Estimation of tilted solar irradiation using Artificial Neural Networks

被引：15

作者：

Notton, Gilles ^{[1
]}

Paoli, Christophe ^{[1
]}

Diaf, Said ^{[2
]}

机构：

[1] Univ Cors Pasquale Paoli, UMR CNRS 6134, Ctr Georges Peri, Route Sunguinaires, F-20000 Ajaccio, France

[2] Ctr Dev Energies Renouvelables, Algiers, 16340, Algeria

来源：

MEDITERRANEAN GREEN ENERGY FORUM 2013: PROCEEDINGS OF AN INTERNATIONAL CONFERENCE MGEF-13 | 2013年 / 42卷

关键词：

Solar radiation; Articial neural network; Model; Tilted planes; Global solar radiation; INCLINED SURFACES; MODELS; RADIATION; AJACCIO;

D O I：

10.1016/j.egypro.2013.11.003

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Calculation of solar global irradiation on tilted planes from only horizontal global one is particularly difficult when the time step is small. We used an Artificial Neural Network (ANN) to realize this conversion at an hourly and 10-min time step. The ANN is developed and optimized using five years of solar data. The accuracy is respectively for hourly and 10-min data of 6% and 9% for the RMSE and 3.5% and 5.5% for the RMAE i.e. similar or slightly lower than the errors obtained with conventional empirical correlations for hourly data. (C) 2010 The Authors. Published by Elsevier Ltd.

引用

页码：33 / 42

页数：10

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