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Optimization of shared energy storage configuration for village-level photovoltaic systems considering vehicle charging management

Author

Listed:
  • Wang, Haifeng
  • Liao, Yate
  • Zhang, Jiarui
  • Cai, Ziwen
  • Zhao, Yun
  • Wang, Weijun

Abstract

Distributed renewable energy is more abundant in rural areas, and a large amount of distributed photovoltaic grid-connected power brings challenges to the stable of the power grid. How to promote the self-generation and self-consumption of distributed renewable energy has become an urgent problem. In this paper, a village-level distributed photovoltaic power generation system including energy storage and electric vehicles is constructed. With the goal of minimizing the photovoltaic grid-connected power and maximizing the annual comprehensive revenue, the planning model of energy storage capacity allocation for village-level distributed power generation system is constructed. Considering the charging management for different numbers of electric vehicles, the optimal energy storage capacity allocation strategy is solved using the improved particle swarm algorithm.Five scenarios are set up as examples to be analyzed.The conclusions are:(1)After the configuration of a reasonable energy storage,the grid-connected generation of the system is significantly reduced,and the annual comprehensive revenue of the system is significantly increased.(2)After considering charging management for different numbers of electric vehicles, the capacity and power of the energy storage configuration can be significantly reduced, thus reducing the energy storage investment cost and operation and maintenance cost, and further significantly improving the annual comprehensive revenue of this system.

Suggested Citation

  • Wang, Haifeng & Liao, Yate & Zhang, Jiarui & Cai, Ziwen & Zhao, Yun & Wang, Weijun, 2024. "Optimization of shared energy storage configuration for village-level photovoltaic systems considering vehicle charging management," Energy, Elsevier, vol. 311(C).
    • Handle: RePEc:eee:energy:v:311:y:2024:i:c:s0360544224031499
    DOI: 10.1016/j.energy.2024.133373
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