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Share or not share, the analysis of energy storage interaction of multiple renewable energy stations based on the evolution game

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  • Li, Xiaozhu
  • Chen, Laijun
  • Sun, Fan
  • Hao, Yibo
  • Du, Xili
  • Mei, Shenwei

Abstract

With the increasing penetration of renewable energy, the traditional energy storage operation based on individual framework —users own and operate independently mode may become impracticable due to conflicting interests, insufficient utilization, and poor interoperability. Riding on the wave of the proliferation of sharing economy, storage energy sharing expands the existing storage energy without requiring costly and time-consuming infrastructure investments. However, the development path of shared energy storage (SES) mode is not clear due to the asymmetric decision-making of the owners of energy storage systems under bounded rationality. In this paper, the diffusion of the business model of SES among multiple renewable energy stations (the owners, RES) and its key factors are analyzed based on the evolutionary game. The goal is to maximize social welfare and ensure the continuous growth of the sharing market. The numerical simulation is carried out based on the data from northwest China to interpret the development path. The result shows that, in renewable energy cluster the stations with intermittent output or with the higher prediction accuracy are more willing to participate in sharing. The energy storage sharing mode fails when the energy storage capacity ratio of RES is less than 10%. While the high-level ratio (more than 30%) is not conducive to the diffusion of the sharing model in RESs with low power generation prediction accuracy.

Suggested Citation

  • Li, Xiaozhu & Chen, Laijun & Sun, Fan & Hao, Yibo & Du, Xili & Mei, Shenwei, 2023. "Share or not share, the analysis of energy storage interaction of multiple renewable energy stations based on the evolution game," Renewable Energy, Elsevier, vol. 208(C), pages 679-692.
    • Handle: RePEc:eee:renene:v:208:y:2023:i:c:p:679-692
    DOI: 10.1016/j.renene.2023.03.010
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    3. Ju, Liwei & Bai, Xiping & Li, Gen & Gan, Wei & Qi, Xin & Ye, Fan, 2024. "Two-stage robust transaction optimization model and benefit allocation strategy for new energy power stations with shared energy storage considering green certificate and virtual energy storage mode," Applied Energy, Elsevier, vol. 362(C).

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