electricity system ? Joachim Bertsch, Christian Growitsch, Stefan - - PowerPoint PPT Presentation

Do we need an additional flexibility market in the electricity system?

Joachim Bertsch, Christian Growitsch, Stefan Lorenczik, Stephan Nagl

Institute of Energy Economics, University of Cologne

Background

• EU goal: 80 % of renewables in 2050
• Majority: Wind and photovoltaics

Stochastic electricity generation Two major impacts:

• Capacity mix has to be flexible enough
• Sufficient backup capacities needed

Background

Discussion of implications for backup capacities and capacity mechanisms (e.g. Cramton and Stoft 2008, Joskow 2008 etc.) Lamadrid et al. (2011) propose a “new market for ramping services” CAISO discusses ramping product (Xu and Threteway 2012) Is there a need for an additional flexibility market?

Methodological approach (I)

Integrated system modelling

• Contribution of all parts of the electricity system, leading to

interdependencies between different flexibility sources

• Inter-temporal dependencies (dispatch and investments)

Previous research

• Changes in optimal capacity mix from base to peak-load

capacities (Nicolosi 2010, De Jonghe et al. 2011 etc.)

• Utilization rate rather than operational constraints determine

investments into peak-load capacities (Nicolosi 2012)

Methodological approach (II)

Linear dispatch and investment model DIMENSION

• Object function minimizing total system costs
• Cost-efficient capacity and generation mix

Additions to previous literature

• Considering large deployment of renewables (EU goals)
• Renewables-dependent balancing power
• Demand side reactions
• CCS power plants with detachable CCS unit

Flexibility within the model

Ramping / Start-up constraints (depending on characteristics of technology) Positive and negative balancing power provision (depending on expected wind and photovoltaics feed-in)

positive negative

• Ramping of thermal power plants in part load
• peration
• Thermal power plants in operation (ramping

down)

• Start-up of technologies (OCGT)
• Storage technologies
• Utilization of stored energy or stop of storage
• Curtailment of wind power
• Shifting through demand side management

(reduction)

• Shifting through demand side management

(increase)

• Utilization of previously curtailed wind power
• Switching off CCS unit to increase power output

Results: Changes in residual load

• 40
• 20

20 40 60 80 100 4380 8760 GW h DE 2050 DE 2020

• 40
• 20

20 40 60 80 100

• 20000
• 10000

10000 20000 GW MW

Residual load duration Hourly changes of residual load

Results: volatility of residual load

Positive Negative 2006 2011 2020 2050 2006 2011 2020 2050 Mean 2230 2242 3083 4105

• 1753 -1853 -2604 -3656

Standard deviation 2092 2148 2572 3373 1332 1420 1922 2727 Max 11052 11396 14106 22775 -6273 -8016 -12069 -18984

Results: European capacity and generation mix

500 1.000 1.500 2.000 2.500 2000 2008 2020 2030 2040 2050 GW 500 1.000 1.500 2.000 2.500 3.000 3.500 4.000 4.500 5.000 2000 2008 2020 2030 2040 2050 TWh

10.000 20.000 30.000 40.000 50.000 Mon Tue Wed Thu Fri Sat Sun MW Storage Thermal plants DSM Wind availability CCS Flexibility requirement 5.000 10.000 15.000 20.000 25.000 30.000 Mon Tue Wed Thu Fri Sat Sun MW OCGT Storage Thermal plants DSM Wind availability CCS Flexibility requirement

Results: Availability of balancing power

Positive balancing power availability in June 2020, Germany Negative balancing power availability in June 2020, Germany

Conclusion

• Main trigger for investments are backup capacities
• Cost-efficient backup capacities are flexible (e.g. gas turbines)
• Under system adequacy, flexibility never poses a challenge in a

cost-minimal capacity mix Any Market design providing incentives in cost-efficient generation technologies provides flexibility as an inevitable complement.

Backup

Literature

• Capros, P., Mantzos, L., Tasios., N., DeVita, A., Kouvaritakis, N., 2010. Energy Trends to 2030

— Update 2009. Tech. rep., Institute of Communication and Computer Systems of the National Technical University of Athens.

• Cramton, P., Stoft, S., 2008. Forward reliability markets: Less risk, less market power, more
• efficiency. Utilities Policy 16, 194–201.
• Davison, J., 2009. The need for flexibility in power plants with ccs.
• De Jonghe, C., Delarue, E., Belmans, R., D’haeseleer, W., 2011. Determining optimal

electricity technology mix with high level of wind power penetration. Applied Energy 88, 2231–2238.

• Denholm, P., Hand, M., 2011. Grid flexibility and storage required to achieve very high

penetration of variable renewable electricity. Energy Policy 39, 1817–1830.

• ENTSO-E, 2011. Yearly electricity consumption data for Europe. URL

https://www.entsoe.eu/index.php?id=92

• EWI, 2011. Roadmap 2050 - a closer look. Cost-efficient RES-E penetration and the role of

grid extensions. Tech. rep., M. Fürsch, S. Hagspiel, C. Jägemann, S. Nagl, D. Lindenberger (Institute of Energy Economics at the University of Cologne) L. Glotzbach, E. Tröster and T. Ackermann (energynautics).

Literature

• Finkenrath, M., 2011. Cost and performance of carbon dioxide capture from power
• generation. IEA Working Paper.
• Fürsch, M., Hagspiel, S., Jägemann, C., Nagl, S., Lindenberger, D., Tröster, E., 2012. The

role of grid extensions in a cost-efficient transformation of the European electricity system until 2050 (Working Paper No. 12/04) Institute of Energy Economics at the University of Cologne.

• Giebel, G., Brownsword, R., Kariniotakis, G., Denhard, M., Draxl, C., 2011. The state-of-the-art

in short-term prediction of wind power. Tech. rep., ANEMOS.plus, project funded by the European Commission under the 6th Framework Program, Priority 6.1: Sustainable Energy Systems.

• Holttinen, H., 2005. Impact of hourly wind power variations on the system operation in the

nordic countries. Wind energy 8 (2), 197–218.

• Holttinen, H., Horvinen, H., 2005. Power system requirement for wind power. T. John Wiley &

Sons Ltd, Ch. 8, pp. 144–167.

• IEA, 2011. World energy outlook 2011. Tech. rep., International Energy Agency.
• J¨ägemann, C., Fürsch, M., Hagspiel, S., Nagl, S., 2012. Decarbonizing Europe’s power sector

by 2050 - Analyzing the implications of alternative decarbonization pathways (Working Paper

• No. 12/13) Institute of Energy Economics at the University of Cologne.

Literature

• Joskow, P., 2008. Capacity payments in imperfect electricity markets: Need and design.

Utilities Policy 16, 159–170.

• Lamadrid, A., Mount, T., Thomas, R., 2011. Integration of Stochastic Power Generation,

Geographical Averaging and Load Response. WP 2011-09, Charles H. Dyson School.

• Luickx, P. J., Delarue, E., D’haeseleer, W., 2008. Considerations on the backup of wind power:

Operational backup. Applied Energy 85, 787–799.

• Martens, P., Delarue, E., D’haeseleer, W., 2011. A Mixed Integer Linear Programming Model

for A Pulverized Coal Plant With Post-Combustion Carbon Capture. WP EN2011-01, TME Working Paper - Energy and Environment, KU Leuven Energy Institute.

• Möst, D., Fichtner, W., 2010. Renewable energy sources in european energy supply and

interactions with emission trading. Energy Policy 38, 2898–2910.

• Nagl, S., Fürsch, M., Jägemann, C., Bettzüge, M., 2011. The economic value of storage in

renewable power systems - the case of thermal energy storage in concentrating solar plants (Working Paper No. 11/08) Institute of Energy Economics at the University of Cologne.

• Nicolosi, M., 2010. Wind power integration and power system flexibility - an empirical

analysis of extreme events in germany under the new negative price regime. Energy Policy 38, 7257–7268.

Literature

• Nicolosi, M., 2012. The economics of electricity market integration - an empirical and

model-based analysis of regulatory frameworks and their impacts on the power market,

• Dissertation. Ph.D. thesis, Universität zu Köln.
• Prognos/EWI/GWS, 2010. Energieszenarien für ein Energiekonzept der Bundesregierung.
• Tech. rep., M. Schlesinger, P. Hofer, A. Kemmler, A. Kirchner and S. Strassburg (all Prognos

AG); D. Lindenberger, M. Fürsch, S. Nagl, M. Paulus, J. Richter and J. Trüby (all EWI); C. Lutz, O. Khorushun, U. Lehr and I. Thobe (GWS mbH).

• Richter, J., 2011. DIMENSION - A Dispatch and Investment Model for European Electricity

Markets (Working Paper No. 11/03) Institute of Energy Economics at the University of Cologne.

• Ummels, B., Gibescu, M., Pelgrum, E., Kling, W., 2006. System Integration of Large-Scale Wind

Power in the Netherlands. Power Engineering Society General Meeting, 2006. IEEE.

• Xu, L., Threteway, D., 2012. Flexible ramping products - second revised draft final
• proposal. Tech. rep., California ISO (CAISO).

Methodological approach: Linear Investment and Dispatch model DIMENSION

17

• Coventional,

storage and nuclear plants

• RES-E plants
• transmission

expansion between countries European Investment and Dispatch Model for Electricity Markets Including: Demand Fuel and CO2-Prices Existing generating and transmission capacities Technical and Economic parameters of generating and

transmission capacities Potentials of RES-E plants

INPUT

Political restrictions, i.e.:

• RES-E quota
• Nuclear Policy

Feed-in profiles of RES-E plants per region Transmission loss Installed capacities; commissioning and decommissioning of generating and transmission capacities Annual generation structure Plant dispatch by load level Fixed, variable and average generation costs CO2-emissions Fuel consumption Utilization rates RES-E curtailment Import and export streams(trade and physical flows)

OUTPUT

Source: EWI.