ECONOMIC POTENTIAL OF DEMAND SIDE MANAGEMENT IN AN INDUSTRIALIZED COUNTRY THE CASE OF GERMANY

Transcription

1 ECONOMIC POTENTIAL OF DEMAND SIDE MANAGEMENT IN AN INDUSTRIALIZED COUNTRY THE CASE OF GERMANY 10th IAEE European Conference Vienna, September 10th 2009 Dipl.-Wi.-Ing. Moritz Paulus Dipl.-Wi.-Ing. Frieder Borggrefe

2 Agenda 1. Motivation 2. Modelling DSM with DIME 3. Preliminary results

3 RES-E feed-in will constitute approximately 25 30% of total German electricity generation in 2020 RES feed-in, especially wind energy feed-in is stochastic and leads to a higher requirement for flexibility of deterministic generation capacities Framework Projected development of RES-E feed-in in Germany Achieve EU climate targets through more RES-E feed-in Electricity grid faces higher requirements Higher stochastic energy feed-in 120TWh 80TWh 40TWh 12% 15% 23% 30% 40% 30% 20% 10% TWh % Challenges Additional flexibility is necessary to cope with the increasing stochastic RES-E feed-in Potential electricity grid bottlenecks

4 Demand Side Management means capturing the flexibility potential of the consumer side through changing price signals Households Scope Energy intensive industries Spot market & market for ancillary services (tertiary reserve) Energy management systems Data exchange technology Smart Metering Central control unit technology Technology Demand Side Management Peak Shaving Valley Filling Peak Shaving : Load shedding during peak periods Valley Filling : Load catch-up during offpeak periods Load shifting: DSM potential equivalent to a power storages Load reduction: DSM potential equivalent to a power plants Load shifting / Load reduction

5 Demand Side Management should decrease variable system costs of electricity generation Load catch-up / Valley Filling Load shedding / Peak Shaving Supply curve Electricity market p old p new p old p new x 1 x 1 = Load shifting x 2 = Load reduction x 1 x 2 1 How are total electricity generation costs affected by introducing Demand Side Management in Germany? 2 To what extent are price volatilities and hourly spot prices affected by the introduction of DSM?

6 Processes were selected on the basis of power consumption and power intensity and then classified as load shifting or load reduction potentials Households Energy intensive industry Selection Night storage heaters Electrical warm water supply Fridges & Freezers Dish washers, washing machines & tumblers Heating pumps Chloralkali process Wood pulp production Aluminium electrolysis Electric arc furnace Cement mills Percentage of total electricity demand of German households in % Percentage of total electricity demand of German industry in % Classification Not storable Utilisation Storage Technical parameters Storable Load reduction Load shifting

7 Model structure of DIME Dispatch and Investment Model for Electricity Markets in Europe Input Output Total power demand Exogenous feed-in Residual load Demand DIME Investment Commissioning and decommissioning of power plant technologies Installed capacities Fixed and variable generation costs Existing generation capacities Technical and economic parameters of new technologies Fuel prices Net transfer capacities Grid losses Supply Linear optimisation for competitive markets Dispatch Annual power generation structure Power plant dispatch Physical exchange Marginal costs of production Fuel consumption CO 2 emissions Quelle: EWI

8 Most investments into DSM potentials take place in the cement industry and in the production of wood pulp while almost all DSM potentials in households remain unused DSM potentials - industry DSM potentials - households 3.000MW 60MW 2.500MW MW 2.000MW 40MW MW 30MW 1.000MW MW MW MW 17 MW MW Chloralkali process Wood pulp production Aluminium electrolysis Electric arc furnace Cement mills Night storage heating & warm water supply Heating pumps

9 First model runs show a reduction of total system costs in the electricity market which, amongst others, are generated by a contribution of DSM of ~60% to positive tertiary capacity Tertiary reserve [%] Market parameters [ ] Positive reserve capacity offered** 15,5% 44,2% Load shifting* 0,5 Positive reserve energy** 0,1% Load reduction* 0,2 Negative reserve capacity offered** 1,8% Cumulated reduction of total system costs *** 3,6 Negative reserve energy** 5,6% Reduction of base price volatility**** 2, already used 2020 used Change of base price for electricity 0,6 *relative to projected total German electricity load in 2020 **relative to total positive/negative projected reserve energy / reserve capacity of the tertiary reserve market in Germany in 2020 ***Reduction of cumulated total system costs in the German electricity market until 2020 ****Measured as difference of variances of hourly power prices in 2020 in Germany

10 DSM will save approximately 0.5 bn of total system costs in Germany until Breakdown of the discounted cost savings generated by DSM until Mio.! [2008] Total Reserve energy Grid Production Ramp-up Part load IM-EX FO&M Invest Costs: -0,3% -4,1% +0,1% 0,0% 0% 0% -0,7% -0,4% -2,3%

11 Preliminary results show moderate positive effects regarding actual load shifting as well as cost savings 1 Cost savings of 0.5 bn are mostly generated through reduced investment into capacity. Investment cost savings correspond to approx. 800 MW of gas turbine capacity. 2 Effects of DSM on hourly spot price volatility and price levels remain negligible as the merit order curve is not strictly convex and investment costs influence the load shifting/shedding strategies of DSM processes 3 Especially household appliances are extremely sensitive with regard to assumptions made on learning curve effects for investment costs. 4 Load shifting strategies on the tertiary reserve market do not respect the uncertainty associated with calls for energy.

12 Thank you for your attention

13 References Auer H., Huber C., Faber T., Resch G Economics of Large-scale Intermittent RES-E Integration into the European Grids: Analyses based on the Simulation Software GreenNet. International Journal of Global Energy Issues, Vol. 25, no. 3: Bartels M., Gatzen C., Peek M., Schulz W Planning of the grid integration of wind energy in Germany onshore and offshore up to the year International Journal of Global Energy Issues, Vol. 25, no. 3: Bartels M., Lindenberger D Systemanalyse und Szenariorechnung. Schwerpunkte und Effizienzstrategien in der Energieforschung, final report, AGFW. Benston A. editor Implementing Agreement on Demand-Side Management Technologies and Programmes Annual Report 2007, IEA Demand- Side Management Programme. Brückel O., Neubarth J., Wagner U Regel- und Reserveleistungsbedarf eines Übertragungsnetzbetreibers Energiewirtschaftliche Tagesfragen 56 (1/2): DSTATIS, Produierendes Gewerbe Produktion im Produzierenden Gewerbe. Fachserie 4 Reihe 3.1. Statistisches Bundesamt. GDA, German Aluminium Industry Association on Production Figures for Germany, Geiger B., Hardi M., Brückl O., Roth H., Tzscheutschler P CO2 Vermeidungskosten im Kraftwerksbereich, bei den erneuerbaren Energien sowie bei nachfrageseitigen Energieeffizienzmaßnahmen. Herrsching: Energie & Management Verlag. Klobasa M Dynamische Simulation eines Lastmanagements und Integration von Windenergie in ein Elektrizitätsnetz auf Landesebene unter regelungstechnischen und Kostengesichtspunkten. PhD diss., ETH Zürich. Stadler I Demand Response: Nichtelektrische Speicher für Elektrizitätsversorgungssysteme mit hohem Anteil erneuerbarer Energien. Berlin: dissertation.de. WV Stahl, German Economic Association for Steel on Production Figures for Germany

14 Mostly reserver capacity is offered while actual calls for reserve energy remain rare as the opportunity costs are prohibitive Ø Positive capacity offered [MW] Call probability [%] Ø Negative capacity offered [MW] Call probability [%] Night storage heaters & warm water 0 1, Chloralkali process Wood pulp production Aluminum electrolysis 167 Electric arc furnace 685 Cement mills 204