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Speed control of induction motor supplied by wind turbine via Imperialist Competitive Algorithm

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  • Ali, Ehab S.

Abstract

This paper proposes the speed control of IM (Induction Motor) fed by wind turbine using ICA (Imperialist Competitive Algorithm). The wind turbine plays as a prime mover to a connected DC (Direct Current) generator. PWM (Pulse Width Modulation) is used to get three phase AC (Alternating Current) voltage from the output of DC generator. The proposed design problem of speed controller is established as an optimization problem. ICA is adopted to search for optimal controller parameters by minimizing the time domain objective function. The behavior of the proposed ICA has been estimated with the behavior of the conventional ZN (Ziegler–Nichols) and GA (Genetic Algorithm) in order to prove the superiority of the proposed ICA in tuning PI (Proportional plus Integral) controller. Also, the behavior of the proposed controller has been tested over a wide range of operating conditions. Simulation results confirm on the better behavior of the optimized PI controller based on ICA compared with other algorithms.

Suggested Citation

  • Ali, Ehab S., 2015. "Speed control of induction motor supplied by wind turbine via Imperialist Competitive Algorithm," Energy, Elsevier, vol. 89(C), pages 593-600.
    • Handle: RePEc:eee:energy:v:89:y:2015:i:c:p:593-600
    DOI: 10.1016/j.energy.2015.06.011
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    1. Mohammadi-ivatloo, Behnam & Rabiee, Abbas & Soroudi, Alireza & Ehsan, Mehdi, 2012. "Imperialist competitive algorithm for solving non-convex dynamic economic power dispatch," Energy, Elsevier, vol. 44(1), pages 228-240.
    2. Ghasemi, Mojtaba & Ghavidel, Sahand & Ghanbarian, Mohammad Mehdi & Gharibzadeh, Masihallah & Azizi Vahed, Ali, 2014. "Multi-objective optimal power flow considering the cost, emission, voltage deviation and power losses using multi-objective modified imperialist competitive algorithm," Energy, Elsevier, vol. 78(C), pages 276-289.
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    2. Zhang, Xiaoshun & Chen, Yixuan & Yu, Tao & Yang, Bo & Qu, Kaiping & Mao, Senmao, 2017. "Equilibrium-inspired multiagent optimizer with extreme transfer learning for decentralized optimal carbon-energy combined-flow of large-scale power systems," Applied Energy, Elsevier, vol. 189(C), pages 157-176.
    3. Jouda Arfaoui & Hegazy Rezk & Mujahed Al-Dhaifallah & Mohamed N. Ibrahim & Mami Abdelkader, 2020. "Simulation-Based Coyote Optimization Algorithm to Determine Gains of PI Controller for Enhancing the Performance of Solar PV Water-Pumping System," Energies, MDPI, vol. 13(17), pages 1-17, August.
    4. Frikha, Sobhi & Driss, Zied & Ayadi, Emna & Masmoudi, Zied & Abid, Mohamed Salah, 2016. "Numerical and experimental characterization of multi-stage Savonius rotors," Energy, Elsevier, vol. 114(C), pages 382-404.
    5. Wang, Jianzhou & Hu, Jianming, 2015. "A robust combination approach for short-term wind speed forecasting and analysis – Combination of the ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vec," Energy, Elsevier, vol. 93(P1), pages 41-56.
    6. Mahdy, Ahmed & Hasanien, Hany M. & Helmy, Waleed & Turky, Rania A. & Abdel Aleem, Shady H.E., 2022. "Transient stability improvement of wave energy conversion systems connected to power grid using anti-windup-coot optimization strategy," Energy, Elsevier, vol. 245(C).
    7. Memon, Abdul Jabbar & Shaikh, Muhammad Mujtaba, 2016. "Confidence bounds for energy conservation in electric motors: An economical solution using statistical techniques," Energy, Elsevier, vol. 109(C), pages 592-601.
    8. Xu, Fangqiu & Liu, Jicheng & Lin, Shuaishuai & Dai, Qiongjie & Li, Cunbin, 2018. "A multi-objective optimization model of hybrid energy storage system for non-grid-connected wind power: A case study in China," Energy, Elsevier, vol. 163(C), pages 585-603.
    9. Ahmet Selim Pehlivan & Beste Bahceci & Kemalettin Erbatur, 2022. "Genetically Optimized Pitch Angle Controller of a Wind Turbine with Fuzzy Logic Design Approach," Energies, MDPI, vol. 15(18), pages 1-15, September.
    10. Cheng, Youliang & Xue, Zhanpu & Jiang, Tuo & Wang, Wenyang & Wang, Yuekun, 2018. "Numerical simulation on dynamic response of flexible multi-body tower blade coupling in large wind turbine," Energy, Elsevier, vol. 152(C), pages 601-612.
    11. Adewuyi, Adeolu O. & Awodumi, Olabanji B., 2017. "Biomass energy consumption, economic growth and carbon emissions: Fresh evidence from West Africa using a simultaneous equation model," Energy, Elsevier, vol. 119(C), pages 453-471.

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