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Research on distributionally robust energy storage capacity allocation for output fluctuations in high permeability wind and solar distribution networks

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  • Xin Wang
  • Bo Sun
  • Cheng Ge
  • Qian Liu
  • Zhiwei Li
  • Mengqi Huang

Abstract

This paper presents a novel approach to addressing the challenges associated with energy storage capacity allocation in high-permeability wind and solar distribution networks. The proposed method is a two-phase distributed robust energy storage capacity allocation method, which aims to regulate the stochasticity and volatility of net energy output. Firstly, an energy storage capacity allocation model is established, which considers energy storage’s investment and operation costs to minimize the total cost. Then, a two-stage distributed robust energy storage capacity allocation model is established with the confidence set of uncertainty probability distribution constrained by 1-norm and ∞-norm. Finally, a Column and Constraint Generation (C&CG) algorithm is used to solve the problem. The validity of the proposed energy storage capacity allocation model is confirmed by examining different wind and solar penetration levels. Furthermore, the model’s superiority is demonstrated by comparing it with deterministic and robust models.

Suggested Citation

  • Xin Wang & Bo Sun & Cheng Ge & Qian Liu & Zhiwei Li & Mengqi Huang, 2024. "Research on distributionally robust energy storage capacity allocation for output fluctuations in high permeability wind and solar distribution networks," PLOS ONE, Public Library of Science, vol. 19(3), pages 1-18, March.
    • Handle: RePEc:plo:pone00:0299226
    DOI: 10.1371/journal.pone.0299226
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    References listed on IDEAS

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    1. Dongmei Zhao & Xuan Xia & Ran Tao, 2019. "Optimal Configuration of Electric-Gas-Thermal Multi-Energy Storage System for Regional Integrated Energy System," Energies, MDPI, vol. 12(13), pages 1-22, July.
    2. Zhao, Haoran & Wu, Qiuwei & Hu, Shuju & Xu, Honghua & Rasmussen, Claus Nygaard, 2015. "Review of energy storage system for wind power integration support," Applied Energy, Elsevier, vol. 137(C), pages 545-553.
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