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A Comparative Study on Maximum Power Point Tracking Techniques of Photovoltaic Systems

Author

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  • Afef Badis

    (National School of Engineers of Monastr, Monastr, Tunisia)

  • Mohamed Habib Boujmil

    (Higher Institute of the Technological Studies of Nabeul, Kelibia, Tunisia)

  • Mohamed Nejib Mansouri

    (National School of Engineers of Monastr, Monastr, Tunisia)

Abstract

This article concerns maximizing the energy reproduced from the photovoltaic (PV) system, ensured by using an efficient Maximum Power Point Tracking (MPPT) process. The process should be fast, rigorous and simple for implementation because the PV characteristics are extremely affected by fast changing conditions and Partial Shading (PS). PV systems are popularly known to have many peaks (one Global Peak (GP) and several local peaks). Therefore, the MPPT algorithm should be able to accurately detect the unique GP as the maximum power point (MPP), and avoid any other peak to mitigate the effect of (PS). Usually, with no shading, nearly all the conventional methods can easily reach the MPP with high efficiency. Nonetheless, they fail to extract the GP when PS occurs. To overcome this problem, Evolutionary Algorithms (AEs), namely the Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are simulated and compared to the conventional methods (Perturb & Observe) under the same software.

Suggested Citation

  • Afef Badis & Mohamed Habib Boujmil & Mohamed Nejib Mansouri, 2018. "A Comparative Study on Maximum Power Point Tracking Techniques of Photovoltaic Systems," International Journal of Energy Optimization and Engineering (IJEOE), IGI Global, vol. 7(1), pages 66-85, January.
    • Handle: RePEc:igg:jeoe00:v:7:y:2018:i:1:p:66-85
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