[ Comparaison du contrôleur flou Takagi-Sugeno et de la commande "P & O" pour l'extraction de la puissance maximale d'un système photovoltaïque ]
Volume 10, Issue 1, January 2015, Pages 192–206
M. Ajaamoum1, M. Kourchi2, B. Bouachrine3, Ahmed Ihlal4, and Lahoucine Bouhouch5
1 ERTAIER, ESTA, Université Ibn Zohr, BP 33/S, 80050 Agadir, Maroc
2 ERTAIER, ESTA, Université Ibn Zohr, BP 33/S, 80050 Agadir, Maroc
3 ERTAIER, ESTA, Université Ibn Zohr, BP 33/S, 80050 Agadir, Maroc
4 Faculté des Sciences, Université Ibn Zohr, B.P 8106, 80060 Agadir, Maroc
5 ERTAIER, ESTA, Université Ibn Zohr, BP 33/S, 80050 Agadir, Maroc
Original language: French
Copyright © 2015 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The maximum power point tracking (MPPT) plays a very important role in obtaining the maximum power of a solar panel because it ensures optimal operation of a photovoltaic system, regardless the conditions of irradiation and temperature. In this paper, we will introduce, a technique for improving and optimising the performances of a control system consisting of a photovoltaic panel, a buck converter and a load. This control is carried out by implementing two techniques of tracking the maximum power point (MPP). The first one, is based on the fuzzy logic control Takagi-Sugeno type ("TS fuzzy"), whereas the second uses the "Perturb and Observe" algorithm (P & O). Simulations of different parts of the system have been developed under Matlab / Simulink, enabling a comparison between the performances of the two controllers studied: "P&O" and "TS fuzzy". Both algorithms of command MPPT associated to these techniques are tested under the weather conditions of Agadir city located in the South of Morocco. So, the results obtained under various operating conditions, show a significant improvement in the performances of MPPT control of a photovoltaic system using the fuzzy logic controller.
Author Keywords: Photovoltaic, MPPT controller, Buck converter, ", Perturb and Observe", , Fuzzy Logic.
Volume 10, Issue 1, January 2015, Pages 192–206
M. Ajaamoum1, M. Kourchi2, B. Bouachrine3, Ahmed Ihlal4, and Lahoucine Bouhouch5
1 ERTAIER, ESTA, Université Ibn Zohr, BP 33/S, 80050 Agadir, Maroc
2 ERTAIER, ESTA, Université Ibn Zohr, BP 33/S, 80050 Agadir, Maroc
3 ERTAIER, ESTA, Université Ibn Zohr, BP 33/S, 80050 Agadir, Maroc
4 Faculté des Sciences, Université Ibn Zohr, B.P 8106, 80060 Agadir, Maroc
5 ERTAIER, ESTA, Université Ibn Zohr, BP 33/S, 80050 Agadir, Maroc
Original language: French
Copyright © 2015 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
The maximum power point tracking (MPPT) plays a very important role in obtaining the maximum power of a solar panel because it ensures optimal operation of a photovoltaic system, regardless the conditions of irradiation and temperature. In this paper, we will introduce, a technique for improving and optimising the performances of a control system consisting of a photovoltaic panel, a buck converter and a load. This control is carried out by implementing two techniques of tracking the maximum power point (MPP). The first one, is based on the fuzzy logic control Takagi-Sugeno type ("TS fuzzy"), whereas the second uses the "Perturb and Observe" algorithm (P & O). Simulations of different parts of the system have been developed under Matlab / Simulink, enabling a comparison between the performances of the two controllers studied: "P&O" and "TS fuzzy". Both algorithms of command MPPT associated to these techniques are tested under the weather conditions of Agadir city located in the South of Morocco. So, the results obtained under various operating conditions, show a significant improvement in the performances of MPPT control of a photovoltaic system using the fuzzy logic controller.
Author Keywords: Photovoltaic, MPPT controller, Buck converter, ", Perturb and Observe", , Fuzzy Logic.
Abstract: (french)
Le suiveur du point de puissance maximale (MPPT : Maximum Power Point Tracker) joue un rôle très important pour l'obtention de la puissance maximale d'un panneau solaire, car il permet d'assurer un fonctionnement optimal d'un système photovoltaïque, quelles que soient les conditions de variations d'ensoleillement et de température. Dans ce sens, nous présentons dans ce papier, une technique pour l'amélioration et l'optimisation des performances de contrôle d'un système, composé d'un panneau photovoltaïque, d'un hacheur série et d'une charge. Ce contrôle est effectué en mettant en œuvre deux techniques de poursuite du point de puissance maximale (MPP): l'une à base du contrôle par la logique floue de type Takagi Sugeno ("Flou TS") et l'autre employant l'algorithme "Perturber et Observer" ("P&O": Perturb and Observ). Des simulations des différentes parties du système sont développées sous Matlab/Simulink, permettant ainsi une comparaison entre les performances des deux contrôleurs étudiés ; "P&O" et "Flou TS". Les deux algorithmes de commande MPPT associées à ces techniques sont testés, sous les conditions météorologiques de la ville d'Agadir située au sud du Maroc. Les résultats ainsi obtenus, sous différentes conditions de fonctionnement, montrent une nette amélioration des performances de contrôle MPPT d'un système photovoltaïque en utilisant le contrôleur à base de la logique floue.
Author Keywords: Photovoltaïque, Contrôleur MPPT, Hacheur Buck, ", Perturber et Observer", , Logique Floue.
How to Cite this Article
M. Ajaamoum, M. Kourchi, B. Bouachrine, Ahmed Ihlal, and Lahoucine Bouhouch, “Comparaison du contrôleur flou Takagi-Sugeno et de la commande "P & O" Comparison of Takagi-Sugeno fuzzy controller and the command "P & O" for extracting the maximum power from a photovoltaic system,” International Journal of Innovation and Applied Studies, vol. 10, no. 1, pp. 192–206, January 2015.
