Application of Machine Learning in Photovoltaic Power Generation Prediction
Photovoltaic power generation has typical characteristics of intermittency,randomness,and uncertainty.An accurate photovoltaic power generation prediction model is essential for ensuring power balance,optimizing mode arrangements,and pro-moting new energy consumption.Machine learning can form predictions and judgments by learning a large amount of existing data,and can explore the intrinsic value of the data,achieving rich results in the field of photovoltaic power generation.This arti-cle provides a framework for predicting photovoltaic power generation based on machine learning,with a focus on analyzing five types of photovoltaic power generation prediction methods:traditional machine learning models,deep learning models,combina-torial ensemble learning models,online learning models,and physical data joint driving models.And research recommendations are provided for each type of method.
machine learningphotovoltaic power generation predictionsmall sample learningonline learningintegrated learning
NETL
NSTL
万方数据
