[en] Battery energy storage is becoming an important asset in modern power systems. Considering the market prices and battery storage characteristics, reserve provision is a tempting play fields for such assets. This paper aims at filling the gap by developing a mathematically rigorous model and applying it to the existing and future electricity market design in Europe. The paper presents a bilevel model for optimal battery storage participation in day-ahead energy market as a price taker, and reserve capacity and activation market as a price maker. It uses an accurate battery charging model to reliably represent the behavior of real-life lithium-ion battery storage. The proposed bilevel model is converted into a mixed-integer linear program by using the Karush-Kuhn-Tucker optimality conditions. The case study uses real-life data on reserve capacity and activation costs and quantities in German markets. The reserves activation quantities and activation prices are modeled by a set of credible scenarios in the lower-level problem. Finally, a sensitivity analysis is conducted to comprehend to what extent do battery storage bidding prices affect its overall profit.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > FINATRAX - Digital Financial Services and Cross-organizational Digital Transformations
Disciplines :
Management information systems Electrical & electronics engineering Computer science
Author, co-author :
Pandžić, Kristina; Croatian TSO (Hrvatski Operator Prijenosnog Sustava d.o.o.-HOPS), Zagreb, Croatia
PAVIĆ, Ivan ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > FINATRAX
Andročec, Ivan; Hrvatska Elektroprivreda d.d., Zagreb, Croatia
Pandžić, Hrvoje ; Department of Energy and Power Systems, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia
External co-authors :
yes
Language :
English
Title :
Optimal battery storage participation in european energy and reserves markets
Original title :
[en] Optimal battery storage participation in european energy and reserves markets
ERDF - European Regional Development Fund EU Horizon
Funding number :
863876; KK.01.1.1.04.0034
Funding text :
Funding: This work was funded in part by the European Union through the European Regional Development Fund Operational Programme Competitiveness and Cohesion 2014–2020 of the Republic of Croatia under project KK.01.1.1.04.0034 “Connected Stationary Battery Energy Storage”. It also received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 863876 in the context of the FLEXGRID project.
Official Journal of the European Union. Commission Regulation (EU) 2017/2195 of 23 November 2017 Establishing a Guideline on Electricity Balancing; European Commission, Directorate-General for Energy: Brussels, Belgium, 2017.
Koch, C.; Hirth, L. Short-term electricity trading for system balancing: An empirical analysis of the role of intraday trading in balancing Germany’s electricity system. Renew. Sustain. Energy Rev. 2019, 113, 109275.
Lackner, C.; Nguven, T.; Byrne, R.H.; Wiegandt, F. Energy Storage Participation in the German Secondary Regulation Market. In Proceedings of the 2018 IEEE PES Transmission and Distribution Conference and Exposition (T&D), Denver, CO, USA, 16-19 April 2018; pp. 1-9.
PICASSO Project TSOs. Consultation on the Design of the Platform for Automatic Frequency Restoration Reserve (AFRR) of PICASSO Region, The Platform for the International Coordination of Automated Frequency Restoration and Stable System Operation (PICASSO). 2017.
Figgener, J.; Stenzel, P.; Kairies, K.P.; Linßen, J.; Haberschusz, D.; Wessels, O.; Angenendt, G.; Robinius, M.; Stolten, D.; Sauer, D.U. The development of stationary battery storage systems in Germany-A market review. J. Energy Storage 2020, 29, 101-153.
Simon, B. The German Energy Storage Market 2016-2021: The Next Energy Transition. In GTM Research Report; GTM Research: Boston, MA, USA, 2016.
RTE-Le RéSeau de Transport De L’électricité; Electricity Report 2018; Réseau de Transport d’Électricité: Paris, France, 2019.
Regelleistung.net. Internetplattform zur Vergabe von Regelleistung. 2019. Available online: Https://www.regelleistung.net/ext/static/prl (accessed on 5 March 2019).
Butler, P.C.; Iannucci, J.; Eyer, J. Innovative business cases for energy storage in a restructured electricity marketplace. In Sandia National Laboratories Report; Sandia National Laboratories: Albuquerqe, NM, USA, 2003.
Eyer, J.M.; Iannucci, J.; Corey, G.P. Energy storage benefits and market analysis handbook. In Sandia National Laboratories Report; Sandia National Laboratories: Albuquerqe, NM, USA, 2004.
Sioshansi, R.; Denholm, P.; Jenkin, T.; Weiss, J. Estimating the value of electricity storage in PJM: Arbitrage and some welfare effects. Energy Econ. 2009, 31, 269-277.
Akhavan-Hejazi, H.; Mohsenian-Rad, H. Optimal Operation of Independent Storage Systems in Energy and Reserve Markets With High Wind Penetration. IEEE Trans. Smart Grid 2014, 5, 1088-1097.
Kazemi, M.; Zareipour, H.; Amjady, N.; Rosehart, W.D.; Ehsan, M. Operation Scheduling of Battery Storage Systems in Joint Energy and Ancillary Services Markets. IEEE Trans. Sustain. Energy 2017, 8, 1726-1735.
Fleer, J.; Zurmuhlen, S.; Meyer, J.; Badeda, J.; Stenzel, P.; Hake, J.-F.; Sauer, D. Price development and bidding strategies for battery energy storage systems on the primary control reserve market. Energy Procedia 2017, 135, 143-157.
Fleer, J. Techno-economic evaluation of battery energy storage systems on the primary control reserve market under consideration of price trends and bidding strategies. J. Energy Storage 2018, 17, 345-356.
Gomes, I.L.R.; Pousinho, H.M.I.; Melício, R.; Mendes, V.M.F. Stochastic coordination of joint wind and photovoltaic systems with energy storage in day-ahead market. Energy 2017, 124, 310-320.
Miletić, M.; Pandžić, H.; Yang, D. Operating and Investment Models for Energy Storage Systems. Energies 2020, 13, 4600.
Alberta Electric System Operator AESO. Comparison Between Sequential Selection and Co-Optimization Between Energy and Ancillary Service Markets; Technical Report; AESO: Calgary, AB, Canada, 2018.
Pavić, I.; Dvorkin, Y.; Pandžić, H. Energy and Reserve Co-optimization-Reserve Availability, Lost Opportunity and Uplift Compensation Cost. IET Gener. Trans. Dis. 2019, 13, 229-237.
Ehsani, A. A Proposed Model for Co-Optimization of Energy And Reserve In Competitive Electricity Market. Appl. Math. Model. 2009, 33, 92-109.
Chen, Y.; Gribik, P.; Gardner, J. Incorporating Post Zonal Reserve Deployment Transmission Constraints Into Energy and Ancillary Service Co-Optimization. IEEE Trans. Power Syst. 2014, 29, 537-549.
Ela, E.; Milligan, M.; Kirby, B. Operating Reserves and Variable Generation. In National Renewable Energy Laboratory Report; National Renewable Energy Laboratory: Golden, CO, USA, 2011.
Chen, Y.; Wan, J.; Ganugula, V.; Merring, R.; Wu, J. Evaluating Available Room for Clearing Energy and Reserve Products under Midwest ISO Co-Optimization Based Real Time Market. In Proceedings of the 2010 IEEE PES General Meeting, Providence, RI, USA, 25-29 July 2010.
Hassan, M.W.; Rasheed, M.B.; Javaid, N.; Nazar, W.; Akmal, M. Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty. Energies 2018, 11, 2833.
Zeh, A.; Müller, M.; Naumann, M.; Hesse, H.C.; Jossen, A.; Witzmann, R. Fundamentals of Using Battery Energy Storage Systems to Provide Primary Control Reserves in Germany. Batteries 2016, 2, 29.
Goebel, C.; Jacobsen, H. Aggregator-Controlled EV Charging in Pay-as-Bid Reserve Markets with Strict Delivery Constraints. IEEE Trans. Power Syst. 2016, 31, 4447-4461.
Merten, M.; Rücker, F.; Schoeneberger, I.; Sauer, D.U. Automatic frequency restoration reserve market prediction: Methodology and comparison of various approaches. Appl. Energy 2020, 268, 114978.
Merten, M.; Olk, C.; Schoeneberger, I.; Sauer, D.U. Bidding strategy for battery storage systems in the secondary control reserve market. Appl. Energy 2020, 268, 114951.
Pandžić, H.; Bobanac, V. An Accurate Charging Model of Battery Energy Storage. IEEE Trans. Power Syst. 2019, 4, 1416-1426.
Conejo, A.J.; Castillo, E.; Minguez, R.; Garcia-Bertrand, R. Decomposition Techniques in Mathematical Programming; Springer: Berlin/Heidelberg, Germany, 2006.
Pandžić, H.; Dvorkin, Y.; Carrion, M. Investments in merchant energy storage: Trading-off between energy and reserve markets. Appl. Energy 2018, 230, 277-286.