摘要
石油、天然气、和煤炭等化石燃料日益枯竭及经济快速发展对能源需求日益增加的矛盾,使得新型能源的开发应用受到了越来越广泛的关注。针对如何提高太阳能光伏发电量问题,采用小波神经网络建立独立光伏发电量预测模型,解决提高太阳能光伏发电效率问题。并通过将BP神经网络算法及小波神经网络发电量预测模型算法[5]对比得出小波神经网络发电量预测模型算法的优越性。
The contradiction between the depletion of fossil fuels such as petroleum,natural gas,coal and the increasing demand for energy due to the rapid economic development has caused the development and application of new energy sources to receive more and more attention.Aiming at how to improve the solar photovoltaic power generation,an independent photovoltaic power generation forecasting model based on wavelet neural network is established to solve the problem of improving the efficiency of solar photovoltaic power generation[9].By comparing the BP neural network algorithm with the wavelet neural network algorithm,the superiority of the wavelet neural network algorithm is obtained[10].
作者
何韦玲
He Wei-ling(Jiangxi New Energy Technology and Equipment Engineering Research Center ofEast China University of Technology,Jiangxi Nanchang 330013;Software College of Jiangxi AheadUniversity,Jiangxi Nanchang 330041)
出处
《电子质量》
2019年第4期61-64,共4页
Electronics Quality
关键词
独立光伏
小波
神经网络
预测
independent photovoltaic
wavelet
neural network
prediction
