PV array output power forecasting based on similar day and RBFNN

doi:10.3969/j.issn.1006-6047.2013.01.019

	PV array output power forecasting based on similar day and RBFNN
	Wang, Xiaolan1,2 ; Ge, Pengjiang 1
	2013
发表期刊	Dianli Zidonghua Shebei/Electric Power Automation Equipment
ISSN	10066047
卷号	33 期号:1 页码:100-103+109
摘要	As the solar radiation time, solar radiation intensity and air temperature are the main influencing factors of PV array output power and there is strong correlation in output power among the similar days, a forecasting model of PV array output power is designed based on similar days and RBFNN(Radial Basis Function Neural Network), which takes the difference of meteorological feature vector between the nearest similar day and the day to be forecasted as the input variable of RBFNN and its output as the forecasted PV array output power. The proposed model is trained and verified with the measured power dada of a PV array in Northwest China. Its mean absolute percentage error obtained is 13.82% and its root mean square error is 0.4054, showing its high accuracy.
关键词	Atmospheric temperature Forecasting Functions Mean square error Models Neural networks Photovoltaic cells Solar radiation Forecasting modeling Mean absolute percentage error Output power PV arrays Rbfnn(radial basis function neural network) Root mean square errors Similar day Solar radiation intensity
DOI	10.3969/j.issn.1006-6047.2013.01.019
收录类别	EI
语种	中文
出版者	Electric Power Automation Equipment Press
EI入藏号	20130816047126
EI主题词	Radial basis function networks
EI分类号	443.1 Atmospheric Properties - 657.1 Solar Energy and Phenomena - 921 Mathematics - 922.2 Mathematical Statistics
来源库	Compendex
分类代码	443.1 Atmospheric Properties - 657.1 Solar Energy and Phenomena - 921 Mathematics - 922.2 Mathematical Statistics
引用统计	无
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/113697
专题	电气工程与信息工程学院
作者单位	1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China; 2.Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou 730050, China
第一作者单位	兰州理工大学
第一作者的第一单位	兰州理工大学
推荐引用方式 GB/T 7714	Wang, Xiaolan,Ge, Pengjiang. PV array output power forecasting based on similar day and RBFNN[J]. Dianli Zidonghua Shebei/Electric Power Automation Equipment,2013,33(1):100-103+109.
APA	Wang, Xiaolan,&Ge, Pengjiang.(2013).PV array output power forecasting based on similar day and RBFNN.Dianli Zidonghua Shebei/Electric Power Automation Equipment,33(1),100-103+109.
MLA	Wang, Xiaolan,et al."PV array output power forecasting based on similar day and RBFNN".Dianli Zidonghua Shebei/Electric Power Automation Equipment 33.1(2013):100-103+109.