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Artificial Intelligence Technics Applied to Analisys of Photovoltaic Energy Systems

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4 Author(s)
Rampinelli, G.A. ; Lab. de Energia Solar, Univ. Fed. do Rio Grande do Sul, Porto Alegre, Brazil ; Teyra, M.A.A. ; Krenzinger, A. ; Prieb, C.W.M.

This paper presents a procedure to determine the energetic behavior of photovoltaic systems through genetic algorithms and artificial neural networks. The method divides the I-V Curve of the photovoltaic generator in three regions. The best results are achieved for the region around the maximum power point, which can be advantageous for grid-connected systems. The method allows determining the energy delivered by the system and the inverter performance from a few experimental data. The output is a vector comprising the DC power, the maximum power point tracker efficiency, the inverter efficiency and the AC power.

Published in:

Latin America Transactions, IEEE (Revista IEEE America Latina)  (Volume:8 ,  Issue: 5 )

Date of Publication:

Sept. 2010

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