DocumentCode :
2235467
Title :
Solar irradiation forecasting using RBF networks for PV systems with storage
Author :
Ciabattoni, Lucio ; Ippoliti, Gianluca ; Longhi, Sauro ; Cavalletti, Matteo ; Rocchetti, Marco
Author_Institution :
Dipt. di Ing. dell´´Inf., Univ. Politec. delle Marche, Ancona, Italy
fYear :
2012
fDate :
19-21 March 2012
Firstpage :
699
Lastpage :
704
Abstract :
In this paper a Radial Basis Function (RBF) neural network is proposed to obtain the 24-hr forecast of the solar irradiation on the horizontal plane in the city of Ancona, Italy. This information is used to estimate the production of a PhotoVoltaic (PV) plant in order to provide the ´Gestore dei Servizi Energetici´ (the main italian provider of energy services) with the power production profile of the next day. The company Energy Resources SPA has experimentally tested the proposed solution by a 14 KWp PV plant and a lithium battery pack. The battery pack is used to store the exceding power produced or to supply the lack of power compared with the reference.
Keywords :
lithium; load forecasting; neural nets; photovoltaic power systems; power engineering computing; power supply quality; secondary cells; Ancona; Gestore dei Servizi Energetici; Italy; Li; RBF neural network; company energy resources SPA; lithium battery pack; photovoltaic plant; photovoltaic systems; power production profile; power supply; radial basis function; solar irradiation forecasting; time 24 hr; Artificial neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Technology (ICIT), 2012 IEEE International Conference on
Conference_Location :
Athens
Print_ISBN :
978-1-4673-0340-8
Type :
conf
DOI :
10.1109/ICIT.2012.6210020
Filename :
6210020
Link To Document :
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