Estimation of the energy of a PV generator using artificial neural network

被引：89

作者：

Almonacid, F. ^{[1
]}

Rus, C. ^{[1
]}

Perez, P. J. ^{[1
]}

Hontoria, L. ^{[1
]}

机构：

[1] Univ Jaen, Grp Invest & Desarrollo Energia Solar & Automat, Dpto Ingn Elect, EPS Jaen,EPS Linares, Jaen 23071, Spain

来源：

RENEWABLE ENERGY | 2009年 / 34卷 / 12期

关键词：

PV generator; Artificial neural network; MODULES;

D O I：

10.1016/j.renene.2009.05.020

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The integration of grid-connected photovoltaic (GCPVS) systems into urban buildings is very popular in industrialized countries. Many countries enhance the international collaboration efforts which accelerate the development and deployment of photovoltaic solar energy as a significant and sustainable renewable energy option. A previous method, based on artificial neural networks (ANNs), has been developed to electrical characterisation of PV modules. This method was able to generate V-1 curves of si-crystalline PV modules for any irradiance and module cell temperature. The results showed that the proposed ANN introduced a good accurate prediction for si-crystalline PV modules performance when compared with the measured values. Now, this method, based on ANNs, is going to be applied to obtain a suitable value of the power provided by a photovoltaic installation. Specifically this method is going to be applied to obtain the power provided by a particular installation, the "Univer generator", since modules used in these works were the same as the ones used in this photovoltaic generator. (C) 2009 Elsevier Ltd. All rights reserved.

引用

页码：2743 / 2750

页数：8

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