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Planning shared energy storage systems for the spatio-temporal coordination of multi-site renewable energy sources on the power generation side

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  • Song, Xiaoling
  • Zhang, Huqing
  • Fan, Lurong
  • Zhang, Zhe
  • Peña-Mora, Feniosky

Abstract

The application prospects of shared energy storage services have gained widespread recognition due to the increasing use of renewable energy sources. However, the decision-making process for connecting different renewable energy generators and determining the appropriate size of the shared energy storage capacity becomes a complex and interrelated problem when considering the multi-site spatio-temporal characteristics. This paper presents an optimal planning and operation architecture for multi-site renewable energy generators that share an energy storage system on the generation side. Furthermore, an economic-environmental model is proposed to minimize the costs associated with the energy system infrastructure while maintaining a high penetration rate of renewable energy. The centralized multi-objective model allows renewable energy generators to make cost-optimal planning decisions for connecting to the shared energy storage station, while also optimizing the size of the storage capacity to maximize renewable energy generation and minimize costs. The Non-dominated Sorting Genetic Algorithm-II is employed in a centralized manner to solve the multi-objective nonlinear model. Numerical experiments are conducted to demonstrate the economic and environmental benefits of the proposed system. Therefore, this method is highly recommended for implementation on the generation side.

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  • Song, Xiaoling & Zhang, Huqing & Fan, Lurong & Zhang, Zhe & Peña-Mora, Feniosky, 2023. "Planning shared energy storage systems for the spatio-temporal coordination of multi-site renewable energy sources on the power generation side," Energy, Elsevier, vol. 282(C).
  • Handle: RePEc:eee:energy:v:282:y:2023:i:c:s0360544223023708
    DOI: 10.1016/j.energy.2023.128976
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