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Analysis of offering behavior of generation-side integrated energy aggregator in electricity market:A Bayesian evolutionary approach

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  • Yang, Peiwen
  • Dong, Jun
  • Lin, Jin
  • Liu, Yao
  • Fang, Debin

Abstract

Integrated energy systems (IESs) as the widely concerned multi-energy systems have significant contributions to enhancing energy utilization efficiency and renewable energy (RE) consumption. With the increasing proportion of RE, integrated energy aggregators (IEAs), who coordinate IESs with multiple generators, will have more important roles in the future smart grid. This paper presents a Bayesian evolutionary game (BEG) method to study the optimal supply strategy for generating units of different energy types to maximize their own profits in an unregulated power market. The competition among IEAs lowers their willingness to share their information and restricts the profit themselves. Given this information asymmetry, the interaction of three types of generators in IESs is captured by the Bayesian game to transform the incomplete game into a complete game with imperfect information. Given the dynamic of the spot market, this paper combines the Evolutionary game theory with Bayesian theory to study the symbiotic evolution among them. Simulations are introduced to examine the asymptotic stability of various evolutionary stabilization strategies. The results verify the effectiveness of the proposed model. Finally, the implications of different renewable energy penetration, market-clearing rules, market share, and the market supply-demand ratio on IEAs’ offering behavior are explored by applying the experimental economics principle.

Suggested Citation

  • Yang, Peiwen & Dong, Jun & Lin, Jin & Liu, Yao & Fang, Debin, 2021. "Analysis of offering behavior of generation-side integrated energy aggregator in electricity market:A Bayesian evolutionary approach," Energy, Elsevier, vol. 228(C).
  • Handle: RePEc:eee:energy:v:228:y:2021:i:c:s0360544221007593
    DOI: 10.1016/j.energy.2021.120510
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    as
    1. Daniel Friedman, 1998. "On economic applications of evolutionary game theory," Journal of Evolutionary Economics, Springer, vol. 8(1), pages 15-43.
    2. Cai, Wei & Mohammaditab, Rasoul & Fathi, Gholamreza & Wakil, Karzan & Ebadi, Abdol Ghaffar & Ghadimi, Noradin, 2019. "Optimal bidding and offering strategies of compressed air energy storage: A hybrid robust-stochastic approach," Renewable Energy, Elsevier, vol. 143(C), pages 1-8.
    3. Dai, Xuemei & Li, Yaping & Zhang, Kaifeng & Feng, Wei, 2020. "A robust offering strategy for wind producers considering uncertainties of demand response and wind power," Applied Energy, Elsevier, vol. 279(C).
    4. Jorgen W. Weibull, 1997. "Evolutionary Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262731215, December.
    5. Clements, A.E. & Hurn, A.S. & Li, Z., 2016. "Strategic bidding and rebidding in electricity markets," Energy Economics, Elsevier, vol. 59(C), pages 24-36.
    6. 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.
    7. Wang, Jianxiao & Zhong, Haiwang & Tang, Wenyuan & Rajagopal, Ram & Xia, Qing & Kang, Chongqing & Wang, Yi, 2017. "Optimal bidding strategy for microgrids in joint energy and ancillary service markets considering flexible ramping products," Applied Energy, Elsevier, vol. 205(C), pages 294-303.
    8. Moghaddam, Saeed Zolfaghari & Akbari, Tohid, 2018. "Network-constrained optimal bidding strategy of a plug-in electric vehicle aggregator: A stochastic/robust game theoretic approach," Energy, Elsevier, vol. 151(C), pages 478-489.
    9. Chen, Xi & Wang, Chengfu & Wu, Qiuwei & Dong, Xiaoming & Yang, Ming & He, Suoying & Liang, Jun, 2020. "Optimal operation of integrated energy system considering dynamic heat-gas characteristics and uncertain wind power," Energy, Elsevier, vol. 198(C).
    10. Wang, Haiyang & Zhang, Chenghui & Li, Ke & Ma, Xin, 2021. "Game theory-based multi-agent capacity optimization for integrated energy systems with compressed air energy storage," Energy, Elsevier, vol. 221(C).
    11. Pingkuo, Liu & Huan, Peng & Zhiwei, Wang, 2020. "Orderly-synergistic development of power generation industry: A China’s case study based on evolutionary game model," Energy, Elsevier, vol. 211(C).
    12. Lasemi, Mohammad Ali & Arabkoohsar, Ahmad, 2020. "Optimal operating strategy of high-temperature heat and power storage system coupled with a wind farm in energy market," Energy, Elsevier, vol. 210(C).
    13. Xin-gang, Zhao & Ling-zhi, Ren & Yu-zhuo, Zhang & Guan, Wan, 2018. "Evolutionary game analysis on the behavior strategies of power producers in renewable portfolio standard," Energy, Elsevier, vol. 162(C), pages 505-516.
    14. Aliabadi, Danial Esmaeili & Kaya, Murat & Şahin, Güvenç, 2017. "An agent-based simulation of power generation company behavior in electricity markets under different market-clearing mechanisms," Energy Policy, Elsevier, vol. 100(C), pages 191-205.
    15. Ma, Tengfei & Pei, Wei & Xiao, Hao & Kong, Li & Mu, Yunfei & Pu, Tianjiao, 2020. "The energy management strategies based on dynamic energy pricing for community integrated energy system considering the interactions between suppliers and users," Energy, Elsevier, vol. 211(C).
    16. Yang, Xiaohui & Chen, Zaixing & Huang, Xin & Li, Ruixin & Xu, Shaoping & Yang, Chunsheng, 2021. "Robust capacity optimization methods for integrated energy systems considering demand response and thermal comfort," Energy, Elsevier, vol. 221(C).
    17. Fazlalipour, Pary & Ehsan, Mehdi & Mohammadi-Ivatloo, Behnam, 2019. "Risk-aware stochastic bidding strategy of renewable micro-grids in day-ahead and real-time markets," Energy, Elsevier, vol. 171(C), pages 689-700.
    18. repec:hhs:iuiwop:487 is not listed on IDEAS
    19. Aghamohamadi, Mehrdad & Mahmoudi, Amin, 2019. "From bidding strategy in smart grid toward integrated bidding strategy in smart multi-energy systems, an adaptive robust solution approach," Energy, Elsevier, vol. 183(C), pages 75-91.
    20. Mu, Chenlu & Ding, Tao & Qu, Ming & Zhou, Quan & Li, Fangxing & Shahidehpour, Mohammad, 2020. "Decentralized optimization operation for the multiple integrated energy systems with energy cascade utilization," Applied Energy, Elsevier, vol. 280(C).
    21. Fang, Yujuan & Chen, Laijun & Mei, Shengwei & Wei, Wei & Huang, Shaowei & Liu, Feng, 2019. "Coal or electricity? An evolutionary game approach to investigate fuel choices of urban heat supply systems," Energy, Elsevier, vol. 181(C), pages 107-122.
    22. 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).
    23. Wang, Jianhui & Zhou, Zhi & Botterud, Audun, 2011. "An evolutionary game approach to analyzing bidding strategies in electricity markets with elastic demand," Energy, Elsevier, vol. 36(5), pages 3459-3467.
    24. Zhang, Menglin & Wu, Qiuwei & Wen, Jinyu & Pan, Bo & Qi, Shiqiang, 2020. "Two-stage stochastic optimal operation of integrated electricity and heat system considering reserve of flexible devices and spatial-temporal correlation of wind power," Applied Energy, Elsevier, vol. 275(C).
    25. Motalleb, Mahdi & Annaswamy, Anuradha & Ghorbani, Reza, 2018. "A real-time demand response market through a repeated incomplete-information game," Energy, Elsevier, vol. 143(C), pages 424-438.
    26. Zhang, Minhui & Zhang, Qin & Zhou, Dequn & Wang, Lei, 2021. "Punishment or reward? Strategies of stakeholders in the quality of photovoltaic plants based on evolutionary game analysis in China," Energy, Elsevier, vol. 220(C).
    27. Laia, R. & Pousinho, H.M.I. & Melíco, R. & Mendes, V.M.F., 2016. "Bidding strategy of wind-thermal energy producers," Renewable Energy, Elsevier, vol. 99(C), pages 673-681.
    28. 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.
    29. Dominguez, R. & Baringo, L. & Conejo, A.J., 2012. "Optimal offering strategy for a concentrating solar power plant," Applied Energy, Elsevier, vol. 98(C), pages 316-325.
    30. Tsimopoulos, Evangelos G. & Georgiadis, Michael C., 2019. "Optimal strategic offerings for a conventional producer in jointly cleared energy and balancing markets under high penetration of wind power production," Applied Energy, Elsevier, vol. 244(C), pages 16-35.
    Full references (including those not matched with items on IDEAS)

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    2. Xinyi Xie & Liming Ying & Xue Cui, 2022. "Price Strategy Analysis of Electricity Retailers Based on Evolutionary Game on Complex Networks," Sustainability, MDPI, vol. 14(15), pages 1-17, August.

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