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Appl. Sci. 2018, 8(1), 9; https://doi.org/10.3390/app8010009

Online Identification of Photovoltaic Source Parameters by Using a Genetic Algorithm

1
Dipartimento di Ingegneria dell’Informazione ed Elettrica e Matematica Applicata, Università degli Studi di Salerno, 84084-Fisciano, Italy
2
Consiglio Nazionale delle Ricerche, Istituto di Studi sui Sistemi Intelligenti per l’Automazione, 90146-Palermo, Italy
Current address: Via Giovanni Paolo II n.132-84084 Fisciano, Salerno, Italy.
*
Author to whom correspondence should be addressed.
Received: 26 November 2017 / Revised: 12 December 2017 / Accepted: 15 December 2017 / Published: 22 December 2017
(This article belongs to the Special Issue Computational Intelligence in Photovoltaic Systems)
View Full-Text   |   Download PDF [1895 KB, uploaded 22 December 2017]   |  

Abstract

In this paper, an efficient method for the online identification of the photovoltaic single-diode model parameters is proposed. The combination of a genetic algorithm with explicit equations allows obtaining precise results without the direct measurement of short circuit current and open circuit voltage that is typically used in offline identification methods. Since the proposed method requires only voltage and current values close to the maximum power point, it can be easily integrated into any photovoltaic system, and it operates online without compromising the power production. The proposed approach has been implemented and tested on an embedded system, and it exhibits a good performance for monitoring/diagnosis applications. View Full-Text
Keywords: single-diode photovoltaic model; online diagnosis; genetic algorithm; embedded systems single-diode photovoltaic model; online diagnosis; genetic algorithm; embedded systems
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Petrone, G.; Luna, M.; La Tona, G.; Di Piazza, M.C.; Spagnuolo, G. Online Identification of Photovoltaic Source Parameters by Using a Genetic Algorithm. Appl. Sci. 2018, 8, 9.

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