Title :
Smart diagnosis algorithm of the open-circuit fault in a photovoltaic generator
Author :
Rezgui, Wail ; Mouss, Nadia Kinza ; Mouss, Leila-Hayet ; Mouss, Mohamed Djamel ; Amirat, Yassine ; Benbouzid, Mohamed
Author_Institution :
LAP-Lab., Univ. of Batna, Batna, Algeria
Abstract :
This article proposed a new smart diagnosis algorithm of the open-circuit fault in a PV generator. For the faults conventional diagnosis, it used the analysis of the actual operation parameters of the PV generator. For the faults smart diagnosis, it based on the optimization of SVM technique by the neural network for the classification of observations located on its margin. The resulting algorithm can ensure a better monitoring function of the open-circuit fault within the PV generator, with a high classification rate and a low error rate.
Keywords :
fault diagnosis; neural nets; optimisation; photovoltaic power systems; power engineering computing; power generation faults; support vector machines; SVM technique optimization; error rate; faults conventional diagnosis; monitoring function; neural network; observation classification; open circuit fault; photovoltaic generator; smart diagnosis algorithm; Artificial neural networks; Classification algorithms; Conferences; Generators; Photovoltaic systems; Support vector machines; Diagnosis; NN; Open-circuit fault; PV generator; SVM;
Conference_Titel :
Control, Engineering & Information Technology (CEIT), 2015 3rd International Conference on
Conference_Location :
Tlemcen
DOI :
10.1109/CEIT.2015.7233125