山东电力技术2026，Vol.53Issue(6)：23-34,12.DOI:10.20097/j.cnki.issn1007-9904.250148
考虑分布式光伏电站时空相关特性的集群功率预测
Cluster Power Prediction Considering Spatiotemporal Correlation Characteristics of Distributed Photovoltaic Power Plants
摘要
Abstract
The rapid popularization of distributed photovoltaic(PV)power generation systems has made accurate power prediction particularly critical for stable grid operation and energy dispatch.However,compared with a single PV power plant,the prediction of distributed PV clusters is much more difficult because of the complex spatio-temporal correlations among the various sites,which are difficult to be effectively modeled by traditional methods.In order to improve the accuracy of cluster prediction,this paper proposes a method for distributed PV cluster power forecasting that incorporates representative station selection and Spatio-Temporal Graph Convolutional Networks(STGCN).Firstly,the spatio-temporal correlation among distributed PV stations is considered.After constructing the comprehensive correlation coefficients,the output power of each distributed PV station is taken as a distinct feature affecting the cluster power.Representative stations are selected based on the Maximum Relevance Minimum Redundancy(mRMR)feature selection method.Then the Hiking Optimization Algorithm(HOA)is introduced to portray the contribution of the output power from each representative station to the cluster power,enabling the calculation of optimal weight allocation for each representative power station.Finally,a spatio-temporal graph convolutional network is constructed using the historical data from the representative stations to realize the feature extraction of complex spatio-temporal data among PV stations.After outputting the power prediction data of each representative station,the cluster prediction power is obtained through optimal weight calculations.Example calculations are conducted in two PV clusters in S1 and S2 provinces to prove the effectiveness of the proposed method in cluster prediction.关键词
光伏预测/分布式光伏集群/代表电站选取/徒步优化算法/时空图卷积网络Key words
photovoltaic forecast/distributed photovoltaic cluster/selection of representative power stations/hiking optimization algorithm/spatiotemporal graph convolutional network分类
信息技术与安全科学引用本文复制引用
白雪峰,周颖,徐靖,田传波,杜苁聪,王连辉..考虑分布式光伏电站时空相关特性的集群功率预测[J].山东电力技术,2026,53(6):23-34,12.基金项目
国家电网有限公司总部科技项目"高比例分布式光伏台区电能质量主动感知与协同控制技术研究与应用"(5400-202421209A-1-1-ZN).Science and Technology Project of State Grid Corporation of China"Research and Application of Active Perception and Collaborative Control Technology for Power Quality in High Proportion Distributed Photovoltaic Power Stations"(5400-202421209A-1-1-ZN). （5400-202421209A-1-1-ZN）
