensure that rights to the flexibility that exists can be efficiently reallocated among the programme responsible parties; and Chapter 8 set out our conclusions, including our views on potential additional policy measures There are supporting annexes providing information on the data used in the modelling and on experience with wind integration in other EU countries with high rates of wind penetration on which we draw in the report. Introduction

32

33 April 2010 Frontier Economics 23 3 Our approach 3.1 We answered the questions raised by EnergieNed by applying both quantitative and qualitative analysis. For the quantitative aspects we use a model based approach which allows us to calculate the optimised hourly dispatch of power plants in the CWE area for the year 2020 given certain assumptions on plant capacities, fuel prices etc. and subject to a number of constraints. 3.2 In our qualitative analysis we deal with questions of market design, access to flexibility and related issues in order to link the quantitative results with the real world vision for wind integration in At the beginning of the study we built up a clear and consistent view of the situation in the CWE power system in 2020 and how this might best be modelled to show the impact of fluctuating wind generation output. Specifically, we assembled plant and load data (capacity balances for CWE regions) in 2020; defined key drivers including fuel and carbon prices and reserve requirements and reviewed relevant Dutch energy policies with EnergieNed; and undertook the technical adaptation of our despatch tool to enable us to simulate system operation in the CWE countries in The modelling was complemented by a review of experiences from other EU countries with high wind penetration; and thinking about market dynamics and the related questions of future market design and market integration. 3.5 Together, this work gave us the information to answer the questions raised by EnergieNed and to reach conclusions on the flexibility of the Dutch power system and its ability to accept higher rates of intermittent and unpredictable wind generation. 3.6 Our overall approach to the work is shown in Figure 6 below. Our approach

34 24 Frontier Economics April 2010 Figure 6. Our approach Assemble plant and load data Define and agree scenarios Adapt system despatch model Lessons and developments elsewhere Model runs and analysis of interim results Thinking on market dynamics Answers to Questions and Conclusions Source: Frontier Economics 3.7 We describe the main elements of this approach in greater detail below. Plant and load data for CWE area in Our starting point for plant data was the information obtained from nonconfidential sources that we have used for each of the relevant countries on other assignments. In the case of the Netherlands, we needed to model the generation park in more detail than we have done before and to this end were benefited from input from EnergieNed and from experts at Nuon in order to assemble a detailed list of conventional and CHP plants with the relevant capacities (heat and power in the case of CHP) and date of commissioning. 3.9 In the case of CHP plants, we made assumptions on the proportion of the local heat load that would be met by the plant itself and how much would be met by Heat Only Boilers (HOBs). We built into the data a 10% excess of heat capacity based on HOBs. Nuon also assisted with data on typical heat load profiles for CHP plants The intermittent nature of wind was modelled using randomisation functions derived from hourly German wind data and then scaled for onshore and offshore Our approach

35 April 2010 Frontier Economics 25 wind to reach the load factors reported in other studies of wind in the Netherlands Further details of the data used are set out in Chapter 3 and in Annex 1. Define and agree scenarios 3.12 The definition of the scenarios we have used in our modelling work is presented in Chapter 3. These were discussed at the first Steering Group meeting and a number of amendments were made in the light of comments received. Adaptation of CWE system dispatch model 3.13 We first describe the main features of our system despatch model and then explain how we adapted it for the purpose of the study for EnergieNed The model is a linear, mixed integer optimisation tool that is normally applied to the whole of Western Europe 19. Adjacent regions are considered as satellites and the border price for these is taken to the marginal cost of the relevant technology at assumed fuel prices for the purpose of deciding whether to import or export across the available interconnector capacity. It models chronological hourly loads taking into account available generation capacity which is given to the model inclusive of planned maintenance (unavailability of plant) and is usually considered in the form of clusters of different technologies; any available storage capacity; fuel prices and the cost of carbon emission in the case of thermal plant (including technical data on any plants with CCS); the thermal efficiency of plants, including the impact of lower efficiency for part load operation; start up costs and variable O&M costs; the ability of the plant to provide automatic (fast response) reserve and manual (instructed) reserve; and the minimum stable generation at which each plant can run The model finds the least cost solution subject to the following constraints: 18 We assumed a rather windy year with on average a 36% load factor for the Dutch wind park. Correlation of wind in-feed in countries of the CWE region is assumed to be about 80%. 19 We also include some semi-continuous variables to be able to account for minimum load restrictions for power plant operation. Our approach

36 26 Frontier Economics April 2010 meeting hourly residual demand (demand minus infeed from wind and other intermittent sources) in each country and the local heat demand associated with each plant (industrial, district heating or greenhouse); interconnection capacity between each country based on NTC capacities in each direction; and total requirements for automatic and manual reserve The model does not assess whether new investment is required or whether there is a surplus of plant on the system. If required, fixed costs for plant (capital and O&M) must therefore be considered outside the actual model It is important to note that the model operates with the assumption of perfect foresight of wind, load and plant conditions in future hours. The results for the CWE region therefore approximate to perfect market integration and optimal use of interconnection capacity between TSO control areas. The flexibility which is available within the modelled system is used perfectly The model is written in General Algebraic Modelling System (GAMS) and inputs and outputs are based on Excel. The program uses ILOG s LP/MIP solver CPLEX For the purpose of this study we adapted the model in the following ways: the geographical scope was restricted to the five CWE countries (The Netherlands, France, Belgium and Germany) with all other countries/regions being treated as satellites; therefore, we increased the granularity of the model in the Netherlands. Plants with a capacity in excess of 60 MW were modelled as individual generating units and clusters were only used for small units such as greenhouse motors; a mixed integer condition was introduced to allow for minimum stable generation and a specific ramping constraint was also applied to thermal plant; and additional functionality was added to model the heat to power ratio on CHP plants and to include heat to power loss factors for those plants considered to be flexible with respect to the ratio of heat and power production. In terms of meeting heat demand, the model chooses the optimum mix of CHP plant and HOBs The updated model was tested before being put to use. Results have been benchmarked against existing Dutch Central Bureau of Statistics (CBS) and capacity and load data from other publications. Our approach

37 April 2010 Frontier Economics 27 Developments in other EU countries 3.21 We focussed our analysis of experience with managing wind infeeds on Denmark West, which already has wind penetration of over 20% in its energy balance, on Germany and on Spain. In the case of Denmark and Spain we carried out phone interviews with the TSOs in order to understand recent developments in how wind is integrated into the system. We also draw on our own knowledge of developments in the case of Germany. This material is presented in Annex 2 and we draw out the lessons in the main text of our report. Market dynamics 3.22 Wind generators in the Netherlands, unlike those in Germany, are exposed to imbalance charges through the Programme Responsible Party (PRP) to whom they are attached. The PRPs have a strong incentive to forecast generation output and maintain a balanced programme as they approach real time. The characteristics of wind generation makes output difficult to forecast with accuracy ahead of real time, but experience indicates that forecasts improve gradually in the period from t-36 hours down to real time. There is nevertheless significant forecast error even at 3-4 hrs ahead of real time. To address this problem the PRPs and, close to real time, the TSO will need access to flexibility In this study, we consider flexibility to be the availability of resources, from the day ahead of delivery to the time of delivery, that can change their level of production or demand by defined amounts and sustain this position for a period of at least one hour in a reliable manner As noted above, the model assumes perfect markets and perfect market integration within the CWE region. In practice, therefore, achieving the results reported by the dispatch model will depend on the existence of efficient markets to permit the reallocation of rights to flexibility from those with too much to those with too little In order to assess how this might be done we considered experience to date with market integration in the CWE area and plans for the future. We also looked at experience in the Nordel area (Scandinavia) where integrated intra day and TSO balancing markets already exist for the region as a whole. Our approach

38

39 April 2010 Frontier Economics 29 4 Definition of scenarios 4.1 This chapter explains how we developed the scenarios for 2020 to be modelled using our system despatch tool. 4.2 The basic ingredients of a scenario for 2020 are the following: the wind generation capacity on the system; projected coal and gas prices; the load forecast; reserve requirements; thermal plant additions and retirements which define how the existing park is projected forward; and any changes in interconnection capacity with neighbouring countries. 4.3 We consider each of these in turn in order to define the scenarios for modelling purposes. Wind generation capacity 4.4 The purpose of the study is to explore the impact of the policy of providing incentives sufficient to induce construction of 12 GW of wind generation capacity by It follows that the base scenario must therefore have this wind generation capacity. We have assumed that the capacity is split 50:50 between onshore and offshore wind the significance is that offshore wind has a higher load factor. However, in order to understand the implications of having such a significant contribution from wind generation, we also wanted to consider an alternative scenario which reflected a more moderate increase in wind generation from the present level of 2.GW but that was much less than implied by the policy target of 12 GW. 4.5 Accordingly we formulated a low wind scenario comprising 6 GW of wind generation (4 GW onshore and 2 GW offshore). As noted below, this corresponds to the maximum capacity that we understand can be added to the system without providing additional manual reserve to deal with the uncertain nature of wind output. Later in this chapter we consider the implications for the balance of the generation park in the Netherlands. 4.6 We have focussed our work on the 12 and 6 GW wind scenarios, treating variations in other factors as sensitivities on the base scenario. Definition of scenarios

40 30 Frontier Economics April We have assumed development of renewable generation in other CWE countries in line with current policies. These have been kept common to both our scenarios so that the implications of different levels of wind generation for the Netherlands are clearly in focus. Fuel prices Gas prices 4.8 In order to make projections of gas prices in 2020 (in 2009 prices) we have reviewed recent projections for crude oil prices over the next 20 years, in particular we took the updated 2009 reference case published by the US Department of Energy Information Service which is slightly higher than the earlier IEA reference case; projected gas prices to Germany at 62% of the crude oil price in energy terms in line with ratios shown in the IEA projections; converted the result to euros at a constant exchange rate of 1=USD1.30; converted from the HHV basis used to quote gas prices to LHV used to calculate generation costs (all our efficiency figures are based on the LHV value); and added 1 per MWh th for onward transport to Netherlands. 4.9 The result is an annual average gas price in 2020 of 34.2 per MWh th at the LHV in 2009 prices. In order to obtain a seasonal profile, we reviewed data on the average monthly TTF prices from and applied the results to obtain seasonal adjustment factors for the average annual gas prices. The range is from 88% in spring to 112% in winter. Coal prices 4.10 We proceeded in a similar fashion to obtain coal prices. We have projected coal FOB Richards Bay at 30% of the crude oil price; added USD15 per tonne to obtain an ARA CIF price and a further USD 5 per tonne for unloading and inland transport; converted the result to obtain a price in euros per MWh th using the same exchange rate assumption as for gas The result is a price in 2020 in 2009 prices of 17 per MWh th delivered to plants in the Netherlands. Definition of scenarios

41 April 2010 Frontier Economics We also need projections for the price of carbon (i.e. the price of an EUA) which we model as a variable cost of generation at the specific emission factor relevant to the fuel for each power plant. We assume an increase in carbon prices compared to today s price level. The intention is to reflect the carbon reduction targets agreed by the EU and the assumed fuel price level in The result is a carbon price of 28 per tonne (EUA) in 2020 in 2009 prices Assuming a coal plant efficiency of 40% and CCGT efficiency of 53%, these projections indicate that coal is always the cheaper source of generation, although gas-fired power is almost as cheap in the spring when gas prices are at a seasonal low 20. Figure 7 show the relative position for each fuel graphically. Figure 7. Projected cost of power generation from gas and coal, including CO2 prices, in /MWh NL CCGT ann. Avg CCGT spring CCGT winter Coal Source: Frontier Economics 4.14 We have also considered a sensitivity case in which increases in the price of coal and carbon are sufficient to make gas-fired generation more attractive than coalfired generation, flipping the merit order. Load forecast 4.15 In order to have a value for Dutch demand in 2020 we reviewed the latest projection of demand in TenneT s Security of Supply Monitoring Report 20 We used an emission factor for coal of t/mwh_th and gas of t/mwh_th Definition of scenarios

42 32 Frontier Economics April 2010 published in June This takes account of the fall in demand due to the recession and then projects demand in 2016 using an annual growth factor of 2%, starting from an expected base of 113 TWh in TenneT also confirmed to us that the data are for total demand, including demand met by on site generation. We have extrapolated the load for 2016 out to 2020 using the same rate of growth to give a demand forecast of about 138 TWh. This compares with the Global-Economy forecast for 2020 of 156 TWh included in the Energy Agreement We have assumed that the load factor remains constant at 68.6% and therefore the projected peak demand in 2020 is 22.9 GW We note that our assumption of unchanged load shape makes no allowance for potential development of electric cars, which are expected to be recharged at night, or of any expansion of heat pumps and time of use tariffs, both of which might have a flattening effect on the load curve Since the implications of higher wind generation depend primarily on the residual load (i.e. load less renewable generation) and because we have already decided upon a 6 and 12 GW scenario for wind, we do not consider any sensitivity cases for load itself. Reserve requirements 4.19 Our dispatch simulation model optimises the allocation to power plants of up to two categories of reserve but the total reserve requirement must be defined exogenously The requirement for primary and secondary reserves depends on UCTE operational rules. Both of these reserves are activated automatically and we have allocated both to a single category. In total we have provided for 451 MW Tertiary reserve must also be held to replace the primary and secondary reserve. This is activated manually Based on review of other studies and discussions with TenneT, our understanding is that the normal reserves are sufficient to deal with uncertain wind output up to a certain point. Once this point is reached, additional reserve must be provided. The conceptual position is shown in Figure TenneT told us that they currently provide manual reserve for the largest single infeed which at present is the NorNed connector of 700 MW. Of this amount, some 300 MW is currently provided by demand response leaving 400 MW to be 21 Energie Ned (2007); Energieagenda Energie Expected demand for 2020 is based on the GE scenario of ECN and the Netherlands Environmental Assessment Agency, which is reported in Referentieramingen energie en emissies (ECN/MNP, 2005). Definition of scenarios

43 April 2010 Frontier Economics 33 provided on generating plant. In 2020 the largest single infeed is expected to be the 1 GW BritNed interconnector. Assuming no change in demand response, this implies a need to find 700 MW of manual reserve from generating plant The TenneT Quality and Capacity Plan for reports work by KEMA which suggests that the system can probably manage without additional manual reserve at wind penetrations up to 6 GW. We have adopted this figure for our own modelling. Beyond this point, studies from the UK and Germany 22 suggest that additional manual reserve equal to about 10% of the incremental wind generation capacity is needed. This suggests that in the 12 GW case, the total manual reserve needed is equal to = 1300 MW. Figure 8. Relationship between manual reserve requirements and wind generation capacity additional reserve required, if wind capacity exceeds this amount (6 GW in NL) reserve (GW) reserve needed for non-wind reasons wind capacity (GW) Source: Frontier Economics 4.25 We have qualified different plant technologies to provide the automatic and manual reserve based on experience of modelling power systems elsewhere in Europe. In the base case we assume that CHP plant can act as a source of upward reserve when not fully loaded (i.e. a proportion of the capacity between actual output and maximum capacity can count as reserve) on the basis that the heat load can be met with some flexibility by use of HOBs To account for the fact that ramping constraints and minimum load condition limit the flexibility of plant technologies, we allow for only 20-60% (depending 22 National Grid, UK, Operating in 2020 (2008) Consultation and dena grid study, Germany (2005) Definition of scenarios

44 34 Frontier Economics April 2010 on plant technology) of the free capacity of plants running at part load to act as potential sources of reserve. In addition to this spinning reserve, we recognise that some reserve can come from very flexible plants like open cycle gas turbines or Compressed Air Energy Storage (CAES) which can be started and ramp up to a target production level within 15 minutes if called upon by TenneT We derive a price indicator for reserve products which aims to reflect the value of reserve or in other words the extra costs introduced to the system from that reserve requirement. Those costs mainly come from holding reserve on plants with low variable costs to provide upward reserve or from a requirement to operate flexible plants to be able to provide downward reserve. Evolution of the thermal plant park and supply curve 4.28 In order to assist comparisons between the two wind scenarios, we modelled the overall plant park to have similar levels of capacity adequacy with respect to demand in the Netherlands. To do this we adapted a method which has been used by UCTE to review system adequacy. The method was to consider demand for capacity in the Netherlands to be the peak load, plus required reserve; to assume that, for thermal plants, the reliable and guaranteed capacity ( capacity credit of plants) is equal to 90% of the nameplate net plant capacity; for wind generation to assume that reliable capacity ( capacity credit ) is equal to 10% of the nameplate capacity; and to use a 5% margin of reliable capacity (after having allowed for the awarded capacity credit) over demand for capacity as the definition of adequacy Note that this method takes no account of interconnection capacity between the Netherlands and neighbouring countries which could serve to provide further reserves To assess how the thermal plant park would evolve we proceed as follows: reviewed data on the capacity and commissioning date of major generating units and take account of comments from EnergieNed; compared total capacity with data from the Dutch CBS on total installed capacity and added clusters of small CHP plants to represent the large number of small gas motors and other small CHP plant on the system; Definition of scenarios

45 April 2010 Frontier Economics 35 projected future retirements based on standard plant lifetimes, except in the case of the Borssele nuclear plant which we assume will continue to operate post 2020; added major new plants now under construction as detailed in the Annex 1 but excluded plant considered only be planned on the basis that it is likely that some of the currently planned plants will not be realised after the earlier investment plans have become more certain; and following discussion with the EnergieNed Steering Group, added a new nuclear plant with a capacity of 1000 MW The results of applying this approach in the 12 GW case are shown in Figure 9. The main points to note are: demand for capacity increases steadily in line with the growth in demand and the need for additional reserve as a result of the increases in wind generation on the system; existing capacity reduces gradually as a result of plant retirement; new plant additions rise gradually as new plant comes on stream; wind generation contributes very little to the system adequacy since its reliability is so limited; and overall there is more than adequate plant in the middle of the period (i.e. capacity column extends above the red line) with the surplus declining so that by 2020 there is an additional margin of 6.3% above that considered to be required. Definition of scenarios

46 36 Frontier Economics April 2010 Figure 9. Projected evolution of system adequacy in the Netherlands (12 GW case) 30,000 25,000 Aggregated capacity (MW) 20,000 15,000 10,000 Existing Under construction 5,000 Onshore Wind Demand Offshore Wind Demand + 5% UCTE Margin + Reserves Source: Frontier Economics 4.32 Details on capacity balances for other CWE regions can be found in Annex 1. We assume a life time extension of nuclear plants in Germany (40 years) and Belgium (old plants are running up to 50 years). For France we assume no net change in nuclear capacity from the present (additions equal retirements). Wind power is assumed to grow strongly in all CWE countries: in 2020 we assume a total of 45GW of wind power installed in Germany, 3.5GW in Belgium and 23GW in France. For all regions we expect more onshore than offshore wind capacity We note that in practice generators may choose, in this situation, to retire some plant earlier than the standard lifetimes would indicate to avoid the excess of capacity in the middle of the period. Our specific modelling work for this particular assessment says nothing about the economics of having more or less capacity on the system. However, the plant park assumptions used do impact the system marginal costs reported by the model Another important point is that the simple margin of capacity over demand, without any deratings for reliability, is just over 80%. This is a consequence of the need to have thermal plant on the system to deal with those occasions when there is very little capacity contribution from wind. The results of the modelling described in Chapter 5 show the implications of this situation for load factors of new thermal plant The capacity projection above was for the 12 GW scenario. In the case of the 6 GW wind scenario, there is no longer a need for 600 MW (10% of 6 GW) of manual reserve. On the other hand, the reliable contribution of the additional wind capacity was only 10% of 6 GW. These two effects cancel each other out Definition of scenarios

47 April 2010 Frontier Economics 37 and the same projected thermal park is no more or less adequate using our criteria than in the 12 GW case. We have therefore made no change to the plant park for the low wind scenario Given the plant park described above for 2020, we have derived a marginal cost supply curve for the park as shown in Figure 10. This is helpful in understanding the results of the modelling. The points to note are: the output from the wind generation is highly variable, shifting the supply curve to the right or the left as wind generation increases or reduces this is indicated by the brown double headed arrow; there is a long plateau of coal plant with similar marginal costs depending on the wind output, this plateau extends from minimum to maximum demand, before allowing for exports; and the tail of the supply curve comprises CCGT and OCGT plant, both with significantly higher costs. 23 This assumption holds for the overall capacity balance requirement which we look at here. The model runs show that we not only need guaranteed capacity in terms of covering peak load but that plant flexibility is also an issue if we look at reserve requirements. One can also assume that for the 12 GW case investors would tend to prefer investment into CCGT or OCGT plants rather than into coal or baseload plants but this depends strongly on the long term view which we do not focus on in our analysis. Therefore (and to allow for a clear comparison of dispatch effects of the 12 GW scenario in 2020) we keep the remaining plant park identical in both cases. Definition of scenarios

48 38 Frontier Economics April 2010 Figure 10. Supply curve 12 GW scenario NL; Min. load Max. load OCGT /MWh CHP Flex Nuclear New coal and IGCC CHP Inflex Greenhouse motor Old coal CCGT 20 0 Wind, Other Re Potential Range of Wind Input 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 MWe Source: Frontier Economics Interconnection capacity 4.37 Our model simulates the optimal dispatch of plant in the CWE region subject to constraints on interconnection capacity. We also consider exchanges with satellite countries based on the marginal technology in those countries and the capacity of the relevant interconnectors In the case of the synchronous AC interconnectors between the Netherland and Belgium and Germany, the aggregate NTC capacity at present is in the range 5.4 to 6.3 GW, depending on flow direction and season. However, for system security reasons there is an aggregate limit of 3.85 GW of NTC capacity for the Netherlands agreed between the TSOs concerned By 2020, we expect that: a new interconnector to be commissioned between Wesel and Doetinchem at 380 kv which will increase capacity between the Netherlands and Germany by between 1 and 2 GW according to RWE statements on the TenneT web site; internal grid constraints which in practice may limit use of interconnectors will be removed by new investment; and flow based market coupling will be introduced within the CWE region which is expected to make more effective use of available transmission capacity and Definition of scenarios

49 April 2010 Frontier Economics 39 leads to a less conservative approach than that reflected in the current NTC values and aggregate limits Against this background, we have therefore assumed that by 2020 there will be 6 GW of useable interconnector capacity in total on the links from the Netherland to Germany and to Belgium, close to the present aggregate NTC values 24. But we have also considered the impact of a lower value in a sensitivity case In relation to the HVDC links we assume that BritNed will be commissioned before 2020 with a capacity of 1 GW (we do not consider the higher peak capacity of 1.35 GW that is mentioned in some documents) and that NorNed will remain at its present capacity of 0.7 GW. We have not considered the proposed COBRA interconnector between the Netherlands and Denmark which has yet to be approved in our base case scenario. However, we ran an additional case study where we explicitly analysed the effect of the COBRA cable on wind integration in the Netherlands In total we therefore consider for the 12 GW base case an interconnection capacity of 7.7 GW between the Netherlands and its neighbours and satellite countries. Summary of scenarios 4.43 In summary, we therefore consider two scenarios: a base scenario with 12 GW of wind capacity divided 50:50 between offshore and onshore; and a low wind scenario with 6 GW of wind capacity of which 4 GW is onshore and 2 GW is offshore For the reasons explained above, other assumptions are common to both these scenarios. However, changes in some of the other key variables are considered in sensitivity cases. 24 Today's sum of listed NTC values overestimates the transfer capacity available to the market by Amprion and TenneT. 25 Details on applied methodology and key findings on the impact of COBRA can be found in the annex. Definition of scenarios

50

51 April 2010 Frontier Economics 41 5 System dispatch simulation for 2020 Results for the 6 and 12 GW scenarios 5.1 We now present the results of our modelling of the 6 and 12 GW wind scenarios for 2020 described in Chapter 4 and those for a number of sensitivity cases used to explore the effect of changing important variables. This discussion provides the foundation that we draw on to answer the detailed questions raised by the Terms of Reference for this Assignment in Chapter 6. Energy balances 5.2 The energy balance in the 6 GW case is shown in Figure 11. The production delivered by the different technologies is shown by the coloured bars in the stacked column on the left. Nuclear and non-wind RES-E (renewable energy sources - electricity) contribute a baseload of 23 TWh in 2020, but the major sources of energy are coal-fired generation and gas-fired CHP. CCGT makes a much smaller contribution. Wind generation is shown as a green bar towards the top of the column and contributes 17 TWh, equivalent to 12% of Dutch demand. The coloured area at the top of the column called flexed CHP is the additional production from CHP plant as a result of moving away from the minimum power to heat ratio. There is no wind curtailment. 5.3 International trade is represented by exports of 44 TWh and imports of 19 TWh, an overall net interchange of 25 TWh. As discussed later on, a high proportion of the gross imports are in fact transit flows that are re-exported to Germany. System dispatch simulation for 2020

52 42 Frontier Economics April 2010 Figure 11. Energy balance in the 6 GW scenario Netherlands; 2020 Production and demand in TWh/a Exports Imports LOAD Supply 6 GW Demand 6 GW Supply and Demand flexed CHP Wind Imports/Exports CCGT gas CHP coal other RE Nuclear Source: Frontier Economics 5.4 Figure 12 below then shows the same energy balance in the 12 GW case. Wind generation now increases by 21 TWh, more than double because so much of the additional capacity (4 GW) is assumed to be offshore. The extra wind energy is absorbed by less generation from CCGT and coal plant, more exports and fewer imports. Therefore, in the 12 GW wind scenario, the Netherlands would achieve an even stronger net export position than in the 6 GW wind scenario. 5.5 In this scenario, there is no wind curtailment visible on the graph but the detailed results show that total wind curtailment of 0.12 TWh does occur and it arises in 171 hours of the year. System dispatch simulation for 2020

53 April 2010 Frontier Economics 43 Figure 12. Energy balance in the 12 GW scenario Netherlands; 2020 Production and demand in TWh/a Imports Exports LOAD Supply 12 GW Demand 12 GW Supply and Demand flexed CHP Imports/Exports Wind CCGT gas CHP coal other RE Nuclear Source: Frontier Economics Operating profiles 5.6 We now look at the operating profiles in typical weeks of the year 2020 for the 6 and 12 GW wind scenarios. 5.7 Figure 13 shows the results for the 6 GW wind scenario for a typical winter week (starting with a Monday). This is an area graph showing different production from different technologies in the Netherlands with load added as a red line. Production above the red line is exported and white areas below the red line represent net imports (none in the winter period) The main points to note with regard to flexibility are: nuclear operates as baseload plant and output is flat while non-wind renewables show some daily variation; CHP plants show the daily variation associated with the heat demand curve there is no observable difference between flexible and inflexible CHP; System dispatch simulation for 2020

54 44 Frontier Economics April 2010 coal-fired generation provides much of the flexibility to respond to changes in load and wind output, regularly shutting down at night and over the weekend 26 ; CCGT plant only runs briefly in peak periods and appears to mainly serve export demand; and we have shown wind output at the top of the picture the better to show the flexibility of other plant. The wind variation is difficult to see in detail but output is clearly much lower on Monday. Figure 13. Production profile in a winter week for 6 GW scenario Netherlands; ,000 25,000 Generation in MW 20,000 15,000 10,000 Wind infeed ocgt ccgt coal CHP flex CHP inflex Other RE nuclear Load 5, Hours of year Source: Frontier Economics 5.8 The same type of graph is shown for the 12 GW scenario for the same week in Figure 14. The large increase in wind output has almost forced CCGT generation to zero, coal-fired generation has significantly reduced and net exports have increased. 26 This incurs additional start up costs for coal plants. We also ran a sensitivity case, described later, where we assume that additional technical constraints limit the flexibility of coal plants to close down over night. System dispatch simulation for 2020

55 April 2010 Frontier Economics 45 Figure 14. Production profile in a winter week for 12 GW scenario Netherlands; ,000 25,000 Generation in MW 20,000 15,000 10,000 Wind infeed ocgt ccgt coal CHP flex CHP inflex Other RE nuclear Load 5, Hours of year Source: Frontier Economics 5.9 We now contrast this winter week with a week in July Figure 15 shows the 6 GW scenario. The main points to note are: wind production is noticeably lower in the summer, as is output from other renewable sources; CHP production in summer is much lower than in winter due to lower heat demand, making room for other conventional plants; coal-fired plant is still providing much of the flexibility but only some plants are shutting down at night; CCGT plant has more production than in the winter week but still only operates in peak periods; and there are days of net exports and at least one with net imports (white area beneath the red load line). System dispatch simulation for 2020

56 46 Frontier Economics April 2010 Figure 15. Production profile in a summer week for 6GW scenario Netherlands; ,000 20,000 15,000 10,000 5, Generation in MW Wind infeed ocgt ccgt coal CHP flex CHP inflex Other RE nuclear Load Hours of year Source: Frontier Economics 5.10 The profile for the same week in the 12 GW scenario is shown in Figure 16. The higher wind output is very apparent. There is less coal-fired generation and significantly reduced CCGT generation. Net exports are higher and there are no net imports. System dispatch simulation for 2020

57 April 2010 Frontier Economics 47 Figure 16. Production profile in a summer week for 12 GW scenario Netherlands, ,000 25,000 Generation in MW 20,000 15,000 10,000 Wind infeed ocgt ccgt coal CHP flex CHP inflex Other RE nuclear Load 5, Hours of year Source: Frontier Economics Generation under the filled load duration curve 5.11 One way to look at the annual results is to consider how thermal generation is used to meet the residual load 27. We have calculated the residual load and then sorted it, and the corresponding generation, in descending order. Were the Netherlands not connected with other countries, this might be expected to produce bands of generation under the residual load corresponding to the utilisation of different technologies at different levels of demand. However, as Figure 17 shows, for the 12 GW case the importance of interchanges with neighbouring countries, which also have variable wind output, gives the bands corresponding to flexible plants very fuzzy edges. Nevertheless, the picture emerges of coal as the lowest cost form of flexible generation with more expensive gas generation used at higher residual load levels only. There is significant production in support of net exports across the whole residual load curve. 27 By residual demand we mean load less wind and less other renewable generation. System dispatch simulation for 2020

58 48 Frontier Economics April 2010 Figure 17. Thermal production ordered by the residual load duration curve for 12 GW scenario Netherlands; ,000 20,000 ccgt coal CHP flex CHP inflex nuclear res load 15,000 MW 10,000 5, hours of the year sorted by residual load Source: Frontier Economics System operating costs and emissions 5.12 We now consider the impact on system operating costs (fuel, carbon costs, start up costs and variable operating costs). Note that we do not consider capital costs or fixed O&M for thermal power plants nor for the projected wind park. Figure 18 shows the impact of adding 6 GW of wind generation. There is a net cost reduction of some 1.2 billion, out of a total of about 35 billion for the CWE region as a whole. The main cost saving is in fossil fuel. Perhaps the most interesting feature is that there are large costs reductions in Germany as a result of increased exports from the Netherlands and smaller reductions in Belgium and France. It is also noteworthy that part load operating costs in the Netherlands increase as a result of the increased flexible plant operation needed to deal with higher levels of intermittent wind generation. System dispatch simulation for 2020

59 April 2010 Frontier Economics 49 Figure 18. Changes in system operating costs between the 6 to 12 GW scenarios DE NL BE FR Net costs developments in mio EUR Partload costs Startup costs Power and heat generation CHP Power generation costs non CHP Region Source: Frontier Economics 5.13 Turning to carbon emissions, Figure 19 shows the absolute level of emissions in the four CWE countries in the 12 GW scenario and the additional emissions in the 6 GW scenario (blue area at top of column). In total the power sector in the CWE 28 area emits about 357m tonnes of carbon in the 6GW scenario in 2020 (in comparison to roughly ~500m tonnes at present). The additional 21 TWh of wind displaces fossil generation emitting some 11m tonnes of carbon, a marginal displacement rate of about 0.5m tonnes per TWh. This corresponds to a mix of gas and coal-fired generation, as expected. Of the displaced carbon, slightly more is displaced in Germany than in the Netherlands due to the increase in exports and the relatively greater carbon intensity of generation in Germany. The impact on Belgium is very small. Again, this reflects the fact that additional wind generation displaces less carbon the cleaner the existing power system. These results do not take into consideration differences in interchanges with satellite regions between the two scenarios. The additional 6 GW of wind capacity in the 28 Note that we do not model pure heating plants or industrial process emissions. Emission of 357 million t by electricity generation within the CWE area (compared to about 500 at present) would imply that the CO2 reduction target for 2020 would be met. This also broadly implies that the price of carbon (28 /ton) which was assumed reflects a fair value for reductions in The CO2 emission which we estimate for electricity generation in the Netherlands by 2020 is higher than the present level. This increase, however, is compensated by reductions elsewhere in the CWE region. Overall our modelling indicates that CO2 within the CWE will decline in line with the EU s 20% reduction target for System dispatch simulation for 2020

60 50 Frontier Economics April 2010 Netherlands would trigger an increase in net exports to the satellite regions by 6 TWh (from 20 to 26 TWh). This will imply further carbon and cost reductions in these countries, as well. 29 Figure 19. Level of CO2 Emissions in the 6 and 12 GW case 2020 Emisions from power sector in Miot/a DE NL BE FR Region reduction 6 to GW case Source: Frontier Economics Exports and imports 5.14 We have referred to the pattern of exports and imports in the discussion of the energy balance. Figure 20 shows the gross export and imports for the Netherlands in the 12 GW scenario. The main points to note are: exports are constrained by the maximum interconnector capacity of 7.7 GW in a number of hours, especially in winter; exports are less pronounced in summer, when surplus generation is lower, and imports are more pronounced; 29 A reduction in CO2 emission from electricity generation within the Netherlands, the entire CWE area or satellite regions in the model does not mean that overall EU CO2 emissions will be reduced as well. Less CO2 from electricity generation merely implies a lower demand for CO2 allowances in the Emissions Trading Scheme (ETS) from these modelled generators and possibly lower CO2 prices. The volume of allowances in the market overall is, however, given by the volume of the EU permit allocations. A reduction in the modelled region could, therefore, lead to higher emissions elsewhere within ETS, as long as the overall EU CO2 cap is not violated. System dispatch simulation for 2020

61 April 2010 Frontier Economics 51 there are significant daily fluctuations which are primarily due to changes in wind generation in the Netherlands and in its neighbours; and when the interconnector capacity is constrained, all flexibility must be provided within the Netherlands. Figure 20. Gross exports from and imports in the 12 GW scenario Netherlands; Exchange in MW 4000 exports imports Hour of year Source: Frontier Economics 5.15 In the 12 GW case almost all of the imports are transit flows in the sense that all but 0.2 TWh of the 12 TWh of imports arise in hours when exports were higher than the energy imported. These flows occur from Belgium to Germany and vice versa. Table 1 shows the full matrix of exports and imports. System dispatch simulation for 2020

62 52 Frontier Economics April 2010 Table 1. Imports from and exports to each CWE country and satellite 2020 To From DE NL BE FR CH AT CZ PL DK_W GB ES NE Total DE NL BE FR CH AT CZ PL DK_W GB ES NE Total Source. Frontier Economics. Columns show imports and rows show exports Heat balance 5.16 Finally, Figure 21 shows the heat balance for the Netherlands. Heat demand from the different sectors is shown on the left, a total of 76 TWh th. On the extreme right the column shows the production of heat from different CHP sources, at the standard heat to power ratio, and from HOBs. In practice, the modelling indicates that it was more economic to vary the heat to power ratio of flexible CHP in order to produce less heat and more power (than would have been the case had system marginal costs been significantly lower). The foregone heat production is shown at the top of the central bar and equals 17 TWh th yielding an additional 2.8 TWh of electricity production. This is little different to the 6 GW scenario and indicates that the change in wind generation has little impact on production from the CHP park. System dispatch simulation for 2020

63 April 2010 Frontier Economics 53 Figure 21. Heat balance in the 12 GW scenario Netherlands; Flexible heat to power ratio HOBs belonging to inflexible plants HOBs belonging to flexible plants Inflexible heat to power ratio Flexible Heat Adjustments Actual Supply District heating Greenhouse Industry 0 Demand Flex Heat Adjustments Production with at standard HtP Source: Frontier Economics Sensitivities 5.17 We noted in our review of the results that international exchanges and conventional thermal generation are the main sources of flexibility on the system. We therefore ran some sensitivity cases to analyse the effect of adding to, or reducing, these sources of flexibility. We looked at the following effects: More interconnector capacity to France - increase of interconnector capacity of 500 MW from Netherlands to Belgium and onwards to France. We thought that hydro power on the French system might be used to store energy and shift generation to periods of higher demand; Merit order switch an increase in coal and carbon prices sufficient to lead to a merit order switch (variable costs of gas generation becoming cheaper than coal-fired generation) which then increases load factors of flexible CCGT plants; Less interconnector capacity to Germany and from Germany to Central and Eastern Europe reduction of 700 MW interconnector capacity between Netherlands Germany and 50% decrease in interconnection capacity from Germany to satellite areas to the South and East; System dispatch simulation for 2020

64 54 Frontier Economics April 2010 Inflexible coal-fired plants we forced non-chp coal-fired generation to run at least at minimum load to reflect the perceived technical and economic constraints on two shifting these plants; and Higher reserve requirement (leading to wind curtailment) we assessed the impact of additional must run generation driven by manual reserve requirements of 2200 MW instead of the assumed value of 1300 MW In the following we discuss the results of the sensitivities in comparison to the 12 GW base scenario. These sensitivities serve two purposes: to demonstrate the robustness of the 12 GW scenario model results by showing plausible reactions of the model to variations in input parameters; and to inform Energie Ned of how results and conclusions change under different circumstances. Increased interconnector capacity to France 5.19 Figure 22 shows the net effects, starting from the 12 GW base scenario, of introducing 500 MW of additional interconnector capacity to France. This means that there are likely to be higher exchanges. System dispatch simulation for 2020

65 April 2010 Frontier Economics 55 Figure 22. Net effects of 500 MW additional interconnector capacity on the energy balance Netherlands; Difference in TWh/a Exports Wind curtailment coal CCGT Imports Flexibility source Source: Frontier 5.20 The additional exchanges appear to be mainly transit flows from France to Germany (these occur in particular in summer, when French prices are expected to be low due to increased hydro production). We also observe a small increase in generation in the Netherlands as local conventional plants can export more themselves. This extra generation occurs mainly in winter when Dutch power prices are very competitive in comparison to other CWE countries. Dutch winter power prices are rather low compared to the rest of CWE area thanks to good wind conditions in winter and, in particular, due to high power output from CHP plants needed to meet high winter heat demand Figure 23 confirms that the increase in imports and exports is mainly due to an increase in flows from France (via BE and Netherlands) to Germany. System dispatch simulation for 2020

66 56 Frontier Economics April 2010 Figure 23. Net effects of 500 MW additional interconnector capacity in TWh on net Netherlands imports/exports Difference in net exports in TWh/a DE BE GB NE Source: Frontier 5.22 There does not seem to be a significant interaction between Dutch wind and French hydro storage. The most likely explanation for this is that marginal costs in the Netherlands, even in the high wind scenario, are not low enough to make it worth importing and keeping water in storage in France. A high wind penetration in the system does not only lower input prices for storage plants but potentially also raises the output re-sale prices, leaving the price spreads on which storage plants arbitrage largely unchanged. In this particular case, the effect of additional Dutch wind on the French hydro storages is also limited by interconnector capacities between France-Belgium-Netherlands. Coal and carbon price increase and corresponding merit-order switch Figure 24 shows that a carbon (EUA) price of 34 per tonne, combined with a coal price of 22 per tonne, leads to a strong decrease in electricity produced by coal which is almost entirely replaced by generation from CCGT plant. In addition to the changes in the energy balance, we note an increase in part load costs of 4%. System dispatch simulation for 2020

67 April 2010 Frontier Economics 57 Figure 24. Net effect of a merit order switch (gas cheaper than coal) on the energy balance Netherlands; Difference in TWh/a Exports coal gas CHPs CCGT Imports Extra power prod from Heat adjustments Flexibility source Source: Frontier In Figure 25 we see that the substitution of coal by gas leads to a substantial decrease in carbon emissions in the modelled regions as gas is a cleaner fuel than coal. Of course, the impact is greatest in the two electricity systems with a large coal park (Netherlands and Germany), and much more limited in Belgium and France due to their nuclear plant parks. System dispatch simulation for 2020

68 58 Frontier Economics April 2010 Figure 25. Net effect of a merit order switch (gas cheaper than coal) on carbon emissions change in carbon emissions in mio t/a DE NL BE FR Source: Frontier Less interconnector capacity to Germany and from Germany to Central and Eastern Europe 5.23 Figure 26 shows what happens if the interconnector capacity to Germany is reduced by 700 MW and the capacity from Germany to the rest of its neighbours is reduced by 50%. It can be seen that both imports and exports are down as the transit flows from France to Germany are reduced. As cross border sources of flexibility are decreased, there is a very small increase in wind curtailment in the Netherlands. Otherwise, the generation mix is largely unaffected. System dispatch simulation for 2020

69 April 2010 Frontier Economics 59 Figure 26. Net effect of a reduction of IC capacity to Germany and its neighbours on the energy balance Netherlands; 2020 Difference in TWh/a Exports Wind curtailment Nuclear coal gas CHPs CCGT Imports Flexibility source Source: Frontier 5.24 Figure 27 shows at which borders the import/export flows actually change. From the increase of net exports to Germany and the decrease of exports to Belgium, we can infer that there is less electricity transiting from France to Germany. In addition, Dutch exports to Germany decrease. This can be seen from the fact that the reduction in flows to Germany is higher than the increase in net exports to Belgium and no other substantial changes in import/export flows are observed. System dispatch simulation for 2020

70 60 Frontier Economics April 2010 Figure 27. Net effect of a reduction of IC capacity to Germany and its neighbours on net imports/exports Difference in net exports in TWh/a DE BE GB NE -0.8 Source: Frontier 5.25 As the Dutch generation mix does not change in this sensitivity run, costs of electricity production in the Netherlands remain substantially unchanged. Germany's costs, on the other hand, increase significantly, because it has lower imports of cheap electricity and less scope for efficiency-enhancing interchanges with other countries, especially Alpine countries with their hydro storages. 30 NE (Northern Europe) and GB (Great Britain) were modelled as satellite region, the other regions ( DE, BE ) have been modelled explicitly. System dispatch simulation for 2020

71 April 2010 Frontier Economics 61 Figure 28. Net effect of a reduction of interconnector capacity to Germany and from Germany to CEE countries on variable generation costs 2020 Net costs developments in mio EUR DE NL BE FR Region Partload costs Startup costs Power and heat generation CHP power generation costs non CHP Source: Frontier 5.26 Under our less interconnector capacity to Germany case, no significant wind curtailment arises on the Dutch system. However, the level of Dutch reserve prices indicates that the system would be less flexible in this case. The reserve price is the implicit cost of holding the last MW of the required tertiary reserve margin in the Dutch system. Figure 29 shows that the positive reserve price increases by 6.5% and the negative reserve price increases by 21.4% with reduced interconnector capacity with Germany. The increase in the negative reserve price, in particular, indicates that the system is less flexible and is having more difficulty to integrate wind generation without curtailment. This extra cost occurs mainly in low demand hours with high wind when there is little scope left for flexible thermal plants to provide required reserve services. In these circumstances, not only are the short run marginal costs important for dispatch, but also the ability of plants to provide reserve services. System dispatch simulation for 2020

72 62 Frontier Economics April 2010 Figure 29. Net effect of a reduction of interconnector capacity to Germany and from Germany to CEE countries on reserve prices Netherlands; 2020 percentage change in average reserve prices 25% 20% 15% 10% 5% 0% 6.5% positive reserve price 21.4% negative reserve price Source: Frontier Inflexible coal plants 5.27 Figure 30 shows what happens if coal plants are made less flexible so that they cannot shut down overnight but have to run at no less than their minimum stable generation output at all times. As could be expected, coal output increases substantially. One third of this increase in coal output is absorbed by decreases in other domestic production and the other two thirds are absorbed by lower imports or higher exports. As coal stations become less flexible, the extra production displaces generation from CHPs and some CCGT output. System dispatch simulation for 2020

73 April 2010 Frontier Economics 63 Figure 30. Net effect of inflexible coal on the energy balance Netherlands; 2020 Difference in TWh/a Exports Nuclear coal gas CHPs CCGT Imports Extra power prod from Heat adjustments Flexibility source Source: Frontier Economics 5.28 In terms of cost developments, we observe a corresponding picture. Generation costs in the Netherlands increase as domestic production rises and as the assumed additional run-time constraint increases the cost of the coal stations that are constrained to operate. Other things being equal, an additional and binding constraint always increases costs in an optimisation problem. It can also be inferred from Figure 31, that most of the additional production is exported to Germany, as inflexible coal production in the Netherlands substitutes German generation. System dispatch simulation for 2020

74 64 Frontier Economics April 2010 Figure 31. Net effect of inflexible coal on variable generation costs Net costs developments in mio EUR DE NL BE FR Partload costs Startup costs Power and heat generation CHP power generation costs non CHP -300 Region Source: Frontier High reserve case and wind curtailment 5.29 In this sensitivity case, we increased the reserve requirement (negative and positive) in the Netherlands from 1300 MW to 2200 MW. In addition, we introduced reasonable reserve requirements in other model regions and kept the assumption that Dutch coal plants cannot stop overnight. The higher reserve requirements and the inflexible coal assumption lead to a generally more inflexible system. This in turn leads to wind curtailment of some 4 TWh, just over 10% of the total (or 25% of the incremental wind feed in the 12 GW case) The higher demand for reserves also means more thermal capacity must be started and run in part load to provide the reserve. As before, additional coal production displaces CHP output, which is therefore lower. Higher imports arise because the reserve requirements in the other electricity systems increase the thermal must run production there. This reduces the available cross border flexibility and makes exports from the Netherlands more difficult to achieve. System dispatch simulation for 2020

75 April 2010 Frontier Economics 65 Figure 32. Net effect of higher reserve requirements on the energy balance Netherlands; Difference in TWh/a Exports -4.0 Wind curtailment coal gas CHPs CCGT Imports Extra power prod from Heat adjustments Flexibility source Source: Frontier Economics System dispatch simulation for 2020

76

77 April 2010 Frontier Economics 67 6 Answers to specific questions 6.1 Having presented the results of the 6 and 12 GW wind scenarios, we now draw on this foundation, and use additional output from the model runs, to answer the questions put by EnergieNed, as given in Chapter 2. Can the market handle the fluctuating supply of wind power? 6.2 Our simulation results clearly indicate that the system is able to handle the fluctuating supply of wind power with minimal wind curtailment given the plant and load assumptions we have adopted. These results are obtained for a year which had very favourable wind conditions, in the sense that production was substantially above average 31. Figure 33 below shows how the additional wind power is absorbed into the system when wind generation capacity is increased from 6 to 12 GW, producing a further 21 TWh in Net exports (more exports and fewer imports) together with reduced coal and gas-fired generation are the primary sources of flexibility. There is very little change in the use of the limited flexibility of the CHP park The average load factor for wind offshore in this scenario is around 46% or 4030 hours and was chosen to align with data in the reference at footnote 33. On average we understand that hours are expected for wind offshore on the North Sea. For total Netherlands, we end up with an average load factor for wind of 3170h per year. 32 This is mainly driven by the additional heat demand constraints for CHP plants and the relative costs to untighten those constraints for example by using HOBs or accepting efficiency losses in CHP plants compared to adjustments of conventional plants. This could also change if fuel or carbon price assumptions change drastically so that the merit order changes. Answers to specific questions

78 68 Frontier Economics April 2010 Figure 33. How the additional wind generation is absorbed impact of an additional 6 GW Netherlands; Difference in TWh/a Wind Exports Coal CCGT Imports Extra power prod from Heat adjustments Flexibility source -7.2 Source: Frontier Economics 6.3 We recall that these simulations assume perfect market integration and that effective mechanisms exist to reallocate rights to flexibility from those who need them to those who have more than they require. The mechanisms for achieving this are discussed in Chapter These results are similar to those obtained by Ummels 33 in his doctorate thesis for the case with efficient use of interconnection capacity, although he looked at the year 2014 and assumed load of only 126 TWh. However, we understand that recent on-going studies by KEMA on behalf of EnergieNed members have shown considerably more wind curtailment than our own base scenario. Our simulations assume that the Dutch power system is relatively flexible by 2020 in terms of: effective use of strong interconnection with neighbouring countries; no internal grid congestion within the Netherlands and other CWE countries (only limits on flows between CWE countries); ability of coal plant to shut down at night; 33 Bart Ummels (2008); Power System Operation with Large-Scale Wind Power in Liberalised Environments; Dissertation at the TU-Delft Answers to specific questions

79 April 2010 Frontier Economics 69 ability of CHP plants to contribute to provision of upward and downward reserve; and ability of nuclear plants to run in part load and provide tertiary/manual reserve. 6.5 From the wind curtailment sensitivity analysis reported in Chapter 5, we know that: requirements for manual reserve in low demand hours is a key determinant of wind curtailment. We obtain about 4 TWh of curtailment (which corresponds to about 10% of the wind energy of 38 TWh available in the 12 GW scenario in comparison to the 6 GW scenario) in the Netherlands if we increased reserve requirements by 900 MW; and being close to the edge in terms of system flexibility means that if we cross the edge, significant curtailment soon arises. 6.6 In terms of system optimisation, the results suggest that must run generation needs to be reduced during low demand hours to avoid wind curtailment. This can be done by ensuring that the plants running in those hours are able to provide reserve products to the TSO. If this is not possible, additional plants need to be operated at minimum load for this purpose which could then trigger wasteful wind curtailment. Important aspects are therefore ensure that any new nuclear plants are able to contribute to manual reserve (and especially to downward reserve); ensure renewable generating plants can contribute to grid stability and flexible reserve provision; and ensure that heat driven CHP plants contribute to reserve provision. This can be done by decoupling power production from heat supply (e.g. by adding HOBs or heat storages to CHP stations). What is the impact of wind on system marginal cost? 6.7 Our model calculates the system marginal cost as the dual of the load constraint for the CWE region or each country (if interconnection capacity is insufficient to for the optimum power flows). We have taken short run system marginal costs as an indicator of market prices, although clearly it does not take account of the potential extra scarcity premia for producers that can arise when, in the real world, there is insufficient available capacity to meet demand. The data is taken Answers to specific questions

80 70 Frontier Economics April 2010 directly from the model but we have eliminated the price for one hour of 2000/MWh caused by a lack of capacity 34 which would have otherwise distorted the graphs. 6.8 Figure 35 shows the pattern of monthly average baseload system marginal cost in the 6 GW and 12 GW wind cases. On average the additional wind generation in 2020 reduces system marginal costs by just under 5/MWh. As expected, prices are higher in winter than summer and this does not change between the scenarios. There were 167 hours in which marginal costs were zero as a result of high wind infeeds. Figure 34. Monthly average system marginal cost for 6 and 12 GW wind scenarios baseload period Netherlands; Monthly average wholesale power price in /MWh NL - base - 6 GW NL - base - 12 GW 50 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Source: Frontier Economics 6.9 Figure 35 shows the same picture for the peak hours. Peak system marginal costs are some 10% higher than baseload ones (on average about 7 per MWh) in both scenarios. The difference between average marginal costs between the two scenarios is just under 4 per MWh, slightly less than in the baseload case. 34 We observe those spikes also in reality when huge drops in wind generation cannot be balanced by the thermal plant system due to ramping constraints. Answers to specific questions

81 April 2010 Frontier Economics 71 Figure 35. Monthly average system marginal cost for 6 and 12 GW wind scenarios peak period Netherlands; Monthly average wholesale power price in /MWh NL - peak - 6 GW NL - peak - 12 GW 50 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Source: Frontier Economics 6.10 Figure 36 shows the annual duration curve of system marginal costs for the two scenarios. The differences between the scenarios are most apparent in lower price hours. The highest system marginal cost is 129 per MWh, reflecting generation from a gas turbine. At EnergieNed s request we have also included on the graph the last 12 months of APX prices. There are major differences with the current APX prices, in large part because our fossil fuel and carbon price projections for 2020 are very different to current commodity prices. However, it is noticeable that, in the highest price hours, the curves appear to converge. Answers to specific questions

82 72 Frontier Economics April 2010 Figure 36. Duration curve of system marginal costs 35 with nominal APX prices in the 12 months to December 2009 superimposed Netherlands; 2020 Wholesale power price in /MWh Source: Frontier Economics Hours of year 6 GW 12 GW Nov 2008 to Nov 2009 APX We have analysed the volatility of peak system marginal costs measured as the standard deviation for each month divided by the mean. The results are shown in Figure 37 for the two scenarios. As expected the 12 GW scenario is more volatile. There is also a pronounced seasonality that corresponds in broad terms to the pattern of wind generation in different months of the year. 35 Please note that our price forecast numbers for 2020 do not consider an inflation forecast, which means that we actually compare like with like in this respect. Answers to specific questions

83 April 2010 Frontier Economics 73 Figure 37. Monthly volatility of real 36 system marginal costs for the 6 and 12 GW scenarios Netherlands; % 20% Monthly volatility (s.d./mean) 18% 16% 14% NL - peak 12 GW vol NL - peak 6 GW vol 12% 10% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Source: Frontier Economics 6.11 There is a final point about the impact on system marginal costs. It is that the additional wind energy lowers system marginal costs and thus exerts downward pressure on the wholesale market prices in However, this does not mean that prices to end users will fall as there are the additional costs of the renewable energy promotion schemes and additional grid costs to take into account. Additional demand for reserve, together with decreasing supply (because of the lowered residual load available for thermal plants) are also likely to drive up reserve prices and thus charges for recovery of system services. What is the role and importance of market integration? 6.12 We have already highlighted the importance of cross-border interchanges to the management of fluctuating wind generation and this can only be optimised by market integration. The best test of whether markets are integrated is price convergence. 36 Concerning prices: As we depart from prices in the year 2009 and do not incorporate an inflation forecast, the prices can be interpreted as real prices in 2009 price levels. Answers to specific questions

84 74 Frontier Economics April Figure 38 shows the number of hours in which system marginal costs are projected to be the same in the different countries of CWE. It is apparent that regional power prices are less often the same in the high wind scenario than in the low wind scenario. Specifically, the Netherlands and Germany are decoupled for an additional 1000 hours. But the main differences in comparison to the present situation is the greater divergence with France, illustrated in more detail below, due to the constraint on its ability to export power in combination with high volumes of must run power and low summer demand. Figure 38. Market coupling in 2020 price convergence between countries No. hours coupled GW 6 GW NL=BE=FR=DE NL=BE=FR NL=DE NL=BE Source: Frontier Economics 6.14 Looking across the CWE region, Figure 39 compares system marginal costs for each country. There is high convergence, especially between the Netherlands and Belgium, but French marginal costs are significantly lower in the summer months for the reasons noted above. It is possible that if more nuclear plants were scheduled to be offline for maintenance over the summer, this effect would not be observed. Answers to specific questions

85 April 2010 Frontier Economics 75 Figure 39. System marginal in the 12 GW scenario across the CWE baseload Monthly average wholesale power price in /MWh BE - base DE - base NL - base - 12 GW FR - base 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Source: Frontier Economics 6.15 The important role of market integration can be seen in Figure 40 which shows the destination of exports and imports from the Netherlands. Germany is the main recipient of power in spite of the correlation of wind generation output, followed by Belgium and Great Britain. The letters NE stand for North East Europe and refer to interconnections between CWE country and the Nordpool area. Answers to specific questions

86 76 Frontier Economics April 2010 Figure 40. Gross exports and imports by destination and origin in the 12 GW scenario Netherlands to/from other countries; Exports Imports 20 Imports/Exports in TWh DE BE GB NE Region Source: Frontier Economics 6.16 In summary, market integration is a crucial source of flexibility, and the German market is especially important in spite of the correlation of Dutch wind production with Germany s own wind output. The Netherlands becomes a major net exporter of power, to a point where interconnector capacity is often constrained in the winter Please note that our analysis does not consider the proposed Cobra cable (a HVDC link is envisaged 37 ) to Denmark West. We understand that feasibility studies are on-going and a firm decision then needs to be taken. If positive, detailed technical planning would be finished by 2012 and the commissioning would take place at the earliest in The cable would connect two regions which are both characterized by a high volume of wind capacity and significant percentage of CHP plants. We would expect there would be hours when the Dutch system will be required to absorb wind overflow from Denmark, and also hours when it would release some pressure from the Dutch system as in those hours when production tends to exceed demand. In such cases, an additional export option can help to provide a market for the surplus power. As wholesale prices will reflect the supply/demand balance at each ends of the cable, the power flow should always go from the 37 Answers to specific questions

87 April 2010 Frontier Economics 77 more critical to the less critical system (this also holds even if both regions were to have negative prices). Denmark is also connected to Norway and Sweden (links which are already used today for export in times of surplus power in Denmark) 38 as well as to Germany Without quantitative analysis, we cannot assess the net effect on power prices in the Netherlands or on import balance between Denmark and the Netherlands of having the Cobra cable. However, from our sensitivity analysis on reduced interconnection capacity with Germany and from the qualitative considerations above we expect a positive effect on system stability in situations with extreme wind conditions. Is CHP the perfect partner to wind production? 6.20 Looking at the results of our modelling, our view is that CHP is not incompatible with wind generation capacity of 12 GW but is also far from being a "perfect partner". This is because: integration of wind generation requires significant flexibility and this comes from conventional gas and coal-fired generation and from international power exchanges but these resources are limited; and CHP does seem not to adapt very much to intermittent wind generation under our assumptions as a consequence of: heat demand constraints; the additional costs of running CHP at part load and switching heat demand to the HOB capacity that we have assumed; and insufficient HOB (or heat storage) capacity This implies that beyond a certain point, the flexible resources we have identified will be exhausted and there will be a choice between wind curtailment and investing to make CHP more flexible. As noted in Annex 2, an important lesson from Denmark is that when electricity prices are low, it can become economically attractive to add electric boilers to CHP plants that can take over heat production, allowing CHP heat and power output to be reduced. 38 Denmark West is connected via a 850 MW submarine cable with Norway and a 480 MW cable to Sweden. 39 EMCC GmbH carries out day-ahead congestion management services on the two interconnectors between Germany and Denmark, DK West (950 MW north / 1,500 MW south) and DK East (550 MW north and south) to allow for market coupling of Denmark and Germany. Answers to specific questions

88 78 Frontier Economics April 2010 What are the implications for business cases? 6.22 We now consider in broad terms the implications of the 12 GW wind scenario for the business cases of new plants and for existing plants 40 : Please note that we did not run a complete business case calculation but that we looked at a snapshot year We observed the following effects which can have important implication for the future capacity balance: 6.23 Existing plants show lower load factors As existing plants tend to have higher variable costs than modern new plants due to the former s lower efficiencies, those existing plants will be the first to reduce production as a consequence of high wind infeeds. Existing conventional plants may therefore struggle to achieve load factors which will allow them to recover their fixed O&M costs. If they failed to recover their annual fixed costs, owners may close down those plants or may keep them standing idle as longer term reserve Business cases for new plants also affected As a growing percentage of the Dutch electricity demand will be met by wind power capacity that benefits from financial support (subsidy) mechanisms, there will be a reduction in the electricity demand that can be met by new power plants. As wind contributes more to energy delivery than it contributes to an adequate capacity balance, additional (dispatchable) thermal plants will still be required in order to have a reliable system. The question that will need to be addressed is how to ensure adequate incentives to invest in this thermal generation capacity. Investors of future new built plants will need to allow for lower utilisation rates and a more volatile operation profile within their business cases. Capacity based revenues, e.g. from ancillary service markets or possibly from capacity markets 41, are likely to play a more important role than they do today We expect reserve prices for manual reserve to increase with increasing wind penetration. This is because the demand for reserve increases and the ability to offer this reserve from thermal plants in part load operation decreases given that these plants will no longer be running in high wind/low load hours. Is there a need for storage? 6.26 The storage plant we have included in the two scenarios has very low load factors and does not appear to be economic by a wide margin in either case. At this level 40 Due to confidentiality reasons we cannot present the results for individual plants in detail here. 41 An example of a capacity market designed to ensure security of supply is that introduced in New England in the USA. The wholesale markets in Spain and Ireland also have a specific payment for capacity. Answers to specific questions

89 April 2010 Frontier Economics 79 of wind penetration, storage does not appear to be needed 42. However, in a situation with significant local grid congestion (and constraints on reinforcing or extending the grid) power storage can become an option if it were able to benefit from extra grid related revenues, e g. from solving potential congestion constraints or from avoiding grid related wind curtailment 43. Together with its wholesale energy price arbitrage and reserve power revenues this could make individual storage projects feasible if they are located at the right place within the grid From our analysis and in line with previous work we undertook on power storage 44 we can conclude that large scale stationary storage is negatively affected by grid extensions that smooth power prices over time and between regions and countries. However, if such grid extensions (on regional, national or international level) do not happen, storage can be an economic option to avoid wind curtailment. 42 Please note that we used price estimators based on short run marginal costs for this study. This tends to underestimate peak prices and thus tends to underestimate the value of storage. We also used cost based prices for reserve capacity which also tend to be lower than ancillary service prices in reality. 43 Here also regulatory rules are important. 44 Gatzen, C. (2008): The economics of power storage Theory and Empirical analysis for Central Europe, phd thesis. Answers to specific questions

90

91 April 2010 Frontier Economics 81 7 Market dynamics 7.1 As discussed in Chapter 3, the results of the system despatch model reported in Chapter 5 demonstrate that, given the assumptions adopted, there is sufficient flexibility to integrate the 12 GW of wind generation capacity with a small risk of wind curtailment. In particular, the model demonstrates the critical importance of international exchanges. As noted in our review of experiences in other EU countries reported in Annex 2, this is a very important factor in the successful integration of large wind generation park in Denmark. 7.2 However, the quantitative model does not deal with the issue of how PRPs with too little flexible resource of their own trade with those, inside or outside the Netherlands, who have more than sufficient flexible resource (or vice versa). In effect the model assumes that subject to interconnection capacity, the market operates perfectly to reallocate rights to flexible resource and is fully integrated across the CWE area (subject to cross-border transmission constraints). This chapter now considers in a more practical sense the market mechanisms that now exist and how these might need to evolve to ensure that those PRPs who need access to additional flexible resources are able to obtain it. 7.3 We now consider in turn: existing arrangements in relevant markets (day ahead, intra day and balancing) in the Netherlands; and the status of integration or coupling with other CWE countries (and with other linked countries) and how this might evolve to improve efficient access to flexibility. 7.4 We draw on the material in Annex 2 about experience in other EU countries, especially in relation to Denmark, in the discussion. 7.5 The focus on short term markets reflects the requirement for short term flexibility to facilitate wind integration. The need for flexibility arises from the unpredictable nature of wind energy which in turns depends on meteorological forecasts of wind speeds. Forecasts may first be made 2 3 days ahead of real time and are gradually refined as better meteorological data become available. There is an accuracy improvement in wind forecast error of about 50% between day ahead (up to 36 h before delivery) and 2-3 hours before delivery, as shown in Figure 41. For this reason we do not consider traditional forward markets for power as a solution to the flexibility challenge. Market dynamics

92 82 Frontier Economics April 2010 Figure 41. Normalised standard deviation of wind generation forecast error Source: Bart Ummels 45 Markets within the Netherlands 7.6 APX currently provides the day ahead (spot) and intraday market and Endex (an affiliated company) provides a futures market in power products. In its Monitoring Report for 2007, the Dutch regulator, Energiekamer (EK), noted that volumes on APX spot market were, relative to the size of the country, higher than those in France but still short of those in Germany. Volumes have continued to grow and reached record levels towards the end of 2009 according to an APX-ENDEX press release, although intraday trading is much less liquid than the day ahead spot market. These energy exchanges are complemented by OTC markets. 7.7 Figure 42 shows the timescales of the day ahead and intra-day markets in the Netherlands at present. 45 Bart Ummels (2009); Power System Operation with Large-Scale Wind Power in Liberalised Environments; Dissertation at the TU-Delft. Market dynamics

93 April 2010 Frontier Economics 83 Figure 42. Timeline for different markets in the Netherlands at present on D hrs Gate closure at t-1 15 mn PTU DAM Continuous Intraday Regulating power and reserve capacity Imbalance settlement TenneT PRPs Traders t Source: Frontier Economics from APX and TenneT sites 7.8 Our observations with regard to flexibility are as follows: the day ahead market, in the form of an auction for which bids must be submitted by 11.00, can be used to trade flexibility based on wind energy forecasts for 13h ahead (the first hour of the following day) to 37h ahead (the last hour of the following day). While this is useful, significant forecast error arises after the day ahead market has closed at 11h, especially for the hours towards the end of the following day; the intraday market, opening at on the day ahead, offers the most scope to deal in flexibility as trading is continuous and products are blocks of power for individual quarter hours, one hour or two hour periods up to 1 hours ahead of real time; and in the balancing market, only TenneT may buy and sell flexibility because PRPs E-programmes have been finalised. However the balancing market is still important as the prices TenneT pays for flexibility are used to determine the price those parties with imbalances must pay (or be paid) to settle their positions 46. Since PRPs with wind generation are very likely to have some imbalance, having an efficient balancing market in which flexibility is traded at least cost is very much in their interest. 7.9 Unlike EEX, APX does not currently permit prices to be negative 47, although a harmonised approach will no doubt have to be agreed in the context of 46 When these are in the opposite direction of the system imbalance. 47 However, we understand from EnergieNed member that negative prices are sometimes observed on the OTC market.. Market dynamics

94 84 Frontier Economics April 2010 pentalateral market coupling. We note that Nordpool is currently introducing negative prices to provide better incentives to increase flexibility when wind generation output is high. Having the potential for negative prices is likely to help reduce the probability of wind curtailment We are uncertain to what extent the operators of CHP plant in the Netherlands participate in these short term markets and are thus encouraged to trade the limited flexibility that they have 48 and, depending on the development of prices, to increase this flexibility. However, we note that Denmark has now required larger CHP plants to participate in Nordpool and many plants in Denmark now have electric HOBs which not only allow them to reduce electricity production but also consume power whenever wholesale market prices are low (and in future potentially negative). As wind penetration in the Netherlands increases, steps to encourage CHP plant to respond to low power prices, especially in off peak hours, will be desirable. By this means, the flexibility of CHP plant is likely to increase. Integration of markets in the Netherlands with interconnected countries 7.11 The possibility for PRPs to access flexibility is improved to the extent that they can not only benefit from national liquidity, but also from the available liquidity in other countries, provided there is cross-border capacity made available to support the integration of the liquidity pool Our discussion of market integration focuses on the status of the relevant day ahead and shorter term markets. Day ahead market The situation today 7.13 The success of the trilateral market coupling between FR-BE-NL is well known. Prices have now converged across the three areas for the majority of hours in the years and are equal in NL and BE in even more hours. The essence of the implicit auction approach used is that market members can simultaneously buy electricity and cross-border capacity in a single transaction, reducing the risks that apply in uncoupled markets where these two elements must be acquired separately and at different times. This enhances efficient utilisation of available power generation options, including flexible resource, as well as interconnection capacity. 48 A 2002 paper on the EK site refers to some CHP plant being connected to TenneT s frequency control system for automatic reserve. We also understand that greenhouse plants invest in heat storage systems to increase their flexibility. Market dynamics

95 April 2010 Frontier Economics We note that at present more than half of the 3850MW of cross-border capacity with BE and DE made available by the TSOs is allocated through annual or monthly auctions where it can be used to hedge the positions of those trading in forward or futures contracts between the different markets. This contrasts with the approach in the Nordpool area where the full interconnection capacity is allocated implicitly in the day-ahead market on the grounds that this is the most efficient approach 49. There is clearly no point in allocating more capacity via the day ahead markets than is needed to achieve price converge in most hours. However, our results indicate that price convergence may occur less often as wind penetration in CWE increases and this may make it necessary to revisit the proportions of cross-border capacity allocated on different timescales. Especially in hours with surplus generation in the Netherlands or in Germany, cross border exchanges gain importance as a means to access flexibility and thus to reduce costs in the power system and limit the risk of price collapse in cases of excess inflexible generation It has to be noted that the NTC values published by ETSO (e g. ETSO list MW in Summer and MW in winter as being available between Netherlands and Germany) and the amount Tennet makes available to market players differs (Tennet publishes in its quality and capacity plan 2008 to 2014 a total maximum of 3850MW of interconnector capacity towards Germany and Belgium 50 ). It is important to take into account technical security requirements from a TSOs point of view. However, it should also be noted that international power flows are an important instrument to balance volatile wind infeed. Therefore an optimal use of existing physical exchange capacities is important. Announced developments to enhance cross border exchanges and market integration 7.16 The intention is to extend market coupling to include Germany and Luxembourg in 2010 (pentalateral coupling). In order to do this it is planned to move all of the day-ahead markets to a common closure time, expected to be of day-ahead. Initially the cross-border capacity will be based on the current approach using NTC values, limited by any applicable aggregate constraints. The declared intention is to move towards what is known as flow based coupling in late 2010 or Under this approach the cross-border capacity is not a static figure but is determined as a function of the potential flows, based on power transfer distribution factors. This dynamic approach is expected to increase the available capacity and the efficiency with which it is allocated. 49 Those trading electricity forward between the markets can buy contracts for difference to manage the basis risk 50 See table 11, Kwaliteits- en Capaciteitsplan, 2008 to 2014., Tennet 2007 Market dynamics

96 86 Frontier Economics April In addition to pentalateral coupling, TenneT and interconnected TSOs have plans to couple markets across two HVDC (high voltage direct current) links: coupling is to be introduced on the existing 700 MW NorNed link at an unspecified time in the future - the present daily allocation of all of the capacity by auction will then cease; and coupling with GB is also expected to be introduced after the 1000 MW BritNed interconnectors is commissioned in early 2011 but some day ahead capacity may continue to be allocated by explicit auction There is a high probability that all these arrangements will be in operation by 2020 and the liquidity pool at the day-ahead stage for flexibility should therefore be much improved. Intraday markets Today s situation intraday markets are still national 7.19 Integrated intraday markets are even more desirable as a mean to increase the liquidity pool for flexibility on timescales relevant to wind generation. However, while the Nordel region already has the fully integrated Elbas market, operated by Nordpool, less progress has been made in the CWE area The lack of accurate wind forecasts at the day ahead stage, combined with an accuracy improvement in wind forecast error of about 50% between day ahead and intraday means that intraday trading will gain significantly in importance for PRPs and traders to balance of their positions. An efficient design of intraday markets will be crucial to reduce wind integration costs. Plans for integrated intraday markets 7.21 In June 2008 the four power exchanges (PX) for the pentalateral coupling area produced a white paper explaining how they might build an integrated platform to manage a central order book for intraday trading. One of the essential concepts, shared with Elbas, is that buy and sell orders posted by members of individual exchange are only visible on the central order platform ( Central order book ) in countries where there is sufficient cross-border capacity to permit delivery of the trade. This means that the trading parties can be sure that their intended trades are feasible in terms of rights to interconnection capacity. This is very important if the transaction is to be considered as firm and settled by physical delivery. For this reason the central order platform is integrated with a cross-border (XB) capacity matrix maintained by the eight TSOs 51. As soon as an order is accepted, an electronic shipping agent linked to the central order platform nominates the XB (Cross Border) capacity and the matrix is updated. At 51 One TSO for each country except Germany which has four TSOs. Market dynamics

97 April 2010 Frontier Economics 87 the same time, the national power exchange notifies the trade to the relevant national TSOs for balancing purposes The approach described above is shown diagrammatically in Figure 43. Model for cross-border intraday trading Country A Country B TSO A XB Capacity Matrix TSO A XB Capacity Interface Single Platform PX A Central Order Book PX B Balancing Mechanism Trades Shipping Agent nominates XB Balancing Mechanism Source: White Paper by Powernext, APX, EEX and Belpex Given the importance of intraday trading as a means to access flexibility, coupling of intraday market will need to be pursued hard as soon as the day ahead markets are coupled. Since these arrangements already work effectively in the Nordel area, there seems to be no reason why this cannot be achieved by 2020 in CWE. Balancing markets 7.24 As noted above, the importance of integrating balancing markets for PRPs with wind generation is an indirect one. Once the intraday market closes, and there is no longer scope to amend E-programmes, responsibility for managing changes in production due to wind forecast error passes to the TSO. If the balancing market is liquid and efficient, prices will be lower and, in consequence, the cash out price paid by PRPs who have a negative imbalance will be lower The very short timescales in which activity needs to take place make integration of balancing markets more of a challenge. However, much has been achieved in other EU/EEA countries: Market dynamics

98 88 Frontier Economics April 2010 the Nordic area has a single market for balancing or regulation services in which the four TSOs work collaboratively to ensure that that only offers which can be physically delivered are accepted; the four German TSO have moved from having four separate procurement procedures for establishment and use of reserve to a common process across the whole of Germany, although clearly this is made easier by the absence of border constraints between TSOs (in other words any constraints are treated as internal transmission constraints); and the French adjustment market operated by RTE has international participation from Switzerland, Spain and Great Britain Given this experience, there seems to be a good probability that by 2020 balancing markets will also be substantially integrated across the CWE area, promoting the efficient use of flexible resources and thus helping to keep the price paid in respect of imbalances down. However, intra country grid constraints may still limit the extent by which flexible resources from outside a control area will be able to substitute flexibility inside the control area as their availability and accessibility to the importing control area need to be guaranteed by the exporting TSO. Other relevant developments 7.27 Three other developments, expected over the next decade, are relevant for the supply and demand for flexibility: As wind generation develops in Europe, it is expected that the ability to forecast wind generation output, both at plant level and across a portfolio of wind farms will increase thanks to experience and compensating interregional balancing effects. Denmark has already made significant progress in this area. To the extent that specific forecasts improve, the volume of flexibility needed will be lower (for a given amount of wind energy). However, as we assume significant increases in installed wind capacity, the forecast error expressed in absolute numbers is expected to increase over time, even if forecast error were to improve. Our dispatch simulation only considers supply side resources. Developments in smart metering and in a number of energy utilisation technologies (electric cars, heat pumps, micro CHP) will mean that more balancing services will be available from aggregation of demand coupled with remote control of selected loads. Power storage technology is also improving and cost may reduce to a point where it becomes economically attractive as a source of flexibility. Market dynamics

99 April 2010 Frontier Economics 89 As renewable generation sources take a more dominant role in the CWE power system they will also need to contribute to system stability and start to provide ancillary services to the grid. First steps towards that have been already included, for example, in the German legislation an extra bonus is awarded to renewable generators in the German Renewable Act for being eligible to contribute to ancillary services; and technical grid connection rules of the DSOs require certain minimum control standards from renewable energy sources It is worth noting in this context that the distinction between wind generation offering downward reserve to the TSO and wind curtailment becomes blurred All of these developments will help to ensure that there is access to adequate flexibility by Market dynamics

100

101 April 2010 Frontier Economics 91 8 Conclusions 8.1 We now draw together the main conclusions of the quantitative modelling and qualitative analysis to consider the flexibility of the power system assuming 12 GW of wind generation capacity is operating in the Netherlands in We consider flexibility to be the availability of resources, from the day ahead of delivery to the time of delivery, that can change their level of production or demand by defined amounts and sustain this position for a period of at least one hour in a reliable manner. 8.3 Wind capacity of 12 GW will require increases in manual reserve for both upward and downward regulation. Based on work reported by TenneT, we have assumed that up to 6 GW of wind capacity will have no impact on reserve requirements but beyond this level additional reserves equal to approximately 10% of incremental wind generation capacity will be needed. The actual amount will be sensitive to the wind forecast error. 8.4 It will be important to have physical flexibility within the system and to make it accessible to those market players who need it. Figure 44 summarizes the main considerations with respect to both of these aspects. Figure 44. Physical flexibility and how to make it accessible to the market We need to make sure that physical flexibility is in the system Thermal plants needed on system and able adjust their output CHP Plants need to become more flexible Nuclear should be able provide manual reserve Interconnectors are important AND make sure that this flexibility is accessible to those who need it! Liquid markets close to delivery (Intraday) CWE market coupling allows for better interconnector usage Harmonize day ahead markets with GB and Norway International balancing markets Source: Frontier 8.5 Our modelling results indicate that the integration of 12 GW of wind power is feasible under the assumptions we have used, if the available flexibility in the Netherlands and interconnected countries is used optimally. This integration of 12 GW of wind capacity can happen along side the substantial growth in conventional capacity and will make the Netherlands a net exporter of electricity within the CWE area. Even for the favourable wind year which was modelled we Conclusions

102 92 Frontier Economics April 2010 found virtually no wind curtailment under the assumption of perfect market integration and strong grids. However, the system will then be at the edge in terms of flexibility. An increase in demand for flexibility (e.g. higher reserve requirements) or a decrease in supply of flexibility (more must run generation, greater build of less flexible technologies, inefficient allocation of flexible resources) could quickly trigger significant wind curtailment. 8.6 Market coupling and market integration, which is assumed by our model to be complete within the limits of the assumed interconnector capacity, plays a crucial role. Spreading the challenge of wind integration over larger areas reduces aggregate fluctuations and lowers costs. Flexible exports from the Netherlands, and flexible transit flows across the country, help to absorb a significant proportion of the fluctuations from wind generation. Interconnection with Germany is particularly important in spite of the fact that it too has an increasingly high proportion of fluctuating wind generation. We note that increasing wind power tends to reduce price convergence in the CWE markets, given fixed interconnection capacity. 8.7 The challenge of wind integration lies in making the power system as flexible as possible. Here a broad portfolio of technologies needs to contribute: conventional thermal power plants (coal/gas) need to adapt to start/stop and partload operation; new nuclear generation can also contribute to system flexibility by providing manual reserve; and CHP plant will need to become more flexible by transferring heat production to alternative sources in order to decouple electricity output and heat demand. 8.8 We think that, for the most part, price incentives will be sufficient to achieve these changes but some measures may be needed to ensure that CHP plant participate in the market so that the owners can respond to these incentives. 8.9 If we ranked the importance of flexibility measures we can conclude that international market integration is the key to successful wind integration. In the case of the Netherlands a flexible conventional plant system is also of importance. Power storage is not required to integrate 12GW of wind. Figure 57 gives an overview of our ranking of the different sources of flexibility. Conclusions

103 April 2010 Frontier Economics 93 Figure 45. Importance of flexibility measures Action points Importance Integration with CWE Increase usable exchange capacities Physical (international) interconnectors Strong internal grids (NL, DE) Efficient allocation of exchange capacities Very high Flexibilize conventional system Reduce must run Nukes and CHP contribute to ancillary services Flexibilize CHP plants Conventional coal needs to contribute High Storages Storages become attractive if points above are not used weak grids (extra revenues from grid congestion), high downward reserve prices Secondary Option DSM Demand side should contribute We account for 300 MW manual reserve from DSM, We did not model DSM but from our experience the practical potential is limited. Not analysed in detail here Source: Frontier 8.10 For the reasons given above, the projected CHP park in 2020 is not incompatible with 12 GW of wind generation but that does not mean it is the perfect partner. As intermittent generation continues to grow the need for flexibility will increase and the CHP park will need to evolve as it has already done in Denmark. Under the scenarios we have modelled CHP shows little response to increased wind generation and therefore its energy performance does not change much Provision of ancillary services to TenneT will have a growing impact on the whole power market. In low load hours the demand for reserve products can lead to high procurement prices (to be paid by the TSO) which then can influence the bidding of plant operators in the wholesale market. Reserve payments are likely to become an increasingly important source of revenue Increasing wind generation will exert significant downward pressure on wholesale electricity prices, especially at times when wind is high, load is low and there are high volumes of inflexible generation. Price volatility will increase as wind generation grows leading to a more unpredictable business environment for generators. The load factors on conventional thermal plant also fall. Both factors act to reduce expected revenues in With regard to the existence of flexible resources, we do not see any need for new policy measures in the Netherlands to mandate specific actions, with the possible exception of taking additional steps to encourage market participation by CHP plant. However, existing policies in support of stronger interconnection with neighbouring countries will need to be pursued strongly at national and regional level. Conclusions

104 94 Frontier Economics April Wind integration requires strong grids both on a national and an international level. Optimum use of existing physical interconnector capacities is a key instrument to deal with volatile wind infeed. It needs to be recognised that regional bottlenecks close to the interconnector (regardless of whether these are on the German, Belgium or Dutch side) can limit cross border power flows and may trigger expensive redispatch of power plant operation (or even wind curtailment) Our modelling work assumes perfect market integration across the CWE area to ensure efficient allocation of flexible resources. Given the profile of wind forecast error in the hours before delivery, the intra day market will be especially important mechanism to achieve this. Well developed day ahead and retail markets already exist but only the day ahead market is coupled at regional level and this has yet to be extended to include Germany Successful integration of high volumes of wind generation will require strong support at policy level for: the planned day ahead pentalateral market and the introduction of flow based coupling to make best use of interconnection capacity; the development of day ahead market coupling between the Netherland and countries linked by HVDC links (GB and Norway); the development of integrated intra day market with simultaneous trading in energy and allocation of interconnection capacity for firm delivery; and the development of arrangements to permit international participation in balancing markets to help keep the costs of exposure to imbalances as low as possible If high volumes of wind capacity limit price convergence in the coupled dayahead market, it may be necessary to review the proportion of cross-border capacity that is allocated through implicit auctions at the day-ahead stage and that which is allocated on a monthly and an annual basis. Conclusions

105 April 2010 Frontier Economics 95 9 Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West Executive Summary of additional COBRA analysis 9.2 The base case analysis as it is presented in the main report did not consider the proposed new 700MW DC link interconnector, COBRA, between the Dutch and the Western Danish power system. EnergieNed has asked us to explore separately, whether such a link with a wind and CHP dominated Danish system could help relieve the strain on the Dutch system or whether it worsens the flexibility issues in the Netherlands. 9.3 We therefore extended our model to explicitly incorporate Denmark West as a further model region and modelled plant dispatch for the year 2020 applying the base case assumptions of our main study. We reran the model extension taking into account the new 700MW COBRA link and compared it with a reference run where we excluded the COBRA cable. 9.4 Based on this analysis we can draw the following conclusions on the effect of the COBRA cable on the Dutch and Danish power system: Usage profile - The cable will likely be used in both directions. However, more power is exported from Netherlands to Denmark (3.7TWh/a) than it is imported from there (1.3 TWh/a). Exports from the Netherlands occur mainly in night hours over all seasons of the year, imports occur in the morning hours. Destination of additional power flows - A significant proportion of exports are transits, mainly to the Nordpool area and Germany. This is possible as Denmark West will extend its connections to Denmark East (+600MW), Norway (+700MW) and Germany (+1000MW) by Effect on Dutch thermal generation - Thus, Cobra increases the utilisation rate of thermal plants in the Netherlands. In particular domestic coal plants benefit from the cable (0.8 TWh/a more than without the cable). However, this is only a relatively small increase when considering that Dutch thermal generation will fall by 5TWh/a when expanding Dutch wind capacity to12gw rather than 6GW. Effect on wholesale prices - As result of creating the COBRA link, average wholesale prices in the Netherlands would rise by around 2 EUR/MWh. Danish wholesale prices could fall by about 10 EUR/MWh. Some of this asymmetric change in prices is that the Dutch system is significantly larger Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West

106 96 Frontier Economics April 2010 than the West Denmark system. It further matters that in our modelling COBRA helps avoid demand curtailment in Denmark (about 30h/a) which is punished in the model with 2000 EUR/MWh (had we chosen a lower reservation price the price change in Denmark would have been lower). This curtailment occurs in hours with low wind feed-in. The need for demand curtailment is not necessarily due to a lack of capacity in the Danish capacity balance (installed nameplate plant capacity adds up to more than 9GW with a peak demand of about 5GW) but due to a lack of flexibility of Danish generation as it is dominated by wind and CHP. Effect on Dutch wind curtailment - COBRA can help to further lower the need for wind curtailment in the Netherlands (e.g. as analysed for the base case) by about 0.1 TWh/a. For a situation with more restrictive assumptions regarding plant flexibility (2300MW of manual reserve requirements, coal must run ) the Cobra cable can avoid almost 1 TWh of wind curtailment in the Netherlands in 2020 (which is about 1/3 of the required curtailment in that scenario) 9.5 Put simply, the Danish system is even more stressed than the Dutch power system. Therefore the relieving effect of the COBRA cable is more obvious at the Danish end of the cable. Power prices in the Netherlands increase by about 2 EUR/MWh whereas average power prices decrease significantly in Denmark West. However - as the curtailment run shows, the COBRA cable can become valuable (and not harmful!) also in the Dutch system and help avoid high costs of wind curtailment or extreme power prices. Case Study: Effects of the COBRA cable 9.6 The base case analysis as it is presented in the main report did not consider the proposed new 700MW DC link interconnector, COBRA, between the Dutch and the Western Danish power system. EnergieNed has asked us to explore separately, whether such a link with a wind and CHP dominated Danish system could help relieve the strain on the Dutch system or whether it worsens the flexibility issues in the Netherlands In this annex we now provide the results of additional analysis which we conducted after the completion of our main study 53. Purpose of this analysis was to specifically analyse the effect of the new COBRA link with respect to wind integration in the Netherlands. In the following section we provide 52 So the purpose of this exercise was not a detailed assessment of the COBRA link but the analysis of the effect of the new link on the wind integration in the Netherlands. 53 Our initial model did not include Western Denmark as separate model region but we modelled it as a satellite region. For this case study we adapted our model and incorporate Western Denmark as new model region where we model power plant dispatch on a plant by plant basis. Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West

107 April 2010 Frontier Economics 97 a short description of key assumptions concerning the Western Danish power system in 2020; a short overview of model results; and our main conclusion on the effect of the COBRA cable in terms of wind integration in the Netherlands. 9.8 We therefore extended our model to explicitly include Denmark West as an additional model region and model plant dispatch for the year 2020 applying the base case assumptions of our main study. We reran the new model taking into account the new 700MW COBRA link and compared it with a reference run where we excluded the COBRA cable. Key assumptions for the COBRA case study The situation in Western Denmark today 9.9 The Danish power system is dominated by wind power and decentral and central CHP already today. In contrast to CHP in the Netherlands Danish CHP is mainly applied in plants for district heating purposes The Western Danish power generation system consists of: 3000MW large central CHP plants (coal and gas fired); 1700MW of small decentral CHP plants (gas and biomass); about 500MW of gas fired plants (non CHP); and 2400MW of wind capacity (mainly onshore). Figure 46 shows the installed plant capacities in Western Denmark by fuel type. Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West

108 98 Frontier Economics April 2010 Figure 46. Power plants in Denmark West in net plant capacities in MW Capacities by fuel Waste Oil Light Natural Gas Coal Hard Proc Gas Coal Generic Wind Fue l type Source: Frontier based on Platts and Danish energy authority ( The Danish system is connected to the NORDEL area via links to Norway and Sweden as well as to the UCTE area via interconnectors to Germany Today there is no interconnection between Eastern and Western Denmark, but a new link is expected to come online by end of Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West

109 April 2010 Frontier Economics 99 Figure 47. The Western Danish system international exchange capacities today DC link DK_W to Norway: 1000MW DK_West to Sweden: 740MW Model region DK_W DK_W to DE: 1500MW export 950MW import Source: Frontier Annual power demand in total Denmark (including grid losses) in 2008 was 36.1TWh of which 21.6 TWh are attributed to Western Denmark. Peak demand in Western Denmark in 2008 was 3.8 GW. The situation in Western Denmark in 2020 Power plant system in Western Denmark in 2020 The Danish system will continue to be dominated by wind power and thermal CHP generation. We assume a trend away from coal fired thermal generation towards even more (decentral) gas fired plants. In detail we assumed the following generation park by 2020: even more wind than today (4GW in 2020 vs. 2.4 GW in 2008); a slightly higher decentral CHP level than today (1.9GW in 2020 vs 1.7 GW in 2008); and Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West

110 100 Frontier Economics April 2010 slightly less coal and more gas capacity. In terms of new entry this will require: a replacement of 1.5GW of small decentral gas motor plants; a new 400MW CCGT CHP plant; a new 100MW OCGT Plant; and a new 100MW OCGT plant. In order to depict the effect of a storage plant we also assumed a new 100MW CAES plant to be available in Demark West by Figure 48. Overview nominal capacities of the power plant system in Denmark West in % 23% Large non CHP Large CHP Decentral CHP 53% 43% 0% 30% Nuclear Lignite Coal Gas Oil Hydro PHs and Reservoir Wind 0% 27% Source: Frontier based on Platts, Energienet and own assumptions We apply the same technology dependent power plant parameters for Danish power plants as we do for the rest of the system which we modelled. Details of those parameters can be found in the annexe 2. Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West

111 April 2010 Frontier Economics 101 Power and heat demand in Western Denmark We assume Danish power demand to increase slowly in the future. Starting from today s demand of 36.1 TWh/a (of which 21.6 TWh/a are consumed in Denmark West) we assume a slight increase of power demand in 2020 of 40.5 TWh/a (Denmark West 24.3/a TWh). This is in line with scenarios applied by Danish TSO Energienet and corresponds to our base case assumptions for other countries. According to scenarios from the Danish district heating association we assume a slight increase in power and heat demand in Denmark West compared to 2008 levels. For Denmark West we apply a heat demand covered by district heating units of 21 TWh/a. Figure 49. Assumed heat demand covered by district heating in total Denmark Source: Danish Heat plan, www. Energymap.dk Interconnectors in 2020 As Danish authorities and the TSO Energienet are aware of the need for further interconnection capacity to cope with Danish wind power extension plans, a significant increase of interconnector capacity is expected for the Danish system. Apart from the COBRA cable and the 600MW Eastern/Western DC link further new links are proposed to connect Western Denmark with Germany (increase of about 1000MW) and Norway (increase of about 700MW). Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West

112 102 Frontier Economics April 2010 Figure 50. Existing and new links around Denmark (brown field show links that are enhanced or new built) DC link DK_W to Norway: 1700MW DK_West to Sweden: 740MW Model region DK_W DC link DK_West to DK_East: 600MW Online April 2010 HVDC Cobra 700MW Online 2016 DK_W to DE: 2012: 2000MW export 1500MW import 2017: 2500MW export 2500MW import Source: Frontier Fuel and carbon prices We apply fuel and carbon prices as in our base case. For Denmark we increase gas price for plants by 10% to reflect that Danish plants are mainly smaller units compared to normal gas plants in Germany or Netherlands and thus pay higher gas prices at the plant gate; that Danish gas prices for industry are among highest in Europe today (partly due to taxes) 54 ; and 54 Compare Eurostat, Gas prices first semester 2009, Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West

113 April 2010 Frontier Economics 103 that Danish gas production will strongly decline by 2020 and that Denmark will become a gas importer Overview of model results of our COBRA case study Changes in plant dispatch and international flows due to the COBRA cable Applying the base case assumptions as presented in our main study and the additional assumptions for Denmark West as shown above we can observe the following effects of the COBRA cable: The new interconnector triggers new load flows between the Netherlands and Denmark in both directions. Netherlands will be a net exporter to Western Denmark. Some of these exports to Denmark will be transit flows to the Nordpool area (see Figure 52). This leads to a slight net increase in coal generation in the Netherlands and a decrease of coal based generation in West Denmark. Both countries can slightly increase their gas fired generation. As expected the main changes induced by the COBRA cable can be observed in Denmark and the Netherlands. However, plant dispatch is also affected to a lesser extent in other countries. Figure 51. Changes in plant dispatch and international exchange due to COBRA base case 4.5 Change through COBRA in TWh/a Extra power prod from Heat adjustments Imports other hydro oil gas coal lignite nuclear other EE in TWh Wind reduc in TWh Wind in TWh Compression in TWh Exports In TWh -1.0 Supply Demand Supply Demand Supply Demand Supply Demand Supply Demand NL BE FR DE DK_W Country Source: Frontier Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West

114 104 Frontier Economics April 2010 Figure 51 shows detailed effects of the new COBRA cable on international flows by comparing load flows of the model run with the COBRA cable versus the flows in the model run without the COBRA cable. Dutch exports to Denmark increase by about 3.7 TWh (from 0) accompanied with a small decrease in exports to Belgium and Germany. Exports from Denmark to the Netherlands are about 1/3 of the exports from the Netherlands to Denmark. It is interesting to see that also the exports from Denmark to Germany and the Nordpool area is increased by the COBRA cable. This means that flows to Denmark are to a significant extent transit flows to those countries. The stronger grid allows to share the flexibility burden via Denmark with Germany and the Nordpool area. Figure 52. Changes to international flows induced by COBRA - detailed 4.0 Change through COBRA in Exchange to a Country in TWh/a DE NL BE FR CH AT CZ PL DK_W GB ES NE From Country NE ES GB DK_W PL CZ AT CH FR BE NL DE Source: Frontier Figure 53 shows the seasonal average of hourly flows between Denmark and the Netherlands. Exports from the Netherlands are shown as negative values. It can be observed that exports mainly occur during night hours over all seasons whereas in the morning the flow is reversed mainly in winter months. Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West

115 April 2010 Frontier Economics 105 Figure 53. Seasonal average of hourly flows between Denamrk West and the Netherlands in the base case in Average Exchange in MW Exports_Spring Exports_Autumn Exports_Summer Exports_Winter Imports_Spring Imports_Autumn Imports_Summer Imports_Winter Hour of day Source: Frontier Price implications of the COBRA cable In line with the observed power flows the new line will have a small price increasing effect in the Netherlands and a significant price decreasing effect in Western Denmark. Average Danish power prices will be decreasing as Dutch coal and gas fired generation (benefitting from lower gas prices) is exported to Denmark; and the cable provides some flexibility in hours with steep ramp rates in the Danish system which without the cable could lead to demand curtailment or extreme expensive generation in Denmark West. Average power prices in Germany, Belgium and France are hardly affected by the new line (see Figure 54). Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West

116 106 Frontier Economics April 2010 Figure 54. Price effect of the COBRA cable in the base case with 12 GW of wind in the Netherlands Base price in EUR(2010)/MWh Base price with COBRA Base price without COBRA 10 0 DE NL BE FR DK_W Region Source: Frontier Role of the COBRA cable in case of alternative wind targets in the Netherlands As a further sensitivity we re-ran the model for a situation with the COBRA cable and assuming the wind target of 6GW (rather than the now proposed 12 GW) for the Netherlands. It is interesting to note that the introduction of COBRA does not change the principle picture we drew in our main study. Even with the introduction of COBRA the key flexibility to cope with addition of 6GW of wind capacity in the Netherlands still comes from (other) international exchange with the CWE region and the adaption of thermal plant dispatch. the extra exports to Denmark West that result from the higher wind target are on average rather low as the cable would already be used in the 6 GW wind capacity case to export towards Denmark and Nordpool area. Therefore COBRA makes little incremental contribution to cope with flexibility when the wind target is raised from 6GW to 12GW. Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West

117 April 2010 Frontier Economics 107 Figure 55. Effect of 12GW vs. 6 GW wind target on plant operation and exchanges with the COBRA cable 25.0 Change 12GW vs 6GW with COBRA in TWh/a Extra power prod from Heat adjustments Imports other hydro oil gas coal lignite nuclear other EE in TWh Wind reduc in TWh Wind in TWh Compression in TWh Exports In TWh Supply Demand Supply Demand Supply Demand Supply Demand Supply Demand NL BE FR DE DK_W Country Source: Frontier The COBRA cable in a situation with more wind curtailment in the Netherlands We also looked at a situation where the flexibility in the Dutch system is lower than in the base case. As in our main study, we derive such a situation by assuming a need for manual reserve of 2300MW instead of 1700MW as in our base case; introducing a reserve requirement also in neighbouring countries; and applying a must run condition (no stopping of coal plants during night hours) on Dutch coal plants. In such a situation a significant amount of wind curtailment occurs in the Netherlands (~3 TWh/a). The COBRA cable can help to avoid about 1/3 of that. COBRA allows transits to Nordpool area and Germany; COBRA slightly increases utilisation of Dutch coal plants. Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West

118 108 Frontier Economics April 2010 Figure 56. Effect of the COBRA cable in the curtailment scenario Extra power prod from Heat adjustments Imports Change through COBRA in TWh/a other hydro oil gas coal lignite nuclear other EE in TWh Wind reduc in TWh -1.0 Wind in TWh -1.5 Supply Demand Supply Demand Supply Demand Supply Demand Supply Demand Compression in TWh Exports In TWh NL BE FR DE DK_W Country Source: Frontier Annexe 1: Case study Effect of the COBRA link between the Netherlands and Denmark West

119 April 2010 Frontier Economics Annexe 2: Data used in simulations This annex provides a summary of the data used in our simulations of the Central West European market (Netherland, Germany, Belgium and France) in As described further below, other countries or areas to which these core countries are interconnected are treated as satellite regions with assumed hourly power price profiles. Netherlands plant park in 2020 To derive the plant park in 2020 we took the following steps: Confirmed our information on date of commissioning and the capacity of the existing plant park with EnergieNed (for major plants). Reconciled the results to CBS data for CHP plant capacity for major plants and added blocks of plant to represent smaller CHP motors and other CHP plant not included in the plant specific data. Added data on thermal plant already under construction in the Netherlands and a single new 1000 MW nuclear power plant at EnergieNed s request at a projected commissioning date. Projected plant retirements based on the relevant technology and a lifetime of 40 years for coal-fired plant and 35 years for gas-fired plants. We also assumed that the nuclear plant at Borssele will still be operating in Added wind capacity in a linear fashion from the current installed capacity of 2 GW up to the assumed capacity in 2020 for each scenario. Overview: development of power plants in the Netherlands up to 2020 Figure 57 shows the development of different types of technologies in the Netherlands up to the year All the capacities have been derated according to the capacity credit figure given in Table 5, in order to account for the expected availability of the different technologies. The development of capacities is put into perspective by comparing it to our demand projections for the Netherlands. Annexe 2: Data used in simulations

120 110 Frontier Economics April 2010 Figure 57. Evolution of different generation technologies in the Netherlands (derated capacity) 30,000 25,000 Aggregated capacity (MW) 20,000 15,000 10,000 5,000 Nuclear CHP Coal Demand renewables Gas Wind Source: EnergieNed and Frontier For our model we used data at generating unit level for the Dutch power plant system in 2020 which we derived from looking both at the age structure of existing plants and plans for new build. In the following paragraphs we set out information on: all thermal plants in the Netherlands included in the model for 2020; new plant additions included; retirement of existing plants included. In addition, we have incorporated renewable energies such as wind power or biomass pants Existing power plant system in the Netherlands 2020 plant-by-plant basis Figure 42 and Figure 58 list the existing plants in the Netherlands assumed to be still operating in 2020 by technology type and capacity. Annexe 2: Data used in simulations

121 April 2010 Frontier Economics 111 Figure 58. Existing plants in the Netherlands Plant Name technology capacity Gelderland 13 Coal 602 Hemweg 8 Coal 630 Maasvlakte 1 Coal 540 Maasvlakte 2 Coal 540 Borssele 12 Coal 403 Amer 8 Coal district heating 645 Amer 9 Coal district heating 600 Velsen 25 blast furnance gas 361 Borssele 30 Nuclear 500 Eems EC 3-7 CCGT 341 Eems EC 4 CCGT 341 Eems EC 5 CCGT 341 Eems EC 6 CCGT 341 Eems EC 7 CCGT 341 Demkolec CCGT 253 Intergen CCGT 770 WKC Almere Gas district heating 64 WKC Almere Gas district heating 54 Leiden Gas district heating 81 Den Haag Gas district heating 78 R'dam Galileistr Gas district heating 219 RoCa ROC 3 Gas district heating 221 Lage Weide Gas district heating 247 Merwedekanaal 11 Gas district heating 103 Merwedekanaal 12 Gas district heating 224 Diemen Gas district heating 249 Purmerend Gas district heating 69 Air Products Gas industrial CHP 42 UCML Gas industrial CHP 80 IJmond Gas industrial CHP 144 Centrale Moerdijk Gas industrial CHP 339 WKC Swentibold Gas industrial CHP 233 Terneuzen Elsta Gas industrial CHP 475 Delesto 2 Gas industrial CHP 340 Source: EnergieNed and Frontier Annexe 2: Data used in simulations

122 112 Frontier Economics April 2010 Figure 59. Existing plants in the Netherlands - continued Plant Name technology capacity Delesto 1 Gas industrial CHP 190 Salinko Hengelo vof Gas industrial CHP 104 Shell Raffinaderij Pernis PER+ Gas industrial CHP 127 Eemshaven-NEW Coal 1,600 Magnum-NEW gasified coal 1,300 Maasvlakte-NEW gasified coal with carbon capture 1,070 Sloecentrale_Vlissingen1 and 2-NEW CCGT 870 Flevo2-NEW CCGT 870 Europoort Rijnmond-NEW CCGT 840 Maasvlakte-NEW Coal 800 Maasbracht_Claus-NEW CCGT 635 Rijhnmond_B-NEW CCGT 419 Moerdijk_2-NEW Gas district heating 400 New NUKE Nuclear 1,000 NEW CAES Compressed air storage 100 non specific gas motors 1 Motor CHP for Greenhouses 100 non specific gas motors 2 Motor CHP for Greenhouses 200 non specific gas motors 3 Motor CHP for Greenhouses 300 non specific gas motors 4 Motor CHP for Greenhouses 300 non specific gas motors 5 Motor CHP for Greenhouses 300 non specific gas motors 6 Motor CHP for Greenhouses 300 non specific gas motors 7 Motor CHP for Greenhouses 300 non specific gas motors 8 Motor CHP for Greenhouses 300 non specific gas motors 9 Motor CHP for Greenhouses 300 non specific gas motors 10 Motor CHP for Greenhouses 300 non specific gas motors 11 Motor CHP for Greenhouses 300 non specific gas motors 12 Motor CHP for Greenhouses 500 Non-specific decentralised CHP 1 Gas industrial CHP 300 Non-specific decentralised CHP 2 Gas industrial CHP 300 Non-specific decentralised CHP 3 Gas industrial CHP 300 Non-specific decentralised CHP 4 Gas industrial CHP 300 Non-specific decentralised CHP 5 Gas industrial CHP 300 Non-specific decentralised CHP 6 Coal industrial CHP 400 Other green capacities at 2020 Intermittent green capacities 3,015 Wind Intermittent Wind 6,000 or 12,000 Source: EnergieNed and Frontier New built plants in the Netherlands taken into account in the despatch model Table 2 shows new thermal plants under construction that has been taken into account in our modelling. As there are an abundance of plans for new plants in the Netherlands, we decided to only consider the ones shown below that are stated in published sources to be already under construction, plus the new nuclear plant. Annexe 2: Data used in simulations

123 April 2010 Frontier Economics 113 Table 2. New thermal plant additions (non CHP) - Netherlands Name MW Technology Comm. Date Eemshaven-NEW 1600 coal 2013 Magnum-NEW 1300 coal 2012 Maasvlakte-NEW 1070 coal 2012 Sloecentrale Vlissingen1 and 2-NEW 870 CCGT 2009 Flevo2-NEW 870 CCGT 2009 Europoort Rijnmond-NEW 840 CCGT 2010 Maasvlakte-NEW 800 coal 2012 Maasbracht Claus-NEW 635 CCGT 2011 Rijhnmond B-NEW 419 CCGT 2010 Moerdijk 2-NEW 400 CHP 2011 New NUKE 1000 nuclear 2018 NEW CAES 100 CCGT 2015 Source: EnergieNed While taking into account new build power plants it is also important to form a view on the retirement of older existing power plants. Our assumptions on the retirement of existing plants are shown in Table 3. Annexe 2: Data used in simulations

124 114 Frontier Economics April 2010 Table 3. Plant retirements in Netherlands between 2009 and 2020 Name MW Technology Comm. date Decomm. date Claus A 640 Gas Claus B 640 Gas Velsen Gas Eems CCGT Bergum CCGT Bergum CCGT Harculo CCGT Hemweg CCGT Donge 121 CCGT RoCa 24 CHP RoCa 24 CHP Merwedekanaal 96 CHP Source: EnergieNed and Frontier For the sake of completeness, Table 4 shows plants that are currently only planned and which were therefore not considered. Table 4. New thermal plant additions (non CHP) - Netherlands Name MW Technology Comm. Date Eemshaven 1200 CCGT 2015 Maasvlakte 600 CCGT 2011 Ijmuiden 600 Ind CHP CCGT 2012 Amsterdam, Hemweg 550 probably DH CHP CCGT 2015* Diemen 550 probably DH CHP CCGT 2015* Bergum 454 Unknown 2014 Europoort 450 probably CHP Coal 2012 Schoonebeek 130 CHP 2011 Source: EnergieNed Figure 60 provides information on our assumptions concerning the power and heat capacity of CHP plant in In total CHP capacity of 11 GW is projected for 2020 of which the district heating is assumed for the most part to have some flexibility in terms of heat to power ratio and industrial and greenhouse CHP are assumed to be inflexible. Annexe 2: Data used in simulations

125 April 2010 Frontier Economics 115 Figure 60. CHP plant capacity Netherlands; 2020 Power capacities by sector CHP capacities evenly spread among sectors total 11 GW ( GW) Flexible CHP dominates DH sector Other sectors rather inflexible HOBs give additional flexibility Heat capacities by sector CHP capacities evenly spread among sectors total 14 GW ( GW) Flexible CHP in DH sector Higher HtoP in the DH sector HOBs take over higher parts of generation In all sectors 10% excess HOB capacity Source: Frontier Economics Plant parks in other CWE countries Plant parks in other countries are based on Frontier experience in other modelling assignments. The assumptions about nuclear capacity are worth highlighting: in Germany, life extension of up to 40 years (on average + 7 years) for all plants except Krümmel; in Belgium, life extension by 10 years of the three oldest plants; and in France, additions and retirements assumed to match with no net change in nuclear capacity. Figure 61 shows our assumptions concerning plant capacity and technologies in All the capacities have been derated according to the capacity credit figure given in Table 5, in order to account for the expected availability of the different technologies. Annexe 2: Data used in simulations

126 116 Frontier Economics April 2010 Figure 61. Installed capacities (derated), by technology in CWE in Aggregated, derated capacity (MW) Wind other RE Other Gas Coal Lignite Nuclear Hydro BE FR DE Source: Frontier Plant characteristics Conventional thermal plants Table 5 shows the main characteristics used to model conventional thermal plant. 55 The values of each characteristic for each technology were adopted from our experience of modelling similar plant elsewhere in Europe. 55 Other parameters we used were technology specific idle costs, start up costs and start up attrition costs. Annexe 2: Data used in simulations

127 April 2010 Frontier Economics 117 Table 5. Key plant characteristics used for conventional thermal plant Plant Type Efficiency at optimum part load efficiency maximum ramp rate minimym stable generation capacity credit lifetime in years Nuclear 33% 28% 40% 70% 90% 40 Lignite 30% - 45% 25% - 40% 40% 50% 90% 40 Coal 32% - 50% 27% -45% 40% 40% 90% 40 IGCC 48% 44% 60% 45% 90% 40 CCGT 52% - 60% 42% - 50% 65% 35% 90% 35 OCGT 27% -46% 22%-42% 100% 75% 90% 30 Oil 37% -43% 32% - 38% 60% 40% 90% 40 Hydro 85% 80% 100% 0% 90% 100 Wind % 10% n.a. Source: Frontier Economics Assumptions on CHP plants For the CHP park we need to make assumptions about both the power and the heat side of the plants. This includes Heat side Power side heat capacities of the plants; hourly heat demand profile (differs by sector); standard power to heat ratios; power loss factors for flexible plants; and existing Heat only Boilers (HOBs) at CHP plant side that help to cover heat demand peaks and that can be use to make CHP production more flexible. pure electrical efficiency and fuel efficiency in CHP mode; power capacity minimum load conditions; ramp rates; and eligibility to provide reserve for the TSO. The heat side assumptions on CHP technologies differ by sector. This takes into account the different requirements in those areas. Key differences are: Annexe 2: Data used in simulations

128 118 Frontier Economics April 2010 Industrial sector industrial CHP plant operators concentrate on heat delivery for their core business the making of their product. Heat demand is quite stable and the plants in consequence are relatively inflexible. Plant operators try to operate in a stable operation mode without focussing too much on the hourly wholesale power price. District heating the heat demand profile shows a strong seasonal effect as heating demand from housing is low in summer and high in winter. Those plants are a lot more flexible than industrial CHP plants. They are often also linked by a heat grid which gives them additional flexibility. Greenhouse Greenhouses often operate a small gas motor for their site. Those are from a technical point of view rather inflexible in isolation. However, often heat storages or HOBs are used in combination, so that some flexibility can be expected from that side. Figure 62 summarizes some key assumptions on CHP plant related heat demand, HOB availability and how those deviate by sector. Figure 62. CHP and HOB capacity and heat demand assumptions by sector Description Industry District heating Flat heat demand of about 90% of installed heat capacity (CHP+HOB) max heat capacity is 110% of peak demand HOB capacity is 40% of installed heat capacity, CHP is 70%. (=>10% excess heat capacity) Seasonal and hourly profile as kindly provided by Nuon Winter (avg 45% of cap), summer (10% of heat cap) CHP plant covers 60% of peak heat demand, 50% of peak demand is covered by HOB Greenhouses As District heating curve, but scaled up by 10% to meet CBS statistics better Hourly DH heat demand profile used Mostly inflexible CHP plants (motors) Source: Frontier Economics Annexe 2: Data used in simulations

129 April 2010 Frontier Economics 119 Following review of a range of different sources and discussions with Nuon s CHP expert, we adopted the plant characteristics for different types of CHP plant shown in Table 6 Where we had specific information from individual plants e.g. on power or heat capacity we used those information instead of the standard values. Table 6. Typical CHP Plant characteristics Plant type Minimum load condition as % of power capacity peak heater capacity as % of plant heat capacity heat to power ratio power "win" factor total efficiency IND_CCGT_CHP_Flex 45% 47% 120% % IND_CCGT_CHP_inflex 45% 47% 120% 0 92% IND_OCGT_CHP_INFLEX 50% 47% 250% 0 91% IND_COAL_CHP_FLEX 45% 47% 110% % IND_COAL_CHP_INFLEX 45% 47% 110% 0 88% DH_CCGT_CHP_Flex 45% 57% 120% % DH_CCGT_CHP_inflex 45% 57% 120% 0 95% DH_OCGT_CHP_INFLEX 50% 57% 250% 0 88% Greenhouse_OCGT 50% 57% 250% 0 88% Greenhouse_MOTOR 50% 57% 134% 0 94% DH_COAL_CHP_FLEX 45% 57% 131% % DH_COAL_CHP_INFLEX 45% 57% 131% 0 92% Source: CBS Statistics for 2008; Bart Ummels 56 ; Some data kindly provided by Hans Rödel; plus other Frontier Experience Wind infeed assumptions We have derived wind infeed assumptions in the same manner for both the 6 and the 12 GW cases. Offshore wind is assumed to have a higher load factor than onshore wind. We have taken account of correlation between wind infeed in the Netherlands and its CWE neighbours. The approach and main assumptions are shown in Figure 63. The result is that in the 12 GW case there is 38 TWh of wind generation and in the 6 GW case there is 17 TWh of wind generation. The additional wind generation more than doubles because of higher offshore load factors. The load factors for Dutch wind units take account of: the proportion of offshore to onshore wind power capacities; and new onshore capacities will include units which can benefit from higher wind speed than those used onshore today. 56 Bart Ummels (2008); Power System Operation with Large-Scale Wind Power in Liberalised Environments; Dissertation at the TU-Delft Annexe 2: Data used in simulations

130 Frontier Economics April 2010 Figure 63. Wind infeed assumptions for the Netherlands Onshore Wind 100% 90% Peak specific infeed 84% of capacity We use historic wind infeed data for Germany (1/4h values for 2008) We calculate hourly specif. infeed per MW installed. We use EON grid data as proxy for NL. Specific FR and BE wind infeed 80% correlation to DE assumed (70% for FR/ BE); Values scaled up to published full load hours/a Houly specific utilisation in % 80% 70% 60% 50% 40% 30% 20% 10% 0% ,264 1,685 2,106 2,527 2,948 3,369 3,790 4,211 4,632 5,053 5,474 Hours of year 5,895 6,316 6,737 7,158 7,579 8,000 8,421 Specific utilisation of wind plants in Germany "Duration curve" of specific wind infeed In 7000h less than 30% infeed. Offshore wind Derive hourly values from onshore German data Scale up to receive higher full load hours (3300 h/a) Add a band to reflect less volatile profile Cut peak specific infeed to 90%. Higher correlation NL with Germany as onshore (80% rather than 70%) Houly specific utilisation in % 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 421 Higher utilisation hours 841 1,261 1,681 2,101 2,521 2,941 3,361 3,781 4,201 4,621 5,041 5,461 5,881 6,301 Hours of year 6,721 7,141 7,561 7,981 8,401 Specific utilisation of wind plants in Germany "Duration curve" of specific wind infeed More stable utilisation, but higher peak infeed Source: Frontier Economics Interconnection capacity The interconnection capacity assumed between the Netherlands and its neighbours (CWE and the satellite areas of Great Britain and Norway) and between CWE countries and all satellite areas in 2020 are shown in Figure 64. Please note that the model regions, which are simulated in detail, are in red whereby the satellite regions are green. By 2020 we assumed a higher transfer capacity available to market participants for power exchange between the Netherlands and its CWE neighbours (Germany and Belgium) than is the case today. This increase in exchange capacity is assumed to come from more efficient use of existing interconnectors and a new line between Wesel and Doentichem. We did not include the Cobra HVDC cable to Denmark which is under discussion between Tennet and Energinet DK. Annexe 2: Data used in simulations

131 April 2010 Frontier Economics 121 Figure 64. Interconnection capacity assumptions for 2020 Model Regions GB 1,000 MW NO/SE/FI 700 MW 1,100 MW DK Satellite Regions PL 2,000 MW 1,000 MW Belgium 2,300 MW Netherlands NL DE* 3,739 MW DE NL * 3,900 MW Germany FR DE 2,400 2,850 MW DE FR 2,700 5,600 MW ES France 3,200 MW CH AT CZ Sources: UCTE and ETSO NB. No BE to DE or NL to DK-W (COBRA) links assumed No aggregate constraints on imports or exports to or from NL assumed Source: ETSO and TSO web sites We did not include any internal grid constraints within a model region as we assume that major ones will be identified and will be substantially resolved by Annexe 2: Data used in simulations

132

133 April 2010 Frontier Economics Annexe 3: Experience in other EU countries with significant wind and CHP generation We have focussed our review of other EU countries primarily on Denmark (as written in the terms of reference) but we have also considered Spain and Germany as we think that this could give us some additional insights and could show potential ways to address the challenges related to the integration of large amounts of wind power. Wind power in Denmark We have investigated the impact of wind power in Denmark in order to extract potential lessons for EnergieNed. We have focussed on Denmark West because the level of wind penetration is comparable to that envisaged for the Netherlands in 2020 under some scenarios, with production equal to 22% of gross consumption, and is significantly higher than in Denmark East. The systems are not interconnected. To review the way the system operates, we downloaded data from Energinet.dk for the 12 month period from July 2008 to June This was a period when few additions were made to wind production capacity. We then carried out a telephone interview with an economist from the company. Looking to the future, Denmark s energy policy is to produce 50% of its electricity requirements from wind energy by 2025, over double the present proportion. More radical measures to those already taken are envisaged in order to absorb this higher level of wind production. Overview of system Denmark West is synchronised to the UCTE system via an interconnector with Germany with a capacity of 1615 MW. There is a DC link to Norway with a capacity of 1000 MW and a line to Sweden with a capacity of 740 MW. In total, there is 3355 MW of interconnection capacity. There are transit flows of power across Denmark to and from Germany and the Scandinavian countries. Maximum demand in 2008/9 was 3.6 GW. There was some 2.5 GW of installed wind generation capacity. For the 12 month period under consideration, production and consumption data is set out in Figure 65. Most of the local production is from CHP plant. Annexe 3: Experience in other EU countries with significant wind and CHP generation

134

135 April 2010 Frontier Economics 125 Figure 65. Production and consumption data for Denmark West in Primary production 13,629 65% Local production 4,790 23% Wind production 4,580 22% Net interchange -2,034-10% Gross consumption 20, % Energienet.dk for July 2008 to June 2009 Wind generation and its implications 11.2 About half the installed wind capacity is contracted directly to the Energinet.dk under legacy arrangements for wind energy that resemble those currently in operation in Germany. This wind production is paid for at a feed in tariff. Energienet.dk sells most of this energy through Nordpool, much of it in the spot market. The other half of more recently constructed wind production capacity, including all offshore wind, belongs to a number of balance responsible parties, some of which focus on wind generation while others have a portfolio of plant of different technologies. These wind producers sell the energy themselves but receive a premium on each MWh produced as an incentive A histogram of wind energy output is shown in Figure 66 and emphasises the variability of wind production. High levels of wind production are rare but for about half the year the output is 300 MW, equivalent to one eighth of the installed capacity. The average load factor on the plant is 22%. Annexe 3: Experience in other EU countries with significant wind and CHP generation

136 126 Frontier Economics April 2010 Figure 66. Frequency of different levels of wind production - Denmark Distribution of wind generation in year Frequency MW Source: Frontier from energinet.dk data 11.4 Another way to consider the impact of wind production and relatively inflexible decentralised/local production is to consider the residual demand that has to be met by central production and interchanges. A histogram of residual demand is shown in Figure 67 and shows how the dispatchable production and interchanges with neighbouring countries have to deal with a wide range of residual load from levels that approach 70% of maximum demand down to negative values for a small number of hours per year. As discussed later, this pattern takes account of the fact that much has already been done to make local production more flexible. Annexe 3: Experience in other EU countries with significant wind and CHP generation

137 April 2010 Frontier Economics 127 Figure 67. Histogram of residual demand - Denmark Residual demand (whole period) Frequency More MW Source: Frontier from energinet.dk data 11.5 The role of the different production sources and interchanges can be seen in Figure 68 which shows the contribution of each one in July 2008 when demand was relatively low. The change in wind output (red line) is compensated for the most part by changes in primary production and by changes in the net interchange. Figure 68. Contribution of production and interchanges in July Denmark 2,000 Wind production Local production 1,500 Primary production Net interchange position 1, Source: Frontier from energinet.dk data Annexe 3: Experience in other EU countries with significant wind and CHP generation

138 128 Frontier Economics April The impact of intermittent wind generation and relatively inflexible local production can be seen in the load duration and residual load duration curve. These are shown as line graphs in Figure 69 and highlight how the baseload part of the demand curve is significantly reduced due to wind and local production and, in consequence, primary production operates at lower load factors. Figure 69. Load and Residual Load Duration Curve - Denmark Gross demand Residual demand Source: Frontier from energinet.dk data 11.7 As expected, wind generation and net exports from Denmark West are correlated as the scatter plot in Figure 70 shows. Once wind generation reaches over 1000 MW there are few hours in which Denmark West is not exporting, but below this level the net interchange may be positive or negative, depending on relative prices. Annexe 3: Experience in other EU countries with significant wind and CHP generation

139 April 2010 Frontier Economics 129 Figure 70. Scatter plot of wind generation against net interchange with neighbours (imports are positive) - Denmark Interchange position (MWh/h) Wind generation (MWh/h) Source: Frontier from energinet.dk data It is also possible to analyse the relationship between wind generation and the Elspot price for Denmark West. The result is show in Figure 71 and indicates a weak correlation. The strong interconnection of Denmark West with its neighbours makes it possible to absorb the wind production in most hours without depressing the spot market price a great deal. However, there are a number of hours when the price falls to zero and more of these occur at high levels of wind production. High prices invariably occur when wind generation is low. Annexe 3: Experience in other EU countries with significant wind and CHP generation

140 130 Frontier Economics April 2010 Figure 71. Scatter plot of wind generation against Elspot price for DK-W Elspot price ( /MWh) Wind generation (MWh/h) Source: Frontier from energinet.dk data Managing fluctuating wind generation Denmark has adopted the following approaches to managing fluctuating wind generation: 1. Strong interconnection with neighbouring countries as noted above the level of interconnection as a percentage of maximum demand is very high. Denmark also plans to build a further DC connection with Norway and to interconnect the DK-W and DK-E systems across the Great Belt. The interconnection with Norway is especially important due to the hydro storage reservoirs on the Norwegian system. 2. Improving the predictability of wind generation Energinet.dk as a major reseller of wind power has put a lot of effort into improving its wind forecasts, as have the wind generators who are responsible for their own balancing. Denmark is also awarding offshore concessions for wind in a manner which will limit the correlation of wind fluctuations as wind capacity increases. For example by ensuring a balanced development of wind energy around the coasts. 3. Making CHP more flexible Denmark now requires all CHP plant with a capacity of > 10 MW to participate in the Nordpool spot market. Many CHP plants now have electric boilers fitted and they are Annexe 3: Experience in other EU countries with significant wind and CHP generation

141 April 2010 Frontier Economics 131 incentivised to use them when electricity is cheap and reduce electricity generation from CHP plants. To increase this incentive, Nordpool will shortly introduce changes to the market rules to allow spot prices to become negative when there is a surplus of production. 4. Making wind generation more flexible new wind turbines have the ability to be regulated and thus to provide downward reserve at times when electricity prices are very low (this is the same as wind curtailment). We understand that there is no legal requirement on this point it is being done because it makes sense for all parties. 5. Demand response although demand response is limited at present, Denmark has plans to roll out smart meters and related equipment both to allow small consumers to be given shorter term price signals and to permit certain loads which are not time sensitive to be reduced by remote control (thus providing a source of upward reserve) in return for some form of discounted price. 6. Intraday market the Elbas intraday market allows continuous trading up to one hour before real time (currently being revised to 45 minutes) in a range of products. The market is common to the Nordel area and to Denmark West 57 and North Germany. Our understanding is the bids and offers appear on screens on both sides of a border if there is interconnection capacity to deliver them. 7. Balancing after gate closure Energinet.dk holds daily tenders for manual reserve which have attracted new sources of capacity. An availability compensation fee is paid. The focus is on upward reserve rather than downward reserve there is a reluctance to pay generators to start so that they can be shut down. All manual reserve must be fully available within 15 minutes. Energienet.dk holds MW of manual reserve, depending on demand. Most of the reserve is held on thermal plant. 8. The TSO also has access to the common Nordel balancing market in which bids from across the regions are put on a common ladder for upward and downward regulation. Contracted reserve is required to be bid in the balancing market and is activated accordingly. Payment is based on the marginal offer accepted, excluding offers that are accepted for congestion management. Liaison between the four TSOs allows bids to be selected by any one of them which are economic but which can also be delivered across the interconnectors. Interconnector capacity is fully allocated through Elspot and no capacity is held back for balancing purposes. 57 Denmark West joined in 2007 Annexe 3: Experience in other EU countries with significant wind and CHP generation

142 132 Frontier Economics April Electricity storage there has been some feasibility work on electricity storage but no concrete actions or incentive programmes. Spain Spain offers strong financial incentives for both renewable generation and CHP which both form part of the special regime market. Basic facts about wind generation are shown in Table 7. The installed capacity has a load factor of about 24%. Most of the wind generation is currently onshore but there is a bigger incentive for offshore wind. Table 7. Basic facts about wind generation - Spain Total electricity demand 2008 (GWh) 263,530 Wind generation 2008 (GWh) 31,393 Wind generation/demand 12% Wind installed capacity on 31/12/2007 (MW) 14,107 Wind installed capacity on 31/12/2008 (MW) 15,874 Source: REE, Informe sistema eléctrico español 2008 Wind generators have a choice between: a feed in tariff which removes any responsibility for balancing; or a predefined premium on the market price with a cap and a collar. Wind generators can change between these options after 12 months. In 2008, when market prices were high, many wind generators chose the premium option, judging that the additional revenue would more than cover the additional risk and costs associated with balancing. Wind generators include both small specialist companies and large portfolio generators. Iberdrola, which also operates a large park of hydro plant, is the largest wind generator in Spain. In contrast, Endesa has recently sold its wind farms to Acciona. By law, all wind generators in Spain have to establish a control centre which forecasts wind output and is in direct contact with the TSO, Red Electrica. Iberdrola has a large centre near Toledo responsible for 6000 wind turbines and many small hydro generators. It is building a second control centre near Valencia. Annexe 3: Experience in other EU countries with significant wind and CHP generation

143 April 2010 Frontier Economics 133 Wind generators who participate in the market, have to manage their positions by: adjustment of their own flexible physical generation such as storage hydro and CCGT plants (if they have a portfolio); and/or by participation in the OMEL intraday market which comprises 6 auction sessions (not continuous trading) with the last session taking place 3h 25 minutes before real time. Figure 72 shows average monthly intraday market volumes which averaged 8% of demand in Figure 72. Intraday market volumes - Spain 3,500,000 3,000,000 2,500,000 2,000,000 MWh 1,500,000 1,000, ,000 0 Jan-07 Mar-07 May-07 Jul-07 Sep-07 Nov-07 Jan-08 Mar-08 May-08 Jul-08 Sep-08 Nov-08 Jan-09 Mar-09 May-09 Jul-09 Sep-09 Source: REE REE prepares a final schedule 1h 40 minutes before real time and thereafter relies on manual reserve and the balancing market to fine tune the system. REE does not participate in the intraday market. REE makes capacity payments for secondary reserve but only pays for manual reserve if called. However, it should be noted that almost uniquely in Europe, generators who participate in the day-ahead market are paid for capacity made available, as well as for energy generated. The capacity payment is shaped to be greatest when there is least surplus capacity. REE told us that forecasts of wind generation have improved significantly in the last 5 years due to better information management and technical progress. There is no policy action to force new wind turbines to be constructed in different areas to reduce correlation this is left to the market. Annexe 3: Experience in other EU countries with significant wind and CHP generation

144 134 Frontier Economics April 2010 When wind generation is high, market prices tend to be lower. However, occasions when the price approaches zero are very few and there are no plans to allow for negative OMEL prices. Figure 73 shows a plot of wind generation and market prices. Wind generation is lower in summer but, for other reasons, supply-demand conditions were tight and market prices were higher. We are not aware of any significant policy measures related to the management of fluctuations in wind generation but the following points are of interest: REE has started to offer a price for downward reserve to wind farms at present there is forced curtailment for about 20 hrs per year there have been discussions about requiring wind farms to maintain some form of power storage to smooth their output but no concrete action has yet been taken. Figure 73. Wind generation and market prices - Spain Source: Monthly electricity Bulletin, Intermoney Annexe 3: Experience in other EU countries with significant wind and CHP generation

145 April 2010 Frontier Economics 135 Germany 11.8 Renewable electricity generation contributed 15.1% of total electricity generation in 2008 of which 6.6% was wind production. Wind production was 40.4 TWh in 2008 and installed capacity at the end of the year was 23.9 GW. Since then 25 GW mark has been crossed. The development of renewable source of electricity generation in the last few years is shown in Figure 74 with the different laws defining the financial incentives shown. The most recent law, EEG 2008, is not shown. Figure 74. Development of wind generation - Germany Source: BMU Key features of wind generation in Germany are as follows: historically all wind production has been purchased at a feed in tariff by the four TSOs and the TSOs have been responsible for forecasting wind infeed and for balancing; the new EEG 2009 contains a target of 30% power generation from renewable energies by 2020 most of the incremental quantities will need to come from wind energy; the investment in offshore parks has been delayed in recent years as EEG tariffs for offshore wind in Germany did not encourage investors to take over the technological risks; developers focussed more on other onshore wind in Germany and other countries. The new EEG 2009 now has significantly improved the conditions for offshore wind so that investments - in particular in the North Sea area are taking place; Annexe 3: Experience in other EU countries with significant wind and CHP generation

146 136 Frontier Economics April 2010 the EEG 2008 introduces an option for generators to sell a share of their production on the open market (and be responsible for imbalance) at a notice period of one month however this is very limited at present; the TSOs will in future sell the wind energy in the market but historically it was transferred to supply utilities as a band. From 2012 a new entity selected by tender will be responsible for selling the wind energy; most wind energy is located in Upper and Lower Saxony and in Brandenburg. It cannot all be used locally but there important constraints in the transmission network to the movement of energy southwards, pending reinforcement. This illustrates the issues that arise when wind generation is developed on a large scale in a relatively concentrated area and is injected into a grid which has been planned to serve regional demand. Wind generation which has to be curtailed is entitled to compensation; to even out the task of managing the fluctuations and the financial and administrative issues associated with wind generation across the four TSOs, there is a horizontal sharing of responsibilities so that VET and Transpower in the North do not bear a disproportionate share of the total; the TSOs manage fluctuations in wind generation in the following manner: using intraday trading based on updated forecasts of wind generation and load (in practice up to 2 or 4 hours ahead); balancing energy minute reserve is then used to balance the overall error arising from forecasts of load, wind infeed and power plant outages in each ¼ hour period; a major expansion in offshore wind plant is expected to take place over the next few years with the first installation commissioning in August German experience shows how the need for new grid lines can lead to significant delays in for development of wind energy. As the approval process for new lines can easily last for up to 10 years, the ambition for new wind additions outpaced the required grid expansion. Therefore a new law (the EnLAG) has been introduced which aims to accelerate building of new high voltage lines (or even installation of expensive high voltage cables). Against this background the following points arise in relation to the integration of wind energy in Germany. We consider TSO related measures and factors arising in relation to power plants separately. The TSO related measures: Annexe 3: Experience in other EU countries with significant wind and CHP generation

147 April 2010 Frontier Economics 137 The regulator has already accepted the necessity of new lines which are needed to transport wind power from North to South. TSOs can get approval for so called investment budgets which in general makes those investments more attractive than normal replacement investments. Coordination of balancing market there are strong movements towards a single balancing market in Germany across all four control areas. As wind power increases balancing costs, the efficiency of these markets becomes more important. TSO are also taking measures to promote market integration There are movements towards a better integration of the German market into the CWE region. This includes alignment of gate closure for the day-ahead market, the more efficient utilisation of existing interconnection capacities as well as a coordinated extension of interconnectors. TenneT and Amprion have already started a cooperation to improve the transfer between Netherlands and Germany. There are discussions about building a new line to Norway to make use of the flexible hydro system to balance the power system in Germany. Measures arising in relation to power plants include: The new government extends the operation of nuclear power plants in Germany. This reduces the need for new power plants and will most probably end in less investment in new (flexible) power generation. There are ongoing discussions about how to promote investments into power storage within the framework of the EEG (Renewable Energy Law). The ambitious wind targets and the life time extension of nuclear power has already led to the cancellation of some announced power plant projects in Germany. CHP - The government wants to increase the percentage of electricity demand met by CHP in Germany to 25% by It might be difficult to achieve this target because, at the same time, energy efficiency improvement programs aim at reducing heat demand. There is no specific incentive or regulatory measure to flexibilize CHP plants but economic factors may drive investors to choose flexible CHP technologies as there are likely to be hours with very low or even negative power prices in Germany in the future. Annexe 3: Experience in other EU countries with significant wind and CHP generation

148

149 Frontier Economics Limited in Europe is a member of the Frontier Economics network, which consists of separate companies based in Europe (Brussels, Cologne, London & Madrid) and Australia (Brisbane, Melbourne & Sydney). The companies are independently owned, and legal commitments entered into by any one company do not impose any obligations on other companies in the network. All views expressed in this document are the views of Frontier Economics Limited.

150 FRONTIER ECONOMICS EUROPE BRUSSELS COLOGNE LONDON MADRID Frontier Economics Ltd 71 High Holborn London WC1V 6DA Tel. +44 (0) Fax. +44 (0)