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Controller design for doubly fed induction generator using particle swarm optimization technique

Author

Listed:
  • Bharti, Om Prakash
  • Saket, R.K.
  • Nagar, S.K.

Abstract

This manuscript describes the controller design for doubly fed induction generator (DFIG) driven by a variable speed wind turbine using particle swarm optimization technique. The mathematical model of the DFIG, its power converters, and their controllers have illustrated in this paper appropriately. The lower order simple illustration of DFIG have been used for PID controller design using numerical differentiation of Simulink model. The controller design for DFIG based WECS using PSO technique and its fitness functions are described in detail. The responses of the DFIG system regarding terminal voltage, current, active-reactive power and DC-Link voltage along with generator speed have slightly improved with PSO based controller. Finally, the obtained output is equated with a standard technique for performance improvement of the DFIG based wind energy conversion system.

Suggested Citation

  • Bharti, Om Prakash & Saket, R.K. & Nagar, S.K., 2017. "Controller design for doubly fed induction generator using particle swarm optimization technique," Renewable Energy, Elsevier, vol. 114(PB), pages 1394-1406.
    • Handle: RePEc:eee:renene:v:114:y:2017:i:pb:p:1394-1406
    DOI: 10.1016/j.renene.2017.06.061
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    References listed on IDEAS

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    1. Caliao, Nolan D., 2011. "Dynamic modelling and control of fully rated converter wind turbines," Renewable Energy, Elsevier, vol. 36(8), pages 2287-2297.
    2. Saidur, R. & Rahim, N.A. & Islam, M.R. & Solangi, K.H., 2011. "Environmental impact of wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(5), pages 2423-2430, June.
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    Cited by:

    1. Subramanian Vasantharaj & Vairavasundaram Indragandhi & Vairavasundaram Subramaniyaswamy & Yuvaraja Teekaraman & Ramya Kuppusamy & Srete Nikolovski, 2021. "Efficient Control of DC Microgrid with Hybrid PV—Fuel Cell and Energy Storage Systems," Energies, MDPI, vol. 14(11), pages 1-18, June.
    2. Yuan, Guanghui & Yang, Weixin, 2019. "Study on optimization of economic dispatching of electric power system based on Hybrid Intelligent Algorithms (PSO and AFSA)," Energy, Elsevier, vol. 183(C), pages 926-935.
    3. Ochoa, Danny & Martinez, Sergio, 2018. "Frequency dependent strategy for mitigating wind power fluctuations of a doubly-fed induction generator wind turbine based on virtual inertia control and blade pitch angle regulation," Renewable Energy, Elsevier, vol. 128(PA), pages 108-124.

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