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Multi-objective optimization of a virtual power plant with mobile energy storage for a multi-stakeholders energy community

Author

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  • Yan, Xingyu
  • Gao, Ciwei
  • Francois, Bruno

Abstract

Virtual power plants play an important role in aggregating and managing flexible distributed energy resources in the local energy community, mitigating security risks such as network congestion and power flow reversal induced by distributed renewable energy sources. Concurrently, mobile energy storage devices offer mobility and dynamic deployment capabilities within the energy community, catering to real-time flexible demand and leveraging opportunities in frequency regulation markets for additional revenue streams. This paper investigates a multi-objective optimization strategy for a local energy community virtual power plant engaged in both energy and frequency regulation markets through coordinated dispatch of mobile energy storage and multiple independent prosumers. The energy community optimization framework integrates economic considerations of virtual power plants, distribution network operation security, and reducing carbon emissions. The empirical results indicate that incorporating mobile energy storage into virtual power plant dispatch operations leads to reductions in operational costs for the local energy community, driven mainly by enhanced economic efficiency. Additionally, participation in the frequency regulation market further enhances revenue potential, albeit with associated network security implications. Moreover, the proposed multi-objective optimization strategy, which balances economic, security, and environmental objectives, demonstrates a 12.7 % reduction in operational costs, a 90.1 % decrease in distribution network congestion, a 40.4 % reduction in peak-to-valley load disparity at network slack bus, and a 71.2 % decrease in equivalent carbon dioxide emissions. The paper concludes with a sensitivity analysis encompassing multi-objective optimization parameters, the probability of frequency regulation bidding being called, and spot market price dynamics.

Suggested Citation

  • Yan, Xingyu & Gao, Ciwei & Francois, Bruno, 2025. "Multi-objective optimization of a virtual power plant with mobile energy storage for a multi-stakeholders energy community," Applied Energy, Elsevier, vol. 386(C).
  • Handle: RePEc:eee:appene:v:386:y:2025:i:c:s0306261925002831
    DOI: 10.1016/j.apenergy.2025.125553
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