南方电网技术2026，Vol.20Issue(7)：46-57,12.DOI:10.13648/j.cnki.issn1674-0629.2026.07.005
基于奇异谱分析和改进密度峰值聚类算法的电力负荷曲线聚类方法
Power Load Curve Clustering Method Based on Singular Spectrum Analysis and Improved Density Peak Clustering Algorithm
摘要
Abstract
To address the misclassification issues in existing density peak clustering algorithms caused by significant local fluctuations in data or uneven distribution of load categories,a power load curve clustering method based on singular spectrum analysis and improved density peak clustering algorithm is proposed.Firstly,singular spectrum analysis is employed to decompose the original power load data into a low-frequency component containing the main contour information and a high-frequency component represent-ing noise.Secondly,the local density of the density peak clustering algorithm is redefined by integrating the ideas of K-nearest neighbors and natural nearest neighbors,followed by clustering the low-frequency component.Finally,applied to real-world power load datasets,the proposed method is compared with other clustering algorithms,and case study results validate its effectiveness in real data.关键词
电力负荷曲线聚类/奇异谱分析/密度峰值聚类/智能电网/数据驱动Key words
power load curve clustering/singular spectrum analysis/density peak clustering/smart grid/data driven分类
信息技术与安全科学引用本文复制引用
赵俊,李鹏,李文超,苏适,梁俊宇..基于奇异谱分析和改进密度峰值聚类算法的电力负荷曲线聚类方法[J].南方电网技术,2026,20(7):46-57,12.基金项目
国家自然科学基金资助项目(62163036) （62163036）
云南省科技计划重大专项(202302AF080006) （202302AF080006）
云南省教育厅科学研究基金资助项目(2025Y0152) （2025Y0152）
云南大学第四届专业学位研究生实践创新项目(ZC-24248916). Supported by the National Natural Science Foundation of China(62163036) （ZC-24248916）
the Yunnan Science and Technology Major Program(202302AF080006) （202302AF080006）
the Scientific Research Fund of Yunnan Education Department(2025Y0152) （2025Y0152）
the Fourth Practical Innovation Project of Postgraduate Students in the Professional Degree of Yunnan University(ZC-24248916). （ZC-24248916）
