电力系统保护与控制2025，Vol.53Issue(12)：165-172,8.DOI:10.19783/j.cnki.pspc.241078
基于K均值聚类的光伏集群发电功率超短期预测研究
Research on ultra-short-term power forecasting of photovoltaic clusters based on K-means clustering
摘要
Abstract
Accurate ultra-short-term power forecasting for distributed photovoltaic(PV)systems is critically important for their integration into the power grid.However,current forecasting efforts face challenges such as insufficient accuracy in meteorological data and incomplete power data.To address these issues,this paper proposes a regional PV forecasting method based on cluster partitioning.First,two metrics,i.e.,forward/reverse electricity ratio and the ratio of power median to mean,are selected as the basis for distance calculation.The K-means clustering algorithm is then used to divide all PV power plants in the region into clusters.Based on this clustering,PV power forecasting is carried out for each cluster,and the combined results from all clusters are used to produce a regional forecast for distributed PV output.Finally,data from a distributed PV power plant in a specific region is used for verification.The results show that the proposed algorithm has high accuracy and can meet the practical requirements of field applications.关键词
分布式光伏/集群划分/功率预测/K均值聚类/长短期记忆网络Key words
distributed photovoltaics/cluster partitioning/power forecasting/K-means clustering/long short-term memory network引用本文复制引用
文贤馗,何明君,张俊玮,周科,蔡永翔,张凡..基于K均值聚类的光伏集群发电功率超短期预测研究[J].电力系统保护与控制,2025,53(12):165-172,8.基金项目
This work is supported by the Science and Technology Plan Program of Guizhou Province(No.CXTD[2022]008). 贵州省科技计划项目资助(CXTD[2022]008) （No.CXTD[2022]008）
南方电网科技项目资助(GZKJXM20222258) （GZKJXM20222258）
