可再生能源2013，Vol.31Issue(7)：1-5,5.
基于小波神经网络的光伏系统发电量预测
Generation forecasting for photovoltaic system based on wavelet neural networks
摘要
Abstract
The various factors that affect the power generation output of photovoltaic (PV) system are studied,and a model of generation forecasting of PV system based on wavelet neural networks (WNN)is built.The historical data such as generation output,ambient temperature,solar panel temperature and relative humidity under similar weather conditions are taken together as samples to train the model and to forecast power generation output.In this paper,the WNN model and BP neural networks model are compared and analyzed,the results show:the WNN model has fewer training times,faster convergence rate and higher prediction accuracy comparing with BP neural networks model.关键词
光伏系统/发电量预测/小波神经网络/BP神经网络Key words
photovoltaic system/generation forecasting/wavelet neural networks/BP neural networks分类
信息技术与安全科学引用本文复制引用
杨德全,王艳,焦彦军..基于小波神经网络的光伏系统发电量预测[J].可再生能源,2013,31(7):1-5,5.基金项目
中央高校基本科研业务启动费资助项目(10QG08). （10QG08）
