基于最小二乘法–遗传算法和改进可变模糊集的电能质量综合评估

肖白; 黄丽婷; 焦明曦; 杨宁; 王大亮; 董光德

doi:10.19725/j.cnki.1007-2322.2024.0166

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基于最小二乘法–遗传算法和改进可变模糊集的电能质量综合评估

智能电网 | 更新时间：2026-10-19

- 基于最小二乘法–遗传算法和改进可变模糊集的电能质量综合评估
- Comprehensive Evaluation of Power Quality Based on LSM-GA and Improved VFS
- 现代电力 2026年43卷第5期页码：801-810
- 作者机构：
  
  1. 现代电力系统仿真控制与绿色电能新技术教育部重点实验室(东北电力大学),吉林市,吉林省,132012
  2. 国网吉林省电力有限公司长春供电公司,吉林省,长春市,130021
  3. 国网重庆市电力公司电力科学研究院, 重庆市渝北区,401123
- 作者简介：
  
  肖白(1973)，男，通信作者，博士，教授，硕士生导师，研究方向为电力系统规划与运行优化、空间电力负荷预测、多能互补协调发电、电能质量分析与治理，E-mail：xbxiaobai@126.com
  黄丽婷(1998)，女，硕士，研究方向为电能质量综合评估及治理，E-mail：2898939783@qq.com
  焦明曦(1986)，男，硕士，高级工程师，研究方向为电力系统规划与运行优化，E-mail：247700218@qq.com
  杨宁(2000)，女，硕士，研究方向为电价套餐设计，E-mail：yangning20000820@163.com
  王大亮(1981)，男，硕士，高级工程师，研究方向为电网调度、自动化及电力通信，E-mail：18136195@qq.com
  董光德(1987)，男，硕士，高级工程师，研究方向为电力系统分析、电能质量评估、综合能源消纳，E-mail：1012423917@qq.com
- 基金信息：
  
  国家重点研发计划项目(2017YFB0902205);吉林省产业创新专项基金项目(2019C058-7);国网重庆市电力公司科技项目(SGCQDK00DWJS2100205)。
- DOI：10.19725/j.cnki.1007-2322.2024.0166
  中图分类号： 5
- 纸质出版：2026
- 稿件说明：
移动端阅览
肖白, 黄丽婷, 焦明曦, 等. 基于最小二乘法–遗传算法和改进可变模糊集的电能质量综合评估[J]. 现代电力, 2026,43(5):801-810.

XIAO Bai, HUANG Liting, JIAO Mingxi, et al. Comprehensive Evaluation of Power Quality Based on LSM-GA and Improved VFS[J]. 2026, 43(5): 801-810.
肖白, 黄丽婷, 焦明曦, 等. 基于最小二乘法–遗传算法和改进可变模糊集的电能质量综合评估[J]. 现代电力, 2026,43(5):801-810. DOI： 10.19725/j.cnki.1007-2322.2024.0166.

XIAO Bai, HUANG Liting, JIAO Mingxi, et al. Comprehensive Evaluation of Power Quality Based on LSM-GA and Improved VFS[J]. 2026, 43(5): 801-810. DOI： 10.19725/j.cnki.1007-2322.2024.0166.

摘要

针对电能质量综合评估中存在的评估指标及指标实测数据处理的不确定性问题，提出一种基于最小二乘法–遗传算法(least squares method-genetic algorithm，LSM-GA)和改进可变模糊集(variable fuzzy set，VFS)的电能质量综合评估方法。首先，建立电能质量指标体系。其次，采用序关系分析法(order relation analysis method，G1)计算各个电能质量指标的主观权重，采用基于指标相关性的权重确定(criteria importance through intercriteria correlation，CRITIC)法计算各个电能质量指标的客观权重。再次，利用LSM思想对电能质量指标权重进行建模，并运用遗传算法(genetic algorithm，GA)求解权重模型，得到各个电能质量评估指标的综合优化权重，以避免单一赋权方法的不足。然后，利用集对分析(set pair analysis，SPA)来改进VFS，以此避免差异度函数的主观随意性，并构建基于LSM-GA和改进VFS的电能质量综合评估模型。最后，算例结果证明了该方法的有效性和可行性。

Abstract

To address the uncertainty associated with evaluation indices and measured data processing in the comprehensive evaluation of power quality

a comprehensive evaluation method of power quality based on the least squares method (LSM)

genetic algorithm (GA)

and improved variable fuzzy set theory (VFS) is proposed. First

the power quality index system is established. Second

the subjective weight of each power quality index is calculated using the order relation analysis method (G1)

while the objective weight of each power quality index is calculated using the criteria importance through intercriteria correlation (CRITIC) method. Third

LSM is employed to model the power quality index weights

and the GA is applied to solve the weight model. In this way

the comprehensive optimal weight of each power quality evaluation index is obtained

which avoids the limitations of single weighting methods. Subsequently

the set pair analysis theory (SPA) is used to improve the VFS

thereby avoiding the subjective randomness of the difference function. A comprehensive evaluation model of power quality based on LSM-GA and improved VFS is constructed. Finally

the results of the example verify the effectiveness and feasibility of the proposed method.

关键词

Keywords

references

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