基于数据挖掘技术和聚类算法的线损模型研究  

Research on Line Loss Model Based on Data Mining Technology and Clustering Algorithm

作　　者：谢灵峰 XIE Jiongfeng(Guangdong Power Grid Co.,Ltd.,Qingyuan Power Supply Bureau,Qingyuan 511500)

机构地区：[1]广东电网有限责任公司清远供电局,广东清远511500

出　　处：《智能物联技术》2025年第1期102-105,共4页Technology of Io T& AI

摘　　要：随着电力行业的发展和人们生活水平的提高,对供电质量和电网性能的要求不断增加。线损作为评估电网质量的重要指标,管理和优化对电力行业的健康发展至关重要。为了有效提高线损管理,提出一种基于数据挖掘和聚类算法的线损预测方法。通过分析电网数据,采用模糊C均值聚类算法预测线损,以提高线损管理的效率和精度,从而降低线损率,提升电力企业的运营效率和盈利能力。With the development of the power industry and the improvement of people's living standards,the requirements for power supply quality and grid performance are constantly increasing.As an important indicator for evaluating the quality of the power grid,line loss management and optimization are crucial for the healthy development of the power industry.In order to effectively improve line loss management,this paper proposes a line loss prediction method based on data mining and clustering algorithms.By analyzing power grid data and using fuzzy C-means clustering algorithm for line loss prediction,the efficiency and accuracy of line loss management can be improved,thereby reducing the line loss rate and enhancing the operational efficiency and profitability of power enterprises.

关 键 词：数据挖掘 模糊C均值聚类算法 线损管理 线损预测 

分 类 号：TM73[电气工程—电力系统及自动化]