电力工程技术2024，Vol.43Issue(4)：147-155,9.DOI:10.12158/j.2096-3203.2024.04.015
计及经济性和低碳性的光储充一体化电站多目标优化配置
Multi-objective optimization based capacity accommodation of PIS considering its ecomomic construction and low-carbon operation
摘要
Abstract
In order to explore the economic and carbon reduction benefits of photovoltaic-storage-charging integrated stations and achieve reasonable configuration of internal components,a multi-objective optimization configuration method for stations that takes into account economic and low-carbon aspects is proposed.Firstly,based on the functions and requirements of each module in the charging station,the sources of carbon emissions generated by station is explored,and a mathematical model for the cost and carbon emissions of each module in the station is established.Then,with the goal of minimizing the annual investment and operating cost of the system and carbon emissions,a multi-objective particle swarm optimization algorithm based on three-black-hole capturing strategy is used to optimize the configuration of various modules of stations in different load scenarios,and the optimal configuration plan for each component module of the station under three scenarios is obtained.The comparative results show that the method proposed in this article can effectively reduce the cost and carbon emissions during planning and operation,and improve the economic and environmental benefits of stations.Finally,the technique for order preference by similarity to ideal solution is used to provide a compromise optimization plan for the optimal scenario,which can provide reference for the current investment and construction of photovoltaic-storage-charging integrated stations.关键词
容量优化配置/车网互动/有序充放电/多目标优化/碳排放/逼近理想解排序法Key words
capacity optimization configuration/vehicle to grid/orderly charging and discharging/multi-objective optimization/carbon emission/technique for order preference by similarity to ideal solution method分类
信息技术与安全科学引用本文复制引用
程杉,刘延光,刘炜炜,王灿,李振兴..计及经济性和低碳性的光储充一体化电站多目标优化配置[J].电力工程技术,2024,43(4):147-155,9.基金项目
国家自然科学基金资助项目(52107108) 本文得到电力系统智能运行与安全防御宜昌市重点实验室开放基金(2020DLXY01)资助,谨此致谢! （52107108）
