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文章摘要
考虑共享储能的氢电微网容量优化配置研究
Study on optimal capacity allocation of hydrogen power microgrid considering shared energy storage
Received:December 02, 2024  Revised:January 06, 2025
DOI:10.19753 / j.issn1001-1390.2026.08.002
中文关键词: 合作博弈  容量配置  可再生能源消纳  经济分析  风光制氢  平准化制氢成本
英文关键词: Cooperative game  Capacity allocation  Renewable energy consumption  Economic analysis  Hydrogen production from wind  Levelised cost of hydrogen production
基金项目:国家自然科学基金面上项目(52277211); 国家 电网有限公司指南项目(5400-202318247A-1-1-ZN)
Author NameAffiliationE-mail
LI Jianlin National User-Side Energy Storage Innovation Research and Development Center North China University of Technology dkyljl@163.com 
WANG Dalong* National User-Side Energy Storage Innovation Research and Development Center North China University of Technology 623781017@qq.com 
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中文摘要:
      发电侧储能电站能够提高可再生能源发电的可靠性,有利于电解水制氢对新能源消纳,因此本文针对氢电微网的容量配置问题提出了一种考虑共享储能的氢电微网容量优化配置方法。首先,考虑可再生能源发电站与共享储能之间的合作联盟机制建立氢电微网双层规划模型,在双层规划模型中,上层考虑风力和光伏发电典型场景的互补特性与波动性,以各合作联盟中博弈参与者全寿命周期下的净收益为优化目标建立氢电微网容量配置优化模型;下层以微网运行成本和共享储能租赁服务费收益为优化目标对共享储能的出力计划与服务费价格进行优化建模。算例分析表明,储能电站与可再生能源发电站进行合作博弈可以使系统净收益等年值至少提高18.74%。
英文摘要:
      Power generation side energy storage plant can improve the reliability of renewable energy power generation, and is conducive to the electrolysis of water to produce hydrogen for new energy consumption, so this paper proposes a method for optimising the capacity allocation of hydrogen microgrids by considering shared energy storage for the capacity allocation of hydrogen microgrids.Firstly, a two-layer planning model for the hydrogen microgrid is established by considering the cooperative alliance mechanism between renewable energy power stations and shared energy storage. In the two-layer planning model, the upper layer takes into account the complementary characteristics and volatility of the typical scenarios of wind and photovoltaic power generation, and establishes an optimization model of the capacity allocation of the hydrogen microgrid by taking the net benefit of the participants of the game in the cooperative alliance in the whole life cycle as the optimization objective; the lower layer takes the o
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