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Parameters Identification of Equivalent Model of Permanent Magnet Synchronous Generator (PMSG) Wind Farm Based on Analysis of Trajectory Sensitivity

Author

Listed:
  • Jian Zhang

    (School of Electric and Automation Engineering, Hefei University of Technology, Heifei 230009, China)

  • Mingjian Cui

    (School of Electric and Electronic Engineering, The University of Tennessee, Knoxville, TN 37996-0150, USA)

  • Yigang He

    (School of Electric and Automation, Wuhan University, Wuhan 430072, China)

Abstract

As wind farms have great influences on power system stability, it is essential to develop an adaptive as well as robust equivalent model of it. In this paper, a detailed equivalent model of PMSG wind farm and initialization method is developed. The trajectory sensitivity of parameters is analyzed. Then, the key parameters are estimated using improved Genetic Learning Particle Swarm Optimization (GLPSO) hybrid algorithm with phasor measurement unit (PMU). The description and generalization capability, stability for parameter identification of the equivalent model under wake effects, and when some wind turbines are off-line or wind speed is unknown after an event are analyzed. The maximum differences between the values of estimated parameters and their real ones are less than 10% for the proportional magnification constant of DC voltage controller K p 2 and grid side current controller K p 3 . The convergence rate and global optimization performance of the improved GLPSO hybrid algorithm is 0.5 times higher than the classical particle swarm optimization algorithm (PSO) and genetic algorithm (GA).

Suggested Citation

  • Jian Zhang & Mingjian Cui & Yigang He, 2020. "Parameters Identification of Equivalent Model of Permanent Magnet Synchronous Generator (PMSG) Wind Farm Based on Analysis of Trajectory Sensitivity," Energies, MDPI, vol. 13(18), pages 1-18, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4607-:d:409117
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    References listed on IDEAS

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    1. Zhang, Jian & Cui, Mingjian & He, Yigang, 2020. "Robustness and adaptability analysis for equivalent model of doubly fed induction generator wind farm using measured data," Applied Energy, Elsevier, vol. 261(C).
    2. Fernández, Luis M. & Jurado, Francisco & Saenz, José Ramón, 2008. "Aggregated dynamic model for wind farms with doubly fed induction generator wind turbines," Renewable Energy, Elsevier, vol. 33(1), pages 129-140.
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    Cited by:

    1. Chuan Qin & Yuqing Jin & Meng Tian & Ping Ju & Shun Zhou, 2023. "Comparative Study of Global Sensitivity Analysis and Local Sensitivity Analysis in Power System Parameter Identification," Energies, MDPI, vol. 16(16), pages 1-21, August.
    2. Ruipeng Guo & Lilan Dong & Hao Wu & Fangdi Hou & Chen Fang, 2021. "A Practical GERI-Based Method for Identifying Multiple Erroneous Parameters and Measurements Simultaneously," Energies, MDPI, vol. 14(12), pages 1-21, June.
    3. Jingde Xia & Shaozhuo Li & Shuping Gao & Wenquan Shao & Guobing Song & Changjiang Chen, 2021. "Research on Differential Protection of Generator Based on New Braking Mode," Energies, MDPI, vol. 14(7), pages 1-16, March.

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