Hybrid Predictive Models for Accurate Forecasting in PV Systems

Hybrid Predictive Models for Accurate Forecasting in PV Systems

The accurate forecasting of energy production from renewable sources represents an important topic also looking at different national authorities that are starting to stimulate a greater responsibility towards plants using non-programmable renewables. In this paper the authors use advanced hybrid ev...

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Bibliographic Details
Main Authors: Marco Mussetta, Sonia Leva, Francesco Grimaccia, Emanuele Ogliari
Format: Article
Language:English
Published: MDPI AG 2013-04-01
Series:Energies
Subjects:
hybrid techniques
PV forecasting
artificial Intelligence
neural networks
Online Access:http://www.mdpi.com/1996-1073/6/4/1918
Description
Summary:The accurate forecasting of energy production from renewable sources represents an important topic also looking at different national authorities that are starting to stimulate a greater responsibility towards plants using non-programmable renewables. In this paper the authors use advanced hybrid evolutionary techniques of computational intelligence applied to photovoltaic systems forecasting, analyzing the predictions obtained by comparing different definitions of the forecasting error.
ISSN:1996-1073

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