IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v311y2022ics030626192200188x.html
   My bibliography  Save this article

An efficient and incentive-compatible market design for energy storage participation

Author

Listed:
  • Fang, Xichen
  • Guo, Hongye
  • Zhang, Xian
  • Wang, Xuanyuan
  • Chen, Qixin

Abstract

With the increasing penetration of renewables, energy storage systems (ESS) are becoming growingly important due to its peak-shaving ability. However, the current market mechanism is not well prepared for the participation of the ESSs. Firstly, the current bidding structure requires the ESSs to submit separate parameters for charging and discharging, but this structure is inconsistent with their operating characteristics. Secondly, the current settlement rule settles the ESSs according to time-variant locational marginal prices (LMP), but the diminishing intertemporal price spreads will encourage them to behave strategically. To this end, this paper proposes a novel bidding structure, a corresponding clearing model and a modified settlement rule: The bidding structure for the ESSs includes cost functions with respect to cycling mileages and valuation functions for ending stored energy. Thereafter the independent system operators (ISO) will manage the ESSs’ state of charge (SOC) and clear the market. A settlement rule based on Vickery-Clarke-Groves (VCG) mechanism and Asymmetric Nash Bargaining theory is adopted to incentivize the ESSs to behave honestly. Numerical tests are conducted to illustrate the social welfare efficiency, incentive compatibility and computational tractability of the proposed mechanism.

Suggested Citation

  • Fang, Xichen & Guo, Hongye & Zhang, Xian & Wang, Xuanyuan & Chen, Qixin, 2022. "An efficient and incentive-compatible market design for energy storage participation," Applied Energy, Elsevier, vol. 311(C).
    • Handle: RePEc:eee:appene:v:311:y:2022:i:c:s030626192200188x
    DOI: 10.1016/j.apenergy.2022.118731
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626192200188X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.118731?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Shiyu & Ren, Yanzhe & Zhang, Zhenyu & Xiao, Yao & Bie, Zhaohong & Wang, Xifan, 2021. "Optimal bid-offer strategy for a virtual energy storage merchant: A stochastic bi-level model with all-scenario feasibility," Applied Energy, Elsevier, vol. 299(C).
    2. Vojvodic, Goran & Jarrah, Ahmad I. & Morton, David P., 2016. "Forward thresholds for operation of pumped-storage stations in the real-time energy market," European Journal of Operational Research, Elsevier, vol. 254(1), pages 253-268.
    3. Huang, Qisheng & Xu, Yunjian & Courcoubetis, Costas, 2020. "Stackelberg competition between merchant and regulated storage investment in wholesale electricity markets," Applied Energy, Elsevier, vol. 264(C).
    4. Henni, Sarah & Staudt, Philipp & Weinhardt, Christof, 2021. "A sharing economy for residential communities with PV-coupled battery storage: Benefits, pricing and participant matching," Applied Energy, Elsevier, vol. 301(C).
    5. Zou, Peng & Chen, Qixin & Xia, Qing & He, Guannan & Kang, Chongqing & Conejo, Antonio J., 2016. "Pool equilibria including strategic storage," Applied Energy, Elsevier, vol. 177(C), pages 260-270.
    6. Omar, Noshin & Monem, Mohamed Abdel & Firouz, Yousef & Salminen, Justin & Smekens, Jelle & Hegazy, Omar & Gaulous, Hamid & Mulder, Grietus & Van den Bossche, Peter & Coosemans, Thierry & Van Mierlo, J, 2014. "Lithium iron phosphate based battery – Assessment of the aging parameters and development of cycle life model," Applied Energy, Elsevier, vol. 113(C), pages 1575-1585.
    7. Xiao, Jiang-Wen & Yang, Yan-Bing & Cui, Shichang & Liu, Xiao-Kang, 2022. "A new energy storage sharing framework with regard to both storage capacity and power capacity," Applied Energy, Elsevier, vol. 307(C).
    8. Wang, Jianxiao & Zhong, Haiwang & Wu, Chenye & Du, Ershun & Xia, Qing & Kang, Chongqing, 2019. "Incentivizing distributed energy resource aggregation in energy and capacity markets: An energy sharing scheme and mechanism design," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    9. De Vivero-Serrano, Gustavo & Bruninx, Kenneth & Delarue, Erik, 2019. "Implications of bid structures on the offering strategies of merchant energy storage systems," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    10. Zou, Xiaoyan, 2009. "Double-sided auction mechanism design in electricity based on maximizing social welfare," Energy Policy, Elsevier, vol. 37(11), pages 4231-4239, November.
    11. Zou, Peng & Chen, Qixin & Yu, Yang & Xia, Qing & Kang, Chongqing, 2017. "Electricity markets evolution with the changing generation mix: An empirical analysis based on China 2050 High Renewable Energy Penetration Roadmap," Applied Energy, Elsevier, vol. 185(P1), pages 56-67.
    12. Afshar, Karim & Ghiasvand, Farshad Shamsini & Bigdeli, Nooshin, 2018. "Optimal bidding strategy of wind power producers in pay-as-bid power markets," Renewable Energy, Elsevier, vol. 127(C), pages 575-586.
    13. Tómasson, Egill & Hesamzadeh, Mohammad Reza & Wolak, Frank A., 2020. "Optimal offer-bid strategy of an energy storage portfolio: A linear quasi-relaxation approach," Applied Energy, Elsevier, vol. 260(C).
    14. Hameed, Zeenat & Hashemi, Seyedmostafa & Ipsen, Hans Henrik & Træholt, Chresten, 2021. "A business-oriented approach for battery energy storage placement in power systems," Applied Energy, Elsevier, vol. 298(C).
    15. Zheng, Weiye & Hill, David J., 2021. "Incentive-based coordination mechanism for distributed operation of integrated electricity and heat systems," Applied Energy, Elsevier, vol. 285(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kwang Mong Sim, 2023. "An Incentive-Compatible and Computationally Efficient Fog Bargaining Mechanism," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1883-1918, December.
    2. Xiao, Jucheng & He, Guangyu & Fan, Shuai & Li, Zuyi, 2022. "Substitute energy price market mechanism for renewable energy power system with generalized energy storage," Applied Energy, Elsevier, vol. 328(C).
    3. Maurizio Sibilla & Esra Kurul, 2023. "Towards Social Understanding of Energy Storage Systems—A Perspective," Energies, MDPI, vol. 16(19), pages 1-11, September.
    4. Jidong Wang & Jiahui Wu & Yingchen Shi, 2022. "A Novel Energy Management Optimization Method for Commercial Users Based on Hybrid Simulation of Electricity Market Bidding," Energies, MDPI, vol. 15(12), pages 1-24, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huang, Qisheng & Xu, Yunjian & Courcoubetis, Costas, 2020. "Stackelberg competition between merchant and regulated storage investment in wholesale electricity markets," Applied Energy, Elsevier, vol. 264(C).
    2. Xia, Yuanxing & Xu, Qingshan & Chen, Lu & Du, Pengwei, 2022. "The flexible roles of distributed energy storages in peer-to-peer transactive energy market: A state-of-the-art review," Applied Energy, Elsevier, vol. 327(C).
    3. Liu, Shiyu & Ren, Yanzhe & Zhang, Zhenyu & Xiao, Yao & Bie, Zhaohong & Wang, Xifan, 2021. "Optimal bid-offer strategy for a virtual energy storage merchant: A stochastic bi-level model with all-scenario feasibility," Applied Energy, Elsevier, vol. 299(C).
    4. Shahmohammadi, Ali & Sioshansi, Ramteen & Conejo, Antonio J. & Afsharnia, Saeed, 2018. "Market equilibria and interactions between strategic generation, wind, and storage," Applied Energy, Elsevier, vol. 220(C), pages 876-892.
    5. Cui, Shiting & Wu, Jun & Gao, Yao & Zhu, Ruijin, 2023. "A high altitude prosumer energy cooperation framework considering composite energy storage sharing and electric‑oxygen‑hydrogen flexible supply," Applied Energy, Elsevier, vol. 349(C).
    6. Khaloie, Hooman & Abdollahi, Amir & Shafie-khah, Miadreza & Anvari-Moghaddam, Amjad & Nojavan, Sayyad & Siano, Pierluigi & Catalão, João P.S., 2020. "Coordinated wind-thermal-energy storage offering strategy in energy and spinning reserve markets using a multi-stage model," Applied Energy, Elsevier, vol. 259(C).
    7. Zheng, Weiye & Lu, Hao & Zhu, Jizhong, 2023. "Incentivizing cooperative electricity-heat operation: A distributed asymmetric Nash bargaining mechanism," Energy, Elsevier, vol. 280(C).
    8. Wang, Haiyang & Zhang, Chenghui & Li, Ke & Liu, Shuai & Li, Shuzhen & Wang, Yu, 2021. "Distributed coordinative transaction of a community integrated energy system based on a tri-level game model," Applied Energy, Elsevier, vol. 295(C).
    9. Noordhoek, Marije & Dullaert, Wout & Lai, David S.W. & de Leeuw, Sander, 2018. "A simulation–optimization approach for a service-constrained multi-echelon distribution network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 292-311.
    10. De Vivero-Serrano, Gustavo & Bruninx, Kenneth & Delarue, Erik, 2019. "Implications of bid structures on the offering strategies of merchant energy storage systems," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    11. Christos N. Dimitriadis & Evangelos G. Tsimopoulos & Michael C. Georgiadis, 2021. "A Review on the Complementarity Modelling in Competitive Electricity Markets," Energies, MDPI, vol. 14(21), pages 1-27, November.
    12. Nitsch, Felix & Deissenroth-Uhrig, Marc & Schimeczek, Christoph & Bertsch, Valentin, 2021. "Economic evaluation of battery storage systems bidding on day-ahead and automatic frequency restoration reserves markets," Applied Energy, Elsevier, vol. 298(C).
    13. Mansour-Saatloo, Amin & Pezhmani, Yasin & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "Robust decentralized optimization of Multi-Microgrids integrated with Power-to-X technologies," Applied Energy, Elsevier, vol. 304(C).
    14. Zou, Peng & Chen, Qixin & Xia, Qing & He, Chang & Kang, Chongqing, 2015. "Incentive compatible pool-based electricity market design and implementation: A Bayesian mechanism design approach," Applied Energy, Elsevier, vol. 158(C), pages 508-518.
    15. Berecibar, M. & Gandiaga, I. & Villarreal, I. & Omar, N. & Van Mierlo, J. & Van den Bossche, P., 2016. "Critical review of state of health estimation methods of Li-ion batteries for real applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 572-587.
    16. Ester Vasta & Tommaso Scimone & Giovanni Nobile & Otto Eberhardt & Daniele Dugo & Massimiliano Maurizio De Benedetti & Luigi Lanuzza & Giuseppe Scarcella & Luca Patanè & Paolo Arena & Mario Cacciato, 2023. "Models for Battery Health Assessment: A Comparative Evaluation," Energies, MDPI, vol. 16(2), pages 1-34, January.
    17. Calvillo, C.F. & Sánchez-Miralles, A. & Villar, J. & Martín, F., 2016. "Optimal planning and operation of aggregated distributed energy resources with market participation," Applied Energy, Elsevier, vol. 182(C), pages 340-357.
    18. Sun, Li & Walker, Paul & Feng, Kaiwu & Zhang, Nong, 2018. "Multi-objective component sizing for a battery-supercapacitor power supply considering the use of a power converter," Energy, Elsevier, vol. 142(C), pages 436-446.
    19. Toufani, Parinaz & Nadar, Emre & Kocaman, Ayse Selin, 2022. "Short-term assessment of pumped hydro energy storage configurations: Up, down, or closed?," Renewable Energy, Elsevier, vol. 201(P1), pages 1086-1095.
    20. Ma, Jian & Xu, Shu & Shang, Pengchao & ding, Yu & Qin, Weili & Cheng, Yujie & Lu, Chen & Su, Yuzhuan & Chong, Jin & Jin, Haizu & Lin, Yongshou, 2020. "Cycle life test optimization for different Li-ion power battery formulations using a hybrid remaining-useful-life prediction method," Applied Energy, Elsevier, vol. 262(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:311:y:2022:i:c:s030626192200188x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.