南方电网技术2025，Vol.19Issue(1)：41-50,62,11.DOI:10.13648/j.cnki.issn1674-0629.2025.01.005
考虑负荷分类增长的多目标光伏选址定容双层多阶段规划
Bi-Level Multi-Stage Planning for Multi-Objective Photovoltaic Siting and Sizing Considering Load Classification Growth
摘要
Abstract
With the increasing scale of distributed photovoltaic connected to the distribution network,conducting research on distributed photovoltaic siting and sizing is of great significance for improving the economy and security of the distribution network.Currently,most research on photovoltaic siting and sizing planning adopts conventional single period programming method for problem modeling,ignoring the medium-and long-term loads growth property of the distribution network,which will have a negative impact on the actual application effect of the model.Therefore,a bi-level multi-stage programming model for multi-objective photovoltaic siting and sizing planning that considers load classification growth is proposed.Firstly,the dynamic time warping(DTW)and LightGBM algorithm are combined to achieve classification and prediction of medium-and long-term loads.Then,a two-stage dynamic planning model is constructed for multi-objective photovoltaic siting and sizing planning considering load clas-sification growth,and the multi-objective bi-level crisscross optimization algorithm(MOBL-CSO)is introduced for solving.The experimental results in the modified IEEE 33-bus system indicate that the proposed scheme can comprehensively consider the load changes throughout the entire planning period for optimization,and can obtain a photovoltaic siting and sizing planning scheme that is more long-term safe and economic compared to traditional methods.关键词
分布式光伏/负荷增长/选址定容/配电网/多目标优化/双层多阶段规划/纵横交叉算法Key words
distributed PV/load growth/siting and sizing/distribution network/multi-objective optimization/bi-level multi-stage planning/crisscross optimization algorithm分类
动力与电气工程引用本文复制引用
杨毅,王明深,庄舒仪,朱继忠,陈一熙,曾琮,文淅宇..考虑负荷分类增长的多目标光伏选址定容双层多阶段规划[J].南方电网技术,2025,19(1):41-50,62,11.基金项目
国家自然科学基金资助项目(52177087) （52177087）
国网江苏省电力有限公司科技项目(J2022067).Supported by the National Natural Science Foundation of China(52177087) （J2022067）
the Science and Technology Project of State Grid Jiangsu Electric Power Co.,Ltd.(J2022067). （J2022067）
