Scholarlink

<p>The paper addresses the economic operation optimization problem of photovoltaic charging-swapping-storage integrated stations (PCSSIS) in high-penetration distribution networks. It proposes a dual-layer optimization scheduling model for PCSSIS clusters and distribution network systems. Firstly, a master–slave game model is constructed. The upper layer takes the high-penetration distribution network as the decision-making entity and aims to maximize its own revenue while considering the energy trading of PCSSIS. The lower layer takes PCSSIS as the decision-making entity, and PCSSIS adjusts energy flow and optimizes revenue based on the internal electricity price provided by the upper-layer distribution network. Secondly, the differential evolution algorithm and GUROBI solver are used to solve for the maximum revenue, internal electricity price, and electricity consumption of PCSSIS and the distribution network. Finally, the effectiveness of the proposed strategy is verified through case studies and simulations.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Double layers optimal scheduling of distribution networks and photovoltaic charging and storage station cluster based on leader follower game theory

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年1月3日

查看全文
  • Zixuan Liu,
  • Jun Wu,
  • Ruijin Zhu,
  • Dewen Kong,
  • Hao Guo

摘要

The paper addresses the economic operation optimization problem of photovoltaic charging-swapping-storage integrated stations (PCSSIS) in high-penetration distribution networks. It proposes a dual-layer optimization scheduling model for PCSSIS clusters and distribution network systems. Firstly, a master–slave game model is constructed. The upper layer takes the high-penetration distribution network as the decision-making entity and aims to maximize its own revenue while considering the energy trading of PCSSIS. The lower layer takes PCSSIS as the decision-making entity, and PCSSIS adjusts energy flow and optimizes revenue based on the internal electricity price provided by the upper-layer distribution network. Secondly, the differential evolution algorithm and GUROBI solver are used to solve for the maximum revenue, internal electricity price, and electricity consumption of PCSSIS and the distribution network. Finally, the effectiveness of the proposed strategy is verified through case studies and simulations.