基于数据驱动的分布式光伏发电功率预测方法研究进展

Research Progress on Data-Driven Prediction Methods for Distributed Photovoltaic Power Generation

从综述的角度,以分布式光伏系统为对象,分析了功率预测技术的发展情况、存在的难点以及主要影响因素,梳理了应用数据驱动方法实现功率准确预测的技术路线。再以空间相关性、历史出力功率以及气象等影响因素为切入点,梳理了光伏系统数据驱动的功率预测研究现状,分析其相应的数据增强、时空图信息以及特征融合的手段,讨论了技术的优缺点。最后给出了功率预测数据驱动方法研究方向和发展建议。

From the perspective of overview,this paper examines the development status,existing difficulties,and main influencing factors of power prediction technology in distributed photovoltaic systems,and outlines the technical route for applying data-driven methods to achieve accurate power prediction.Starting from factors such as spatial correlation,historical output power,and meteorological factors,this paper reviews the current research status of data-driven power prediction in photovoltaic systems,analyzes the corresponding data enhancement,spatio-temporal map information,and feature fusion methods,and discusses the advantages and disadvantages of the technology.Finally,research directions and development suggestions for data-driven methods for power prediction are given.