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High performance of Maximum Power Point Tracking Using Ant Colony algorithm in wind turbine

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  • Mokhtari, Yacine
  • Rekioua, Djamila

Abstract

The growing interest in wind power as a source of electric power generation with minimal environmental impact and the advancement of aerodynamic designs, including wind turbines, have been the subject of numerous studies. When wind energy is integrated into the grid, this gives a significant amount of power added to the one produced by other types of plants. Several researchers aim to achieve high efficiency in wind power systems using maximum power point tracking (MPPT) of a variable-speed turbine but this technique is complicated because the different approximations that occur during the online calculations. The main objective of this work is to develop and improve a maximum power tracking control strategy using metaheuristic methods. Ant colony optimization (ACO) algorithm is used to determine the optimal PI controller parameters for speed control. The optimization of the speed gets a better value of power coefficient therefore the extracting power.

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  • Mokhtari, Yacine & Rekioua, Djamila, 2018. "High performance of Maximum Power Point Tracking Using Ant Colony algorithm in wind turbine," Renewable Energy, Elsevier, vol. 126(C), pages 1055-1063.
    • Handle: RePEc:eee:renene:v:126:y:2018:i:c:p:1055-1063
    DOI: 10.1016/j.renene.2018.03.049
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    10. Ehtisham Lodhi & Fei-Yue Wang & Gang Xiong & Ghulam Ali Mallah & Muhammad Yaqoob Javed & Tariku Sinshaw Tamir & David Wenzhong Gao, 2021. "A Dragonfly Optimization Algorithm for Extracting Maximum Power of Grid-Interfaced PV Systems," Sustainability, MDPI, vol. 13(19), pages 1-27, September.
    11. Yashar Mousavi & Geraint Bevan & Ibrahim Beklan Küçükdemiral & Afef Fekih, 2021. "Maximum Power Extraction from Wind Turbines Using a Fault-Tolerant Fractional-Order Nonsingular Terminal Sliding Mode Controller," Energies, MDPI, vol. 14(18), pages 1-16, September.
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