基于熵权-TOPSIS法的风光柴储互补发电系统容量优化配置

高建强; 张浩; 危日光

doi:10.19805/j.cnki.jcspe.2025.230710

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基于熵权-TOPSIS法的风光柴储互补发电系统容量优化配置

综合能源系统 | 更新时间：2026-01-21

- 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
- 动力工程学报 2025年45卷第2期页码：300-306
- 作者机构：
  
  华北电力大学能源动力与机械工程学院,河北,保定,071003
- 作者简介：
  
  [ "高建强(1966—),男,河北定州人,教授,博士,研究方向为系统建模与仿真" ]
- 基金信息：
- DOI：10.19805/j.cnki.jcspe.2025.230710
  中图分类号： TM61;TM73
- 网络出版：2025-02-15，
  
  纸质出版：2025
- 稿件说明：
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高建强,张浩,危日光. 基于熵权-TOPSIS法的风光柴储互补发电系统容量优化配置动力工程学报, 2025, 45(2): 300-306 https://doi.

org/10.19805/j.cnki.jcspe.2025.230710
高建强,张浩,危日光. 基于熵权-TOPSIS法的风光柴储互补发电系统容量优化配置动力工程学报, 2025, 45(2): 300-306 https://doi. DOI： 10.19805/j.cnki.jcspe.2025.230710.

org/10.19805/j.cnki.jcspe.2025.230710 DOI：

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。

Abstract

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 1.169 04 million yuan.

关键词

Keywords

references

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