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High efficiency control strategy in a wind energy conversion system with doubly fed induction generator

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  • Karakasis, Nektarios E.
  • Mademlis, Christos A.

Abstract

This paper presents a high efficiency control strategy for a wind energy conversion system (WECS) with doubly fed induction generator (DFIG). The proposed control scheme provides power loss reduction for the DFIG and maximum power point tracking (MPPT) for the wind turbine. Therefore, increased electric energy production from the same wind energy potential can be attained. Moreover, the cut-in wind speed is reduced and thereby, extension of the exploitable wind speed region is accomplished. Τhe high efficiency in the DFIG is attained through the stator frequency and magnetic-flux weakening control, and the maximum harvesting in the turbine is accomplished by properly controlling the turbine speed. The proposed control system can be easily implemented, since the controller parameters are determined experimentally and thus, the knowledge of the wind system model is not required. Moreover, for the implementation of the proposed control scheme, a converter system of low power requirements is used, as holds in the conventional system, and thus, this advantage of the WECS with DFIG against other electrical generator types is still valid. The efficiency improvement of the proposed control scheme has been experimentally validated in a laboratory low power scaling emulation WECS with DFIG.

Suggested Citation

  • Karakasis, Nektarios E. & Mademlis, Christos A., 2018. "High efficiency control strategy in a wind energy conversion system with doubly fed induction generator," Renewable Energy, Elsevier, vol. 125(C), pages 974-984.
    • Handle: RePEc:eee:renene:v:125:y:2018:i:c:p:974-984
    DOI: 10.1016/j.renene.2018.03.020
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    Cited by:

    1. Chen, Jian & Yao, Wei & Zhang, Chuan-Ke & Ren, Yaxing & Jiang, Lin, 2019. "Design of robust MPPT controller for grid-connected PMSG-Based wind turbine via perturbation observation based nonlinear adaptive control," Renewable Energy, Elsevier, vol. 134(C), pages 478-495.
    2. Hongyan Dui & Xiaoqian Zheng & Jianjun Guo & Hui Xiao, 2022. "Importance measure-based resilience analysis of a wind power generation system," Journal of Risk and Reliability, , vol. 236(3), pages 395-405, June.
    3. Agha Kashkooli, M.R. & Jovanović, Milutin G., 2021. "Sensorless adaptive control of brushless doubly-fed reluctance generators for wind power applications," Renewable Energy, Elsevier, vol. 177(C), pages 932-941.
    4. Qin Guo & Zhongkui Sun & Ying Zhang & Wei Xu, 2019. "Time-Delayed Feedback Control in the Multiple Attractors Wind-Induced Vibration Energy Harvesting System," Complexity, Hindawi, vol. 2019, pages 1-11, January.
    5. Gupta, Akhilesh Prakash & Mohapatra, A. & Singh, S.N., 2021. "Measurement based parameters estimation of large scale wind farm dynamic equivalent model," Renewable Energy, Elsevier, vol. 168(C), pages 1388-1398.
    6. Wang, Kunlin & Wang, Zhe & Sheng, Songwei & Zhang, Yaqun & Wang, Zhenpeng & Ye, Yin & Wang, Wensheng & Lin, Hongjun & Huang, Zhenxin, 2023. "A method for large-scale WEC connecting to island isolated microgrid based on multiple small power HPGSs," Renewable Energy, Elsevier, vol. 218(C).

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