浙江电力2024，Vol.43Issue(4)：74-84,11.DOI:10.19585/j.zjdl.202404008
基于原型提取和聚类的光伏电站快速集群划分方法
A method for rapid cluster partitioning of photovoltaic plants based on prototype ex-traction and clustering
摘要
Abstract
The penetration rate of photovoltaic power generation keeps increasing.To address the issues of poor clus-ter partitioning and lengthy processing times for photovoltaic power station clusters,the paper proposes a method for rapid cluster partitioning method for photovoltaic(PV)plants based on prototype extraction and clustering.Firstly,photovoltaic data is preprocessed to eliminate differences in magnitude and dimensionality among data sets.Subse-quently,influential factors on photovoltaic output power are identified using the Pearson correlation coefficient method.Random sampling,k-means++,and an improved spectral clustering method are then employed for sam-pling,prototype extraction,and prototype clustering of PV plants,respectively.Building upon an enumeration ap-proach and hierarchical optimization,optimal hyperparameters for the aforementioned processes are determined.Fi-nally,various scenarios are set up for case study comparisons,calculating both intra-cluster and inter-cluster indi-cators as well as clustering time metrics.Through comprehensive analysis,the effectiveness of the proposed method in addressing the rapid clustering for large-scale PV plants is validated.关键词
光伏电站/改进谱聚类算法/原型聚类/Pearson相关系数Key words
photovoltaic power station/improved spectral clustering algorithm/prototype clustering/Pearson corre-lation coefficient引用本文复制引用
陈文进,杨晓丰,祁炜雯,王建军,赵峰,陈建国,王健..基于原型提取和聚类的光伏电站快速集群划分方法[J].浙江电力,2024,43(4):74-84,11.基金项目
国网浙江省电力有限公司科技项目(5211SX220001) （5211SX220001）
