基于混合算法的配电网中电池储能的多目标优化配置研究

曹文思, 张敏, 黄慧

太阳能学报 ›› 2022, Vol. 43 ›› Issue (5) : 541-546.

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太阳能学报 ›› 2022, Vol. 43 ›› Issue (5) : 541-546. DOI: 10.19912/j.0254-0096.tynxb.2020-0529

基于混合算法的配电网中电池储能的多目标优化配置研究

  • 曹文思1, 张敏2, 黄慧1
作者信息 +

RESEARCH ON MULTI-OBJECTIVE OPTIMAL CONFIGURATION OF BATTERY ENERGY STORAGE IN DISTRIBUTION NETWORK BASED ON HYBRID ALGORITHM

  • Cao Wensi1, Zhang Min2, Huang Hui1
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文章历史 +

摘要

基于随机会约束规划理论,计及系统的不确定性因素提出配电网储能电站多目标选址定容模型。首先分析配电网的经济性和可靠性特征,接着基于随机机会约束规划建立储能电站的优化模型。采用二进制粒子群算法和改进粒子群算法的混合算法对模型进行求解。最后利用研究模型,结合IEEE 33标准节点系统建立配电网储能电站优化算例,对离网模式和并网模式2种模式进行仿真,对优化配置结果进行对比和分析。

Abstract

Based on the theory of random constrained programming and considering the uncertain factors of the system, a multi-objective location and capacity model for energy storage power stations in the distribution network is proposed. First, the economic and reliability characteristics of the distribution network are analyzed, and then the optimization model of the energy storage power station is established based on random chance constraint programming. The binary particle swarm algorithm and the hybrid algorithm of improved particle swarm algorithm are used to solve the model. Finally, according to the research model which is established, combined with the IEEE 33 standard node distribution network system, a optimization configuration example of the energy storage power station in the distribution network is established, and the two modes of off-grid mode and grid-connected mode are simulated, and the optimized configuration results are compared and analyzed.

关键词

储能电池 / 可靠性分析 / 主动配电网 / 多目标优化 / 改进粒子群算法

Key words

battery energy storage / reliability analysis / active distribution network / multi-objective optimization / improved particle swarm algorithm

引用本文

导出引用
曹文思, 张敏, 黄慧. 基于混合算法的配电网中电池储能的多目标优化配置研究[J]. 太阳能学报. 2022, 43(5): 541-546 https://doi.org/10.19912/j.0254-0096.tynxb.2020-0529
Cao Wensi, Zhang Min, Huang Hui. RESEARCH ON MULTI-OBJECTIVE OPTIMAL CONFIGURATION OF BATTERY ENERGY STORAGE IN DISTRIBUTION NETWORK BASED ON HYBRID ALGORITHM[J]. Acta Energiae Solaris Sinica. 2022, 43(5): 541-546 https://doi.org/10.19912/j.0254-0096.tynxb.2020-0529
中图分类号: TM732   

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基金

2019年度河南省重点研发与推广专项(科技攻关)(192102210229); 河南省高等学校重点科研项目(19A-470006); 2019年度河南省高等学校青年骨干教师培养计划(2019GGJS104)

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