基于熵权-TOPSIS法的风光柴储互补发电系统容量优化配置  

Capacity Optimization of Wind-Solar-Diesel-Storage Complementary Power Generation System Based on Entropy Weight-TOPSIS Method

作　　者：高建强[1] 张浩 危日光[1] GAO Jianqiang;ZHANG Hao;WEI Riguang(School of Energy,Power and Mechanical Engineering,North China Electric Power University,Baoding 071003,Hebei Province,China)

机构地区：[1]华北电力大学能源动力与机械工程学院,河北保定071003

出　　处：《动力工程学报》2025年第2期300-306,共7页Journal of Chinese Society of Power Engineering

摘　　要：以某地区风光柴储互补发电系统为研究对象,将系统总成本和负荷缺电率作为优化目标,建立容量优化配置模型。采用多目标灰狼算法(MOGWO)对模型进行优化,将优化结果与多目标粒子群算法(MOPSO)的优化结果进行对比。同时,采用熵权-优劣解距离(TOPSIS)多目标决策法对优化解集进行筛选,降低了主观因素对权重系数的影响,增强了最优方案的合理性。结果表明:与MOPSO相比,MOGWO优化精度更高;在算例分析中,系统最优配置方案为风力发电机37台,光伏电池836块,柴油发电机5台,蓄电池531块,系统总成本116.904万元。A capacity optimization configuration model was established for a wind-solar-diesel-storage complementary power generation system in a certain region,with the total system cost and load power deficit rate being the optimization objectives.The model was optimized using the multi-objective grey wolf optimizer(MOGWO),and the optimization results were compared with that of the multi-objective particle swarm optimizer(MOPSO).Additionally,the entropy weight-TOPSIS multi-objective decision-making method was employed to screen the optimized solution set,which was aimed at reducing the impact of subjective factors on the weight coefficients and enhancing the rationality of the optimal solution.Results show that the optimization accuracy of MOGWO surpasses that of MOPSO.In the example analysis,the optimal system configuration is 37 wind turbines,836 solar panels,5 diesel generators,and 531 batteries,with a total system cost of 1.16904 million yuan.

关 键 词：风光柴储互补发电系统 容量配置 熵权-TOPSIS法 多目标灰狼算法 

分 类 号：TM715[电气工程—电力系统及自动化]