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文章摘要
计及无功补偿装置协调优化的配电网分布式光储选址定容
Optimal sizing and siting of distributed photovoltaic in distribution network considering coordinated optimization of reactive power compensation devices
Received:December 17, 2024  Revised:February 17, 2025
DOI:10.19753/j.issn1001-1390.2026.09.012
中文关键词: 配电网  分布式光储  选址定容  源-网-储协同优化  二阶锥松弛  Big-M法  双层模型
英文关键词: distribution network, distributed photovoltaic and energy storage, siting and sizing,source-network-storage collaborative optimization, second-order cone relaxation,Big-M method, bi-level model
基金项目:国家重点研发计划项目(国际合作专项)(2021YFE0190900);唐山市科学计划项目(22130210H)
Author NameAffiliationE-mail
Zhang Yi College of Electrical Engineering, North China University of Science and Technology zhangyi@ncst.edu.cn 
Chu Tianze College of Electrical Engineering, North China University of Science and Technology tiantian9516166@163.com 
WU Baojiang* College of Electrical Engineering, North China University of Science and Technology ctzxsyx@163.com 
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中文摘要:
      针对配电网中因分布式光伏和储能的位置与容量规划不合理所导致的电压质量下降、网损增加及分布式光伏消纳能力降低等问题,提出一种计及无功补偿装置协调优化的配电网分布式光储选址定容方法。该方法首先结合网损灵敏度和动态电压稳定性指数确定分布式光伏和储能的并网位置,在此基础上利用分布式光伏、储能、分组投切电容器及静止无功补偿器进行协同优化配置,构建源-网-储协同优化双层规划模型来确定分布式光储配置的容量。同时,为了有效求解该双层模型,通过关联建模将上下层模型转化为单层模型,将此单层模型转化为混合整数二阶锥规化模型。在IEEE33节点配电系统上设置四种场景进行仿真,结果表明,采用该方法确定分布式光储在配电网中的位置和容量,不仅能提高分布式光伏消纳能力和电压质量,还能延长分组投切电容器寿命,并显著降低网络损耗,从而验证了该方法的有效性。
英文摘要:
      A method for optimal sizing and siting of distributed photovoltaic and energy storage in a distribution network, considering coordinated optimization of reactive power compensation devices, is proposed to address issues such as voltage quality degradation, increased network losses, and reduced photovoltaic absorption capacity caused by improper location and capacity planning of distributed photovoltaic and energy storage.This method first determines the grid connection locations of distributed photovoltaic and energy storage based on network loss sensitivity and dynamic voltage stability index.Subsequently, a collaborative optimization configuration is employed utilizing distributed photovoltaic, energy storage, capacitor banks, and static var compensators, constructing a source-network-storage collaborative optimization bi-level planning model to determine the configuration capacity of distributed photovoltaic and energy storage. Furthermore, to effectively solve this bi-level model, the upper and lower models are transformed into a single-level model through associative modeling, followed by transforming this single-level model into a mixed integer second-order cone programming model using second-order cone relaxation and the Big-M method. Four scenarios are set up for simulation on the IEEE 33-node distribution system. The results indicate that the location and capacity of distributed photovoltaic and energy storagein the distribution network are determined using this method, not only is the photovoltaic absorption capacity and voltage quality improved, but thelifespan of capacitor banks is extended, and network losses are significantly reduced, thus verifying the effectiveness of the method.
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