Forecast of solar energy resource by using neural network methods

被引：0

作者：

Fiorin, Daniel V. ^{[1
]}

Martins, Fernando R. ^{[2
]}

Schuch, Nelson J. ^{[1
]}

Pereira, Enio B. ^{[2
]}

机构：

[1] Inst Nacl Pesquisas Espaciais, Ctr Reg Sul Pesquisas Espaciais, Santa Maria, RS, Brazil

[2] Inst Nacl Pesquisas Espaciais, Ctr Ciencia Sistema Terrestre, Sao Jose Dos Campos, SP, Brazil

来源：

REVISTA BRASILEIRA DE ENSINO DE FISICA | 2011年 / 33卷 / 01期

关键词：

solar energy; artificial neural networks; atmospheric modeling; numeric mesoscale models; RADIATION; MODEL; MM5;

D O I：

暂无

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

This work aims at discussing the artificial neural networks (ANN) and some applications in renewable energy assessment. First, the paper describes the statistical relevance of this tool in different areas of knowledge and the main ANN concepts and configurations. Finally, the paper presents and discusses the use of ANN for the solar energy assessment in Brazil by using data collected in SONDA sites operated by the Center for Earth System Science of the Brazilian Institute for Space Research. The results show that ANN can provide reliable estimates with better performance than other statistical tools.

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页数：20

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