Modelling of sizing the photovoltaic system parameters using artificial neural network

被引：0
|
作者：
Mellit, A
Benghanem, M
Arab, AH
Guessoum, A
机构：
来源：
CCA 2003: PROCEEDINGS OF 2003 IEEE CONFERENCE ON CONTROL APPLICATIONS, VOLS 1 AND 2 | 2003年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The objective of this work is to use an Artificial Neural Network (ANN) to predict the sizing parameters of photovoltaic (PV) system with a minimum of input data. A neural network has been trained by using 54 known sizing parameter data corresponding to 54 locations. In this way the network was trained to accept and even handle a number of unusual cases. Known data were subsequently used to investigate the accuracy of prediction. Prediction with maximum deviation of 6% was obtained. This result indicates that the proposed method can successfully be used for the estimation of sizing parameters data for any locations.
引用
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页码：353 / 357
页数：5
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