POWERGEN Europe 2015 Market Reform Policy Options. Case Example Germany. By Melle Kruisdijk, From Wärtsilä

Transcription

1 POWERGEN Europe 2015 Market Reform Policy Options Case Example Germany By Melle Kruisdijk, Director, Market Development Europe From Wärtsilä Paper ID number: T1S2P2 Page 1

2 TableofContents 1. Introduction... 3 Germany and the Energiewende Quantitative Analysis... 9 Revenues and profitability Total system costs Modelling results New conventional CCGT plant remains commercially unviable The EOM scenario provides stronger incentives for low capex, flexible generation technologies EOM 2.0 is found to deliver at lower overall cost per annum than the CM Conclusions and Recommendations References Page 2

3 1. Introduction Over the last decade, the EU has shown strong commitment to decarbonise its economy. By 2020, the EU defined that following three key objectives i should be achieved: A 20% reduction in EU greenhouse gas emissions from 1990 levels; Raising the share of EU energy consumption produced from renewable resources to 20%; A 20% improvement in the EU's energy efficiency. The energy sector is seen as one of the main enablers for achieving these objectives and EU member states have developed specific policy to achieve the goals through, amongst others, this sector. Member states initiated support schemes to attract significant amounts of low carbon renewable capacity into the energy mix. In 2012, the EU commitment to decarbonise its economy was prolonged to 2030 and further strengthened, when the European council concluded in October of that year the following targets ii : At least 40% emissions reduction in EU greenhouse gas emission from 1990 levels; Raising the share of EU energy consumption produced from renewable resources to 27%; A 27% improvement in the EU s energy efficiency. The effects of all of this on the electricity markets have become clearly visible over the last years. Electricity production from renewable energy sources has increased strongly in the EU. Figure 1 shows the production for different technology sources. The strong increase in energy produced by Renewable Energy Sources (RES) is clear (as is also the decline of produced energy from conventional sources). Page 3

4 Figure 1: production for different technology sources in the EU-28, in TWh. Source: Eurostat Most European electricity markets are organized as Energy Only Markets (EOM), where power plants are dispatched based on their Short Run Marginal Costs (SRMC). The power plants with the lowest SRMC are dispatched first, until supplied energy is in balance with demand. RES such as Wind and Photo Voltaic (PV) have relative high initial capital costs, but close to zero operational costs and therefore close to zero SRMC. Due to the merit order effect, low SRMC RES capacity will be called upon first. Note that this will even be the case when so-called dispatch priority (a regulatory benefit enjoyed for energy produced through RES in several EU member state markets) is no longer valid. The effect is clearly shown in figure 2. Conventional power plants will operate less hours during the year. Page 4

5 Figure 2: impact of merit order effect on conventional thermal generation. Source: Agora Energie wende, 12 Insights on Germany s Energiewende Figure 2 also shows that the intersection of the supply and demand curve leads to a lower whole sale electricity price. In addition to reduced operating hours, conventional power plants therefore also see reduced earnings during these hours. As a result, profitability of conventional power plants is under pressure and many conventional power plant owners consider (or have already initiated) mothballing and even closure of these assets. However, energy provided by RES is by nature related to weather conditions and though forecast technologies improve, ultimately weather conditions determine when and how much energy is produced. The production from these sources is therefore intermittent and difficult to forecast, especially for time frames long before actual delivery. Since demand is still rather inelastic, dispatchable capacity is required in the capacity mix to provide the balance for the fluctuating production from RES and maintain security of supply on the system. These fluctuations can be over longer period (when the wind stops blowing for several days) and very short intervals (when several GW of firm power is required within an hour). Flexibility is seen as the solution for this challenge; both on the production side (flexible power generation) as well as on the demand side (Demand Side Response (DSR)). Additionally, storage solutions such as battery technology or pumped storage hydro can also be used to store produced (renewable) electricity and release it in times when it is required. Though solutions are available, investments in flexibility solutions are not coming forward. Policy makers have over the past years considered how electricity market design can be adjusted to provide market based incentives for these technologies. The market design should provide solutions to the following challenges: 1. Adequacy - Long term security of supply: how can electricity market provide investments signals for secure capacity? Page 5

6 2. Balancing - Short term security of supply: how can electricity markets provide investment signals for required capabilities? This paper will describe two electricity market reform policy options currently under debate in Europe: an updated Energy Only Market (EOM2.0) and a Capacity Market (CM). The paper compares the two options on following core policy goals: Overall system costs: wholesale power costs and any payment under a CM Industrial policy implications: analyse and quantify the impact of a CM / EOM2.0 on the earnings situation of selected conventional power plant technologies The paper will investigate these options through an analysis using Germany as case example, conclude which market reform option delivers best to the policy goals and will make further recommendations. These recommendations should be considered as important guidelines for other markets in transition towards an energy system relying mostly on zero or low marginal cost RES balanced with flexibility resources. GermanyandtheEnergiewende The German Federal Government implemented strong policy measures to decarbonise its economy compared to other EU member states. The goals of this Energiewende by the German government are the following reduce greenhouse gas emissions by 40 percent compared to 1990 levels by 2020; cut primary energy consumption by 20 percent compared to 2008 levels by 2020; increase the share of renewables in the electricity production mix to percent by The German Federal Government has set following goals for By then: greenhouse gas emissions are to be reduced by percent compared to 1990 levels; cut primary energy consumption by 50% compared to 2008 levels; increase the share of renewables in the electricity production mix to at least 80 percent. Figure 3 shows the development of the German capacity over the years 2008 to A strong increase in capacity from PV and Wind can be seen. Page 6

7 Souce: Nuclear Fossil (including pumped hydro) Renewable Energy Sources Figure 3: development of produced Electricity per source in Germany, Source: Agora Energiewende, Die Energiewende im Stromsektor: Stand der Dinge Rückblick auf die wesentlichen Entwicklungen sowie Ausblick auf 2015 Clearly these goals are much more far-reaching compared to the overall EU goals. Through these measures Germany qualifies as a front-runner in decarbonising its economy, both in Europe as well as worldwide. Germany is also a front runner in facing the challenges associated with implementing significant amounts of renewable energy sources into the power system and maintaining security of supply in both Adequacy and Balancing. And therefore an excellent case study of potential solutions to these challenges. Lessons learned from the Energiewende can prove highly valuable for other states following a similar path. The German Federal Ministry for Economic Affairs and Energy (BMWi) identified these challenges and responded in October 2014 with the publication of the discussion paper An Electricity Market for Page 7

8 Germany s Energy Transition, also known as the Green Paper iii. The Green Paper is intended to provide the basis for the market design decisions to be taken in The Green paper describes measures that are considered to make sense, irrespective of the later presented fundamental policy decision ( no regret measures ). This concerns amongst other strengthening the pricing signals in the electricity market and the related ancillary services markets. The paper also presents two options as solution to ensure that sufficient capacity is available at all times. The fundamental policy decision between the two options is the following: trust in an optimised electricity market (energy only market 2.0 (EOM2.0)) or to introduce a second market (the capacity market (CM)) to hold capacity available. To provide insight into the effects of these two policy options on security of supply, system costs, and incentives for investment, Wärtsilä has commissioned Baringa to analyse whether an EOM 2.0 can incentivise investment in the German market over the period 2020 to 2035, and if so, what types of technologies are most incentivised under this market structure compared to an energy market featuring a CM. The full analysis was provided by Wärtsilä as response to BMWi s Greenpaper consultation and can be found on their website iv. Page 8

9 QuantitativeAnalysis Baringa used its in-house model of the North West European electricity markets and Plexos for power systems (a third party market dispatch engine) to model two scenarios for the evolution of the German electricity market across the period : an EOM 2.0 scenario, reflecting a wholesale market where the no-regret measures have taken effect alongside the EOM 2.0 proposals set out by BMWi (including a strategic reserve of 4.5 GW), and wholesale prices are allowed to rise above generators SRMC, and a CM scenario, reflecting a market-wide capacity mechanism, where all generating capacity is able to receive a capacity payment based upon the missing money 1 that an Open Cycle Gas Turbine (OCGT) 2 requires to enter the market, but where the energy market is restricted to SRMC bidding only (i.e. no mark-up rules). The scenarios targeted different generation capacity margins, which take effect after the exit of nuclear capacity in The EOM 2.0 scenario targets a 0% de-rated capacity margin while the CM scenario targets a 5% margin (representing risk aversion in the final design of the CM). Margins were calculated net of the derated contributions of renewables and interconnection, therefore the actual de-rated capacity margin under both scenarios will be closer to the range 5% to 10% on average respectively. In both scenarios, targeting a margin in this way involves the exit of capacity from the currently oversupplied market until 2023 (with only natural end of operating life exits continuing after this point). There is no new capacity entry until after 2023 in either scenario. Notably, Baringa assumed that the EOM 2.0 scenario would also feature a strategic reserve for the transition to the new energy market arrangements, allowing for 4.5 GW of capacity to be retained by Transmission System Operators (TSOs) for emergency purposes (in line with the Greenpaper proposals from BMWi). This strategic reserve is assumed to dispatch as a last resort (e.g. at the Value of Lost Load (VoLL)), and therefore does not affect Baringa s modelled market dispatch results. Baringa assumed that TSOs procure strategic reserve from the lowest-fixed cost plant that would otherwise be retired based upon its profitability. The strategic reserve is made transitional by allowing procured plant to close without being replaced, meaning that the reserve has largely disappeared by itself by approximately Technology decisions for capacity additions are made on the basis of the most profitable generating technology, calculated based on Baringa s profitability analysis. In both the case of the EOM 2.0 and the 1 Missing money refers to the level of revenues missing from the market that are required for a generator to recover its fixed operations and maintenance costs, and any capital costs. 2 Assumed to be a Best New Entrant - a capacity provider that is able to deliver generating capacity at the lowest capital cost. Page 9

10 CM, this was OCGT and gas engines, which were therefore added equally to the capacity mix to meet the targeted margin. Revenuesandprofitability Baringa calibrated the EOM 2.0 scenario so that wholesale energy market prices are able to spike to levels where low-capex best-new entrant peaking generators (i.e. OCGTs and gas engines) are able to recover their fixed costs in few periods of operation (known as uplift ). In contrast, Baringa assumed that the no mark-up precedent in the market today continues to persist in the CM scenario, which restricts generators from bidding at prices that are higher than their SRMC. In both scenarios, the additional value of operating flexibly is accounted for by using a historicallycalibrated multiplier on revenues to quantify the additional upside that plant can earn. The value of flexibility is earned either from operating flexibly in the intraday market, or through offering ancillary services to the TSOs 3. The ability of different generation technologies to earn revenues by offering flexibility is also reflected through constraints on flexible operation (such as minimum running times). Profitability is used as a metric in the analysis to proxy whether there is a sound economic rationale for making investment decisions in new generation projects under the different market structures. The profitability of generators is calculated using the following equation: Net profit = total revenues total costs Where total revenues constitutes: modelled wholesale market revenues + quantified flexibility revenues + capacity payments (if applicable), and Where total costs constitutes: short run marginal costs of production (including variable operations and maintenance costs) + fixed operations and maintenance costs + annuitised capital costs (where applicable). Using this methodology, the most profitable generation technologies are then used to replace retiring capacity across the modelling horizon to maintain the target capacity margin under each scenario. Totalsystemcosts Finally, Baringa calculated the total system costs for both scenarios using the energy market volume and price modelling results, the cost of procuring the strategic reserve (for the EOM 2.0 scenario) and the cost of market-wide capacity payments (for the CM scenario). 4 3 Baringa modelled the intraday market with a simplified dispatch model using historical price data of Germany s day-ahead auction and intraday market. The results from this tool were used as a multiplier on different technologies market revenues, after being corrected for assumed Ancillary Service participation. Baringa modelled Ancillary Services using Plexos to allocate MRL and SRL volumes, and used regression analysis of historical reserve capacity costs with wholesale electricity market prices to calculate the value of the contracts to capacity holders. Intraday value and ancillary services value are treated as mutually exclusive to avoid double-counting of flexibility value. 4 Our estimate of total system costs does not include the cost of ancillary services. Page 10

11 3. Modellingresults This section sets out the key results from the analysis, which are summarised as follows: New CCGT plant remains commercially unviable throughout the modelled period in both the EOM 2.0 scenario and the CM scenarios, Post-2023, the EOM 2.0 scenario provides stronger incentives for low capex, flexible generating capacity than less flexible technologies such as CCGTs, Overall costs in the EOM 2.0 scenario are found to be lower than in the CM scenario. We cover each of these in turn below. NewconventionalCCGTplantremainscommerciallyunviable It is widely acknowledged that the German market is over-supplied, with de-rated capacity margins in excess of % following the effects of recessionary demand. Further, the economics of gas plant in the German market has been negatively impacted by high renewable penetration, as well as movements in fossil fuel and carbon prices in recent years. Baringa s analysis suggests that new CCGTs will remain commercially unviable throughout the modelling period This result holds even under our EOM 2.0 scenario, which enables market participants to reflect scarcity in their wholesale price offers to enable (at least part) recovery of fixed costs and annuitised capital costs. EOM 2.0 scenario The capacity entry and exit profile in EOM 2.0 is shown in Figure below, alongside the profitability of a new CCGT assumed to commission in Page 11

12 Figure 4: New CCGT profitability and capacity exit and entry in EOM 2.0 scenario In the EOM 2.0 scenario, the market is assumed to naturally gravitate towards a targeted de-rated capacity margin of 0% in the lead up to the last of the existing nuclear plants leaving the German market in By the end of 2023, reduction of installed capacity through closures reaches 12 GW in total (excluding nuclear closures), and consists of predominantly coal and some lignite generation (8 GW and 2 GW respectively) and 1 GW of CCGT. Of this total, 4.5 GW of retired coal generation is assumed to be held as a strategic reserve outside of the wholesale market. By 2023, after the last nuclear plant retires, around 400 MW of new investment is needed to sustain the target de-rated capacity margin, with cumulative additions reaching 2.7 GW by The driving factor behind the losses made by new CCGTs in the EOM 2.0 scenario is low-load factors (just 33% on average) meaning that the investments are unable to recover their fixed and capital costs. The low load factors are caused by the significant renewables penetration, as well as competition with coal and lignite generation for baseload, owing to Baringa s coal and carbon price assumptions (which imply a positive clean dark spread 5 throughout the modelling period). This finding reinforces the concerns that market participants (and particularly the owners of new-build CCGTs) are voicing around the commercial viability of recent investments, even if the EOM 2.0 is reformed. While the focus of Baringa s analysis is on the potential for new investment, the analysis also shows that existing CCGT are profitable under EOM 2.0, but only if these investments have been able to recover their capital costs in the time leading up to the implementation of the new arrangements. In each case, 5 The profit realised by a power generator after paying for the cost of coal fuel and carbon allowances Page 12

13 this depends on the age of the plant and whether financing arrangements mean that losses are accrued to the plant itself. CM scenario The same analysis for the CM scenario produces an interesting result. Here, the value of the capacity payment available to conventional capacity is assumed to be set by the level of missing money in the market for a new OCGT. Therefore, the capacity payment is calculated as the level required to deliver a zero net profitability for OCGTs, and ranges between 36 and 48 /kw per annum. Baringa considers this approach to be conservative, as it produces a stable capacity payment that is not necessarily reflective of the dynamic supply-demand balance, nor the missing money required to support other existing loss-making plant. Therefore for comparison, Baringa also calculated a capacity payment based upon the level of missing money in the market for a new CCGT. The analysis shows that: New CCGTs continue to be loss-making if paid an OCGT missing money-based capacity payment, and New CCGTs hit breakeven point if paid a CCGT-based capacity payment (which Baringa estimates would need to exceed 90/kW per annum). These results are shown in Figure below. The key reason for the losses observed when Baringa applies the OCGT-based capacity payment is that the no mark-up rule applied in the wholesale market limits recovery of fixed costs that a new CCGT would otherwise earn through uplift in prices. Figure 5: New CCGT profitability and capacity exit and entry in the CM scenario Page 13

14 Note that in the CM scenario, due to the higher targeted de-rated capacity margin, only 7.3GW of capacity is retired prior to 2023 (compared to around 12GW in the EOM 2.0 scenario). This means that there is greater competition for dispatch in the electricity market, and therefore the level of inframarginal rents that are available to any CCGT in the energy market are diminished. Baringa notes that the average load factor for CCGT in the CM scenario is only 10% across the modelling horizon in the CM scenario (compared to around 33% in the EOM 2.0 scenario). Similar to the analysis of the EOM 2.0 scenario, existing CCGT with no outstanding capital cost recovery requirements are found to be profitable in the CM scenario under both CM payment calculations. However, this is only true where these investments have been able to recover their capital costs in the time leading up to the implementation of the new arrangements. In each case, this depends on the age of the plant and whether financing arrangements mean that losses are accrued to the plant itself. The EOM scenario provides stronger incentives for low capex, flexible generation technologies The profitability analysis also shows that low-capex, flexible forms of capacity such as OCGT and Gas engines are exposed to stronger incentives to invest under the EOM 2.0 scenario. This is driven by their ability to collect uplift in the wholesale market, and superior operational capabilities allowing them to collect additional revenues from operating flexibly in the intraday and ancillary services markets. For example, the profitability for the new build CCGT in the EOM 2.0 scenario is shown in Figure below. This chart demonstrates the difference that uplift can make to CCGT revenues. While the CCGT is still loss-making in the EOM 2.0 scenario, losses are higher still where no uplift is applied. Figure 6: Profitability of a new-build CCGT Page 14

15 The profitability of a new-build OCGT is illustrated in Figure 7 below. As CM payments are assumed to be based on the value of missing money for an OCGT, the profitability under the CM is assumed to be 0 /kw across the modelling timeframe. The EOM without uplift does not provide new build OCGT with the necessary revenues to recover its fixed costs. However, the EOM 2.0 scenario with uplift enables the technology to just achieve profitability after discounting at 6%, Baringa estimate an NPV of profits over the period of just over 3 /kw in the EOM 2.0 scenario. Figure 7: Profitability of a new-build OCGT The profitability of gas engines in the EOM 2.0 scenario is observed to be higher than OCGT, earning 146 /kw in net present value terms across the modelling period (see Figure below). Gas engines deliver higher profitability than an OCGT because they are assumed to have a lower SRMC (allowing them to recover higher infra-marginal rents), are more flexible in operation with a lower minimum stable operating limit, and have a shorter start up time. However, gas engines are observed to be loss-making under the CM, primarily because they have higher annuitised capital costs than OCGTs (meaning that the capacity payment based on OCGT missing money does not recover these fully). While gas engines are still able to earn some infra-marginal rent, even in the energy market with no mark-up rule, these earnings are not sufficient to generate a profit. Page 15

16 Figure 8: Profitability of a new build Gas Engine These results highlight that the market design choice can have a significant impact on technology choice for investors. Baringa analysis suggests that the EOM 2.0 is more likely to deliver more flexible and lower capex-intensive capacity, which is more in line with the future needs on the German system. Indeed, the need for the market arrangements to encourage investment in flexibility to manage intermittency is a key focus in the Greenpaper. EOM2.0isfoundtodeliveratloweroverallcostperannumthantheCM Baringa s modelling results also indicate that the EOM 2.0 can deliver at a lower overall cost than the CM, even after accounting for the additional cost of a strategic reserve. The strategic reserve is assumed to be procured from the 12 GW of plant closures required by 2023 in the EOM 2.0 scenario. The choice of plant is determined based on those that require the lowest payments in terms of missing money to cover fixed costs and stay open (i.e. the least profitable plants are still assumed to decommission). On this assumption, the plants that are procured are mostly coal plants that were commissioned in the 1980s, which have fixed costs of approximately 250m per annum in total. A large portion of this capacity reaches the end of its life expected between 2025 and 2029, and is then decommissioned, which brings down the cost of the strategic reserve. This is shown in Figure below. Page 16

17 Figure 9: Cost of strategic reserve in the EOM 2.0 To calculate total costs in the EOM 2.0 scenario, wholesale market prices incorporating uplift, as well as the costs of the strategic reserve were taken into account. For the CM scenario, the capacity payment based upon the level of missing money calculated for an OCGT was applied across all plant deemed to be eligible (i.e. conventional capacity). Baringa also used the capacity payment based upon the missing money calculated for a CCGT to demonstrate the impact that setting a capacity payment at this level would have on overall costs. The results from these total cost calculations are presented in Figure 1 below. Figure 1: Total cost of EOM 2.0 scenario and CM scenario Page 17

18 As Figure 10 illustrates, the costs under the EOM 2.0 scenario are broadly close to those of the CM scenario in most years. On average Baringa observed that the EOM 2.0 is approximately 150m per annum lower cost than a CM based on OCGT missing money. Over the modelled period , this delivers a saving of 2.5 bn net present value 6. In comparison, using a CM based on the missing money of a CCGT increases costs significantly, by around 3 bn a year on average compared to EOM 2.0. Over the modelled period, this costs German consumers an extra 34 bn in net present value. 6 Discounted at 3.5% Page 18

19 4. ConclusionsandRecommendations Wärtsilä considers that the analysis set out above can provide a number of key insights into the debate on whether the German electricity market should follow an EOM 2.0 or CM design. These include: It is likely that any new conventional baseload capacity such as Combined Cycle Gas Turbines (CCGT) will continue to be loss-making in both market designs, because they are unlikely to generate at the hours required to earn sufficient revenues. This is caused both by the oversupply situation in Germany, and also the long-term reduction in running hours caused by the significant penetration of renewables in the German market. Even if CCGTs are paid capacity payments in the range of /kw per annum, (the missing money of a best new entrant in capex terms) Baringa still does not find them to be profitable in both market designs. The EOM 2.0 creates stronger incentives for flexibility than the CM, as it targets financial incentives on flexible operation itself, instead of remunerating all types of capacity with the same level of payment. Although the analysis is conservatively based on historic intra-day and ancillary service prices, Baringa observes an increase in the profitability of flexible resources relative to inflexible resources in the EOM 2.0 scenario. Lastly, the results showed that between 2020 and 2035, the EOM 2.0 serves the system at a cost that is approximately 2.5 bn lower in net present value terms than the estimated costs under the CM scenario (with missing money based on the cost for a best new entrant). If Baringa instead bases the capacity payment on the missing money of a CCGT, the estimated costs under the CM scenario are 34 bn higher (in NPV terms) than under the EOM 2.0 scenario. Our recommendations for the market design policy debate in Europe in general and Germany specifically are the following: 1. Based on the results of the Baringa analysis, governments should consider the advantages that EOM 2.0 will have in expediting the transition of an electricity market to one that is predominantly supplied by intermittent renewables balanced with a diverse range of controllable flexible resources. 2. Given these advantages, and the compelling results of the Baringa analysis, we believe that a market design based on the EOM2.0 provides a better alternative to provide security of supply to a power system transiting to one that is dominated by RES. This is because: a. An EOM 2.0 market design provides efficient entry and exit signals while creating stronger incentives for the right type of capacity for the market. Page 19

20 b. It reduces the need for political involvement and the administrative burden associated with designing, implementing and running a CM (with recent experience in the UK providing a case in point). c. The overall costs of the EOM2.0 are lower compared to a CM As Germany is one of the front runners of EU member states in transforming its power system, the EOM2.0 market design should be considered as a blue print for other EU member states. When other member states follow the same market design, a truly integrated European market based energy system can emerge that integrates Renewable Energy Sources in a cost efficient and secure manner. Page 20

21 References i The EU Climate and Energy Package, European Commission, ii Conclusions European Council, 23 and 24 October, iii October 2014, Federal Ministry for Economic Affairs and Energy (BMWi), iv Page 21