Modeling, Development and Analysis Performance of an Intelligent Control of Photovoltaic System by Fuzzy Logic approach for Maximum Power Point Tracking

In this paper, we present an intelligent algorithm based upon Fuzzy Logic method for optimizing and improving the control performance of a   photovoltaic system. The main objective of the proposed system is to pursuit the maximum power point (MPPT) under different conditions like the change of sunshine and temperature. The system consists of a photovoltaic solar module connected to a DC-DC step-up converter "Boost" and a battery - like a load . The converter parameters and the inference rule table are determined to ensure maximum output power. The effectiveness of the proposed system is validated through computer simulations using MATLAB / Simulink software and the obtained results shows that our proposed system has the best performance in term maximum power.

[1]  Afshan Ilyas,et al.  Realisation of incremental conductance the MPPT algorithm for a solar photovoltaic system , 2018 .

[2]  Saleh Elkelani Babaa.  Novel Switch Adaptive Control to Improve the Efficiency of Boost Converter in Photovoltaic Systems , 2017 .

[3]  W. Elmenreich,et al.  Efficiency of photovoltaic systems in mountainous areas , 2018, 2018 IEEE International Energy Conference (ENERGYCON).

[4]  El Madjid Berkouk,et al.  Artificial intelligence-based maximum power point tracking controllers for Photovoltaic systems: Comparative study , 2017 .

[6]  Ebrahim H. Mamdani,et al.  An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller , 1999, Int. J. Hum. Comput. Stud..

[7]  Moulay Fatima,et al.  A detailed modeling of photovoltaic module using MATLAB , 2014 .

[8]  Selo Sulistyo,et al.  Fuzzy Adaptive Hysteresis of RSS for Handover Decision in V2V VANET , 2020, Int. J. Commun. Networks Inf. Secur..

[9]  Bhagabat Panda,et al.  A Simplified Design and Modeling of Boost Converter for Photovoltaic Sytem , 2018 .

[10]  Fahli Ahmed,et al.  Photovoltaic Power Control Using Fuzzy Logic and Fuzzy Logic Type 2 MPPT Algorithms and Buck Converter , 2019 .

[11]  C. Larbes,et al.  Commande neuro-floue d'un hacheur MPPT , 2007 .

[12]  Fatima Errahimi,et al.  Modeling and Design of Single-Phase PV Inverter with MPPT Algorithm Applied to the Boost Converter Using Back-Stepping Control in Standalone Mode , 2019 .

[13]  Saad Motahhir,et al.  Modélisation et commande d’un panneau photovoltaïque dans l’environnement PSIM , 2015 .

[14]  Ahmed Naddami,et al.  Design and dimensioning of desalination mobile unit and optimization of electrical energy with MPPT algorithms , 2018 .

[15]  Rachid Outbib,et al.  General review and classification of different MPPT Techniques , 2017 .

[16]  Xu Jietian.  Photovoltaic Array Maximum Power Point Tracking Based on Improved Perturbation and Observation Method , 2011 .

[17]  Zainal Salam,et al.  DC-DC Boost Converter Design for Fast and Accurate MPPT Algorithms in Stand-Alone Photovoltaic System , 2018, International Journal of Power Electronics and Drive Systems (IJPEDS).

[18]  Jingxuan Tang,et al.  Photovoltaic Array Maximum Power Point Tracking Based on Improved Perturbation and Observation Method , 2018, Journal of Physics: Conference Series.