Study of the Intelligent Behavior of a Maximum Photovoltaic Energy Tracking Fuzzy Controller

Gul Filiz Tchoketch Kebir, Cherif Larbes, Adrian Ilinca, Thameur Obeidi and Selma Tchoketch Kebir
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Gul Filiz Tchoketch Kebir: Wind Energy Research Laboratory, Université du Québec à Rimouski, 300, Allée des Ursulines, Rimouski, QC G5L 3A1, Canada
Cherif Larbes: Laboratoire des Dispositifs de Communication et de Conversion Photovoltaïque, Département d’Électronique, École Nationale Polytechnique, 10, Avenue Hassen Badi, El Harrach, Alger 16200, Algerie
Adrian Ilinca: Wind Energy Research Laboratory, Université du Québec à Rimouski, 300, Allée des Ursulines, Rimouski, QC G5L 3A1, Canada
Thameur Obeidi: Wind Energy Research Laboratory, Université du Québec à Rimouski, 300, Allée des Ursulines, Rimouski, QC G5L 3A1, Canada
Selma Tchoketch Kebir: Laboratoire des Dispositifs de Communication et de Conversion Photovoltaïque, Département d’Électronique, École Nationale Polytechnique, 10, Avenue Hassen Badi, El Harrach, Alger 16200, Algerie

Energies, 2018, vol. 11, issue 12, 1-20

Abstract: The Maximum Power Point Tracking (MPPT) strategy is commonly used to maximize the produced power from photovoltaic generators. In this paper, we proposed a control method with a fuzzy logic approach that offers significantly high performance to get a maximum power output tracking, which entails a maximum speed of power achievement, a good stability, and a high robustness. We use a fuzzy controller, which is based on a special choice of a combination of inputs and outputs. The choice of inputs and outputs, as well as fuzzy rules, was based on the principles of mathematical analysis of the derived functions (slope) for the purpose of finding the optimum. Also, we have proved that we can achieve the best results and answers from the system photovoltaic (PV) with the simplest fuzzy model possible by using only 3 sets of linguistic variables to decompose the membership functions of the inputs and outputs of the fuzzy controller. We compare this powerful controller with conventional perturb and observe (P&O) controllers. Then, we make use of a Matlab-Simulink ® model to simulate the behavior of the PV generator and power converter, voltage, and current, using both the P&O and our fuzzy logic-based controller. Relative performances are analyzed and compared under different scenarios for fixed or varied climatic conditions.

Keywords: fuzzy logic controller; MPPT: maximum power point tracking; photovoltaic system; step-up boost converter (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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