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基于分群结构优化的储能配置规划 被引量:5

Optimal Planning of Energy Storage Based on Site Selection of Cluster Structure Optimization
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摘要 储能资源与源网荷资源的深度融合是构建高比例可再生能源新型电力系统的关键,随着系统规划和运行环节源网荷储互动程度的不断提高,在储能资源规划过程中考虑其与源网荷资源的时空耦合特性已是储能规划的核心环节。构建储能选址分群结构优化模型,决策储能布点待选站点集合,并以储能投资净收益最大为目标,联合采用遗传算法和二阶锥松弛算法,求解含分群结构优化的储能配置优化规划模型。算例分析表明,面向大规模复杂网络的储能规划,考虑发用电特性及网架空间分布,分群优化布点储能,有利于协调不同送受特性的集群间储能资源的配置与协同增效运行,经济提高可再生能源消纳水平。 The efficient interaction of source,network,load and storage in a high-proportion renewable energy system depends on the deep integration in its spatial structure. In order to promote the full coordination of energy storage resources in the spatial layout with source network load resources in the planning stage,a cluster division model that considers power generation and consumption characteristics and an energy storage configuration model that integrates cluster structure location selection are constructed to maximize the efficiency of energy storage input and output. For the goal,the analytical method based on second-order cone relaxation is used to solve the optimization model of energy storage station location and capacity. The analysis of the calculation example shows that when considering the network constraints and the characteristics of power generation and consumption at the transmitting and receiving ends,the transmitting and receiving ends can use the coordinated configuration and operation of energy storage to increase the consumption rate of renewable energy and ensure the power consumption of the load.
作者 周毅 黄森 石少伟 李笑蓉 程瑜 ZHOU Yi;HUANG Sen;SHI Shaowei;LI Xiaorong;CHENG Yu(State Grid Jibei Electric Economic Research Institute,Beijing 100038,China;School of Electric and Electronic Engineering,North China Electric Power University,Beijing 102206,China)
出处 《电网与清洁能源》 北大核心 2022年第11期126-133,145,共9页 Power System and Clean Energy
基金 国家重点研发计划(2019YFE0118400) 国家电网公司科技项目(SGJBJY00GPJS2100025)。
关键词 高比例可再生能源系统 储能配置 分群结构优化 优化规划 二阶锥松弛 high renewable energy proportion system energy storage system planning cluster structure optimization optimal planning second-order cone relaxation
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