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Optimal bidding strategy and profit allocation method for shared energy storage-assisted VPP in joint energy and regulation markets

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  • Zhang, Tianhan
  • Qiu, Weiqiang
  • Zhang, Zhi
  • Lin, Zhenzhi
  • Ding, Yi
  • Wang, Yiting
  • Wang, Lianfang
  • Yang, Li

Abstract

Renewable energy sources (RES) generating units such as wind power and photovoltaic (PV) units can be aggregated with controllable loads as virtual power plants (VPPs) to jointly participate in energy and regulation markets for extra market revenue. However, the uncertainty of RES limits the market performance of the VPP, which can be solved by energy storage. Due to the flexibility of the energy storage sharing mode, a two-part price-based leasing mechanism of shared energy storage (SES) considering market prices and battery degradation is proposed to provide the short-term use rights of energy storage for the VPP in a new pattern. Then, an SES-assisted real-time output cooperation scheme for the VPP in joint energy and regulation markets is designed to improve the VPP market performance and a joint optimal market bidding model of the VPP with the assistance of the SES is developed to maximize the expected daily profit. Moreover, a profit allocation approach for the SES-assisted VPP based on the improved Shapley value method and the minimizing deviation algorithm (ISV-MDA) is proposed to reflect the real contributions and balance the interests of its participants. Simulations based on data from PJM and NREL Dataset illustrate that RES can significantly improve their profits by participating in the VPP to jointly lease the use rights of SES and participate in joint energy and regulation markets through the cooperation and bidding strategies. In addition, the proposed profit allocation method is more reasonable and more targeted for allocating the cooperation profit than the cooperative game-based methods.

Suggested Citation

  • Zhang, Tianhan & Qiu, Weiqiang & Zhang, Zhi & Lin, Zhenzhi & Ding, Yi & Wang, Yiting & Wang, Lianfang & Yang, Li, 2023. "Optimal bidding strategy and profit allocation method for shared energy storage-assisted VPP in joint energy and regulation markets," Applied Energy, Elsevier, vol. 329(C).
    • Handle: RePEc:eee:appene:v:329:y:2023:i:c:s0306261922014155
    DOI: 10.1016/j.apenergy.2022.120158
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    References listed on IDEAS

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    1. Luwen Pan & Jiajia Chen, 2024. "Optimal Energy Storage Configuration of Prosumers with Uncertain Photovoltaic in the Presence of Customized Pricing-Based Demand Response," Sustainability, MDPI, vol. 16(6), pages 1-18, March.
    2. Wang, Dongxue & Fan, Ruguo & Yang, Peiwen & Du, Kang & Xu, Xiaoxia & Chen, Rongkai, 2024. "Research on floating real-time pricing strategy for microgrid operator in local energy market considering shared energy storage leasing," Applied Energy, Elsevier, vol. 368(C).
    3. Yan Gao & Long Gao & Pei Zhang & Qiang Wang, 2023. "Two-Stage Optimization Scheduling of Virtual Power Plants Considering a User-Virtual Power Plant-Equipment Alliance Game," Sustainability, MDPI, vol. 15(18), pages 1-28, September.
    4. Uda Bala & Wei Li & Wenguo Wang & Yuying Gong & Yaheng Su & Yingshu Liu & Yi Zhang & Wei Wang, 2024. "The Sharing Energy Storage Mechanism for Demand Side Energy Communities," Energies, MDPI, vol. 17(21), pages 1-19, October.
    5. Lu, Xin & Qiu, Jing & Zhang, Cuo & Lei, Gang & Zhu, Jianguo, 2024. "Seizing unconventional arbitrage opportunities in virtual power plants: A profitable and flexible recruitment approach," Applied Energy, Elsevier, vol. 358(C).
    6. Mei, Shufan & Tan, Qinliang & Liu, Yuan & Trivedi, Anupam & Srinivasan, Dipti, 2023. "Optimal bidding strategy for virtual power plant participating in combined electricity and ancillary services market considering dynamic demand response price and integrated consumption satisfaction," Energy, Elsevier, vol. 284(C).
    7. Alain Aoun & Mehdi Adda & Adrian Ilinca & Mazen Ghandour & Hussein Ibrahim, 2024. "Optimizing Virtual Power Plant Management: A Novel MILP Algorithm to Minimize Levelized Cost of Energy, Technical Losses, and Greenhouse Gas Emissions," Energies, MDPI, vol. 17(16), pages 1-23, August.
    8. Gang Liang & Yu Wang & Bing Sun & Zheng Zhang, 2024. "An Optimization Method for the Distributed Collaborative Operation of Multilateral Entities Considering Dynamic Time-of-Use Electricity Price in Active Distribution Network," Energies, MDPI, vol. 17(2), pages 1-19, January.
    9. Li, Qiang & Zhou, Yongcheng & Wei, Fanchao & Li, Shuangxiu & Wang, Zhonghao & Li, Jiajia & Zhou, Guowen & Liu, Jinfu & Yan, Peigang & Yu, Daren, 2024. "Multi-time scale scheduling for virtual power plants: Integrating the flexibility of power generation and multi-user loads while considering the capacity degradation of energy storage systems," Applied Energy, Elsevier, vol. 362(C).
    10. Ebrahimi, Mahoor & Ebrahimi, Mahan & Shafie-khah, Miadreza & Laaksonen, Hannu, 2024. "EV-observing distribution system management considering strategic VPPs and active & reactive power markets," Applied Energy, Elsevier, vol. 364(C).
    11. Yang, Shenbo & Fang, Jiangpeng & Zhang, Zheyu & Lv, ShuoShuo & Lin, Hongyu & Ju, Liwei, 2024. "Two-stage coordinated optimal dispatching model and benefit allocation strategy for rural new energy microgrid," Energy, Elsevier, vol. 292(C).
    12. Cui, Jingshi & Wu, Jiaman & Wu, Chenye & Moura, Scott, 2023. "Electric vehicles embedded virtual power plants dispatch mechanism design considering charging efficiencies," Applied Energy, Elsevier, vol. 352(C).
    13. Yuanyuan, Zhang & Huiru, Zhao & Bingkang, Li, 2023. "Distributionally robust comprehensive declaration strategy of virtual power plant participating in the power market considering flexible ramping product and uncertainties," Applied Energy, Elsevier, vol. 343(C).
    14. Bian, Yifan & Xie, Lirong & Ye, Jiahao & Ma, Lan & Cui, Chuanshi, 2024. "Peer-to-peer energy sharing model considering multi-objective optimal allocation of shared energy storage in a multi-microgrid system," Energy, Elsevier, vol. 288(C).
    15. Sun, Xiaotian & Xie, Haipeng & Qiu, Dawei & Xiao, Yunpeng & Bie, Zhaohong & Strbac, Goran, 2023. "Decentralized frequency regulation service provision for virtual power plants: A best response potential game approach," Applied Energy, Elsevier, vol. 352(C).
    16. Nurcan Yarar & Yeliz Yoldas & Serkan Bahceci & Ahmet Onen & Jaesung Jung, 2024. "A Comprehensive Review Based on the Game Theory with Energy Management and Trading," Energies, MDPI, vol. 17(15), pages 1-29, July.
    17. Jia, Dongqing & Li, Xingmei & Gong, Xu & Lv, Xiaoyan & Shen, Zhong, 2024. "Bi-level strategic bidding model of novel virtual power plant aggregating waste gasification in integrated electricity and hydrogen markets," Applied Energy, Elsevier, vol. 357(C).
    18. Tang, Qinghu & Guo, Hongye & Zheng, Kedi & Chen, Qixin, 2024. "Forecasting individual bids in real electricity markets through machine learning framework," Applied Energy, Elsevier, vol. 363(C).
    19. Hou, Langbo & Tong, Xi & Chen, Heng & Fan, Lanxin & Liu, Tao & Liu, Wenyi & Liu, Tong, 2024. "Optimized scheduling of smart community energy systems considering demand response and shared energy storage," Energy, Elsevier, vol. 295(C).

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