提升配电网供电性能的风-光-储两阶段规划与配置

刘华晶; 许振波; 董苒; 王佳伟; 秦文萍

刘华晶,许振波,董苒,王佳伟,秦文萍.提升配电网供电性能的风-光-储两阶段规划与配置[J].电测与仪表,2022,59(9):23-30.
Liu Huajing,Xu Zhenbo,Dong Ran,Wang Jiawei,Qin Wenping.Wind-solar-storage two-stage planning and configuration to improve power supply performance of distribution networks[J].Electrical Measurement & Instrumentation,2022,59(9):23-30.

提升配电网供电性能的风-光-储两阶段规划与配置

Wind-solar-storage two-stage planning and configuration to improve power supply performance of distribution networks

DOI：10.19753/j.issn1001-1390.2002.09.004

中文关键词: 配电网分布式电源两阶段规划平均等效负荷混合智能求解算法储能

英文关键词:distribution network, distributed power, two-stage planning, average equivalent load, hybrid intelligent solution algorithm, energy storage

基金项目:山西省科技重大专项项目（20181102028）；山西省电力公司科技项目资助（JYY051900401）,

作者中文名	作者英文名	单位
刘华晶	Liu Huajing	太原理工大学电力系统运行与控制山西省重点实验室，太原 030024
许振波	Xu Zhenbo	国网山西省电力公司经济技术研究院，太原 030000
董苒	Dong Ran	国网山西省电力公司经济技术研究院，太原 030000
王佳伟	Wang Jiawei	国网山西省电力公司经济技术研究院，太原 030000
秦文萍	Qin Wenping	太原理工大学电力系统运行与控制山西省重点实验室，太原 030024

摘要点击次数: 1584

中文摘要:

针对配电网中分布式电源（DG）不合理规划引起供电性能下降的问题，提出了一种在风-光-储接入情况下的配电网两阶段规划与配置方法。第一阶段通过计算节点有功网损灵敏度确定风-光电源的接入位置和容量，第二阶段以储能接入容量最小，系统电压稳定指标最大，负荷缺电率最小建立多目标规划模型，同时结合节点平均等效负荷对储能充/放电进行管理。为提高第二阶段多目标问题的求解精度，提出了一种基于多目标粒子群算法的混合智能求解算法用于求解第二阶段模型，利用序数偏好法（TOPSIS）选出储能最优接入方案。文中在IEEE-33节点系统上设置四种场景进行仿真测试，结果表明所提方法可以明显改善配电网的运行情况，给相关规划与配置提供借鉴与参考。

英文摘要:

Aiming at the problem of degraded power supply performance caused by unreasonable distributed power (DG) planning in distribution network, a two-stage planning and configuration method for the distribution network under wind-solar-storage access is proposed in this paper. In the first stage, the location and capacity of the wind-solar power supply are determined by calculating the node active power loss sensitivity. In the second stage, the multi-objective planning model is established with the minimum energy storage access capacity, the largest system voltage stability index, and the smallest load shortage rate. Meanwhile, the energy storage charge/discharge is managed in conjunction with the average equivalent load of node. In order to improve the solution accuracy of the second-stage multi-objective problem, a hybrid intelligent solution algorithm based on multi-objective particle swarm optimization is proposed to solve the second-stage model. Finally, the optimal number of energy storage is selected by the TOPSIS method into the program. Four scenarios are set on the IEEE-33 node system for simulation testing. The results show that the proposed method can significantly improve the operation of the distribution network and provide reference for related planning and configuration.

查看全文查看/发表评论下载PDF阅读器

关闭