电力系统自动化2026，Vol.50Issue(2)：93-102,10.DOI:10.7500/AEPS20250509007
基于相似云况匹配的分布式光伏集群功率概率预测方法
Probabilistic Power Forecasting Method for Distributed Photovoltaic Clusters Based on Similar Cloud Condition Matching
摘要
Abstract
Distributed photovoltaic(PV)systems lack on-site meteorological measurements,while the cost of acquiring large-scale and high-resolution numerical weather prediction(NWP)data is very high,which makes it difficult for existing power forecasting methods for centralized photovoltaics to be applicable.Satellite cloud images,offering wide-area,high-resolution cloud observations at a low cost,which is expected to become an important source of meteorological information to solve this problem.Therefore,this paper proposes a probabilistic power forecasting method for distributed PV clusters based on similar cloud condition matching.First,an optical-flow-enhanced 3-dimensional convolutional neural network(3D-CNN)is constructed to forecast future satellite cloud images.By incorporating a physical consistency loss,the model is guided to focus on the dynamic evolution of cloud structures,thereby improving the physical plausibility of the forecasting results.Secondly,a cloud condition matching method is introduced,by searching for the cloud conditions that are most similar to the forecasting period in history,the corresponding photovoltaic power is extracted as input features for subsequent power forecasting.Finally,the common information such as similar historical power and measured PV power at adjacent times will be combined as inputs for the spline quantile regression model to achieve accurate probabilistic forecasting of PV power.Case studies are conducted on a large-scale real dataset containing over 600 distributed PV sites,and the results show that the proposed method shows significant improvement compared to classical kernel density estimation methods in terms of the continuous ranked probability score index.关键词
分布式光伏/卫星云图/数值天气预报/气象信息/功率概率预测/卷积神经网络/云况匹配Key words
distributed photovoltaic/satellite cloud image/numerical weather prediction(NWP)/meteorological information/probabilistic power forecasting/convolutional neural network(CNN)/cloud condition matching引用本文复制引用
龚明凯,李康平,李正辉,黄淳驿..基于相似云况匹配的分布式光伏集群功率概率预测方法[J].电力系统自动化,2026,50(2):93-102,10.基金项目
国家重点研发计划政府间国际科技创新合作重点专项(2024YFE0106900) （2024YFE0106900）
上海市"科技创新行动计划"软科学研究项目(25692109700). This work is supported by National Key R&D Program of China(No.2024YFE0106900)and Shanghai"Science and Technology Innovation Action Plan"Soft Science Research Project(No.25692109700). （25692109700）
