电力系统自动化2024，Vol.48Issue(3)：42-50,9.DOI:10.7500/AEPS20230518009
分布式光伏集群功率短期预测的空间互补特性初探
Preliminary Study on Spatial Complementarity Characteristics of Short-term Power Prediction for Distributed Photovoltaic Clusters
摘要
Abstract
With the rapid growth of distributed photovoltaic(PV)installed capacity,the impact of power prediction for distributed PV clusters on grid dispatch is becoming increasingly significant.There are three technical routes for power prediction of distributed PV clusters,i.e.,accumulation before prediction,prediction before accumulation and clustering before prediction.Through experiments on a dataset of over 600 distributed PV sites,the spatial complementarity is found in the power prediction for distributed PV clusters,whereby the prediction errors of the three cluster prediction routes are lower than the average prediction error of a single site.To explore the generation mechanism and influencing factors of the spatial complementarity,this paper first categorizes it into two types of spatial complementarity characteristics,namely power curve complementarity and prediction error complementarity,based on the mechanism analysis.Secondly,the concept of spatial complementarity coefficient is proposed to quantitatively evaluate the complementary effect.Finally,the effects of cluster scale,distribution range,weather type and number of clusters on the spatial complementarity characteristics are explored.The results show that the two types of spatial complementarity characteristics have significant effects on improving the short-term power prediction accuracy of distributed PV clusters,with prediction error complementarity superior to power curve complementarity.The research results can provide a basis for the division of distributed PV clusters and contribute to achieving more efficient and accurate power prediction.关键词
分布式光伏/功率预测/集群/空间互补/误差Key words
distributed photovoltaic(PV)/power prediction/cluster/spatial complementarity/error引用本文复制引用
阮呈隆,李康平,李正辉,黄淳驿..分布式光伏集群功率短期预测的空间互补特性初探[J].电力系统自动化,2024,48(3):42-50,9.基金项目
国家自然科学基金青年基金资助项目(52107103) （52107103）
新型电力系统运行与控制全国重点实验室开放基金课题(SKLD22KM13). This work is supported by National Natural Science Foundation of China(No.52107103)and the State Key Laboratory of Power System Operation and Control(No.SKLD22KM13). （SKLD22KM13）
