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Peer-to-Peer energy trading strategy for energy balance service provider (EBSP) considering market elasticity in community microgrid

Author

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  • Wang, Zibo
  • Yu, Xiaodan
  • Mu, Yunfei
  • Jia, Hongjie
  • Jiang, Qian
  • Wang, Xiaoyu

Abstract

The peer-to-peer (P2P) energy trading technology can effectively promote the mutual exchange and complementation of energy among diversified prosumers in the community microgrid. To further improve the energy resource allocation performance of the P2P energy trading, an energy balance service provider (EBSP) can be involved in the market. EBSP is an independent commercial entity configured with high-capacity energy storage systems (ESS) or auxiliary power sources, participating in the P2P market for profit. The energy shifting ability of EBSP can further improve the overall benefit of the microgrid. However, the scale effect endows the EBSP with comparatively strong market power, which may impose influence on the equilibrium of the P2P market. From the perspective of EBSP, the P2P market can be regarded as a market with elasticity. In the existing researches on optimized pricing and trading strategies of the P2P market, such a characteristic was not fully considered, which may have negative impacts on the economic profit of the EBSP and the overall benefit of the microgrid. Therefore, a P2P energy trading strategy for EBSP considering market elasticity is proposed in this paper. A market equilibrium model for the community microgrid with EBSP is first established, which reflects the elasticity of the market. Then, an optimized pricing model and trading strategy are established and solved to maximize the EBSP’s profit. Numerical results show that the proposed method can improve the profit of EBSP, meanwhile reducing the energy dispatching cost of prosumers, achieving peak load shifting and renewable energy self-consumption of the community microgrid.

Suggested Citation

  • Wang, Zibo & Yu, Xiaodan & Mu, Yunfei & Jia, Hongjie & Jiang, Qian & Wang, Xiaoyu, 2021. "Peer-to-Peer energy trading strategy for energy balance service provider (EBSP) considering market elasticity in community microgrid," Applied Energy, Elsevier, vol. 303(C).
    • Handle: RePEc:eee:appene:v:303:y:2021:i:c:s0306261921009703
    DOI: 10.1016/j.apenergy.2021.117596
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    References listed on IDEAS

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    2. Ma, Huan & Sun, Qinghan & Chen, Qun & Zhao, Tian & He, Kelun, 2023. "Exergy-based flexibility cost indicator and spatio-temporal coordination principle of distributed multi-energy systems," Energy, Elsevier, vol. 267(C).
    3. Zhu, Dafeng & Yang, Bo & Ma, Chengbin & Wang, Zhaojian & Zhu, Shanying & Ma, Kai & Guan, Xinping, 2022. "Stochastic gradient-based fast distributed multi-energy management for an industrial park with temporally-coupled constraints," Applied Energy, Elsevier, vol. 317(C).
    4. Xu, Jiazhu & Yi, Yuqin, 2023. "Multi-microgrid low-carbon economy operation strategy considering both source and load uncertainty: A Nash bargaining approach," Energy, Elsevier, vol. 263(PB).
    5. Wang, Zibo & Dong, Lei & Shi, Mengjie & Qiao, Ji & Jia, Hongjie & Mu, Yunfei & Pu, Tianjiao, 2023. "Market power modeling and restraint of aggregated prosumers in peer-to-peer energy trading: A game-theoretic approach," Applied Energy, Elsevier, vol. 348(C).
    6. Liu, Jia & Zhou, Yuekuan & Yang, Hongxing & Wu, Huijun, 2022. "Uncertainty energy planning of net-zero energy communities with peer-to-peer energy trading and green vehicle storage considering climate changes by 2050 with machine learning methods," Applied Energy, Elsevier, vol. 321(C).
    7. Chang, Weiguang & Dong, Wei & Yang, Qiang, 2023. "Day-ahead bidding strategy of cloud energy storage serving multiple heterogeneous microgrids in the electricity market," Applied Energy, Elsevier, vol. 336(C).

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