分布式能源2025，Vol.10Issue(1)：62-71,10.DOI:10.16513/j.2096-2185.DE.(2025)010-01-0062-10
基于多源预报动态聚类的分布式光伏集群短期功率预测
Short-Term Power Prediction of Distributed Photovoltaic Clusters Based on Dynamic Clustering of Multi-Source Forecasts
摘要
Abstract
Accurate power forecasting for distributed photovoltaic(PV)power plants is essential to address output uncertainty.Distributed PV is characterized by a large number and geographical distribution,if a power prediction system is configured for each distributed PV plant,it will bring high operating costs.For this reason,a short-term power prediction method for distributed PV clusters based on dynamic clustering of multi-source forecasts is proposed.Firstly,the local public weather forecast information of the forecast day is digitally encoded,and the encoded information is fused with the numerical weather prediction(NWP)data of the region through an improved self-encoder for feature extraction to achieve the fusion of multi-source forecast data;Secondly,the fused features of the multi-source forecast data of the forecast day are taken as the clustering features,and self-organizing mapping(SOM)network clustering is utilized to realize the dynamic division of the clusters;Finally,the clusters are predicted by the 1D convolutional neural network(1DCNN),and the cluster prediction results are accumulated to achieve the power prediction of regional distributed photovoltaic.The results show that the proposed method can obtain more accurate and reliable prediction.关键词
分布式光伏集群/神经网络/动态聚类/短期功率预测Key words
distributed photovoltaic clusters/neural networks/dynamic clustering/short-term power prediction分类
能源与动力引用本文复制引用
赵雪锋,张宇宁,詹巍,李明烜,李艳军,杨锡运..基于多源预报动态聚类的分布式光伏集群短期功率预测[J].分布式能源,2025,10(1):62-71,10.基金项目
国家电投集团四川电力有限公司科技项目(XNNY-WW-KJ-2021-16) （XNNY-WW-KJ-2021-16）
四川省科技计划重点研发项目(2023YFG0108) The work is supported by Science and Technology Project of State Power Investment Group Sichuan Electric Power Co.,Ltd.(XNNY-WW-KJ-2021-16) （2023YFG0108）
Key R&D Project of Sichuan Science and Technology Program(2023YFG0108) （2023YFG0108）
