基于轨迹灵敏度分析的永磁直驱风电场等值模型参数辨识

doi:10.19595/j.cnki.1000-6753.tces.190879

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Abstract A large-scale wind farm connected to power grid has huge impact on the stability of power system. In order to improve simulation speed, it is essential to investigate the equivalent model of wind farm. In this paper, in view of the fact that the traditional aggregation method cannot solve the problem of parameter variation during long-term operation of wind farms, and manufacturers regard control system parameters as commercial secrets, a detailed equivalent model of permanent magnet synchronous generators(PMSG) wind farm and initialization method is established. The trajectory sensitivity of parameters is analyzed. Parameters identification strategy that the time-varying parameters with high sensitivity and control parameters with high sensitivity are identified using improved genetic learning particle swarm optimization (GLPSO) hybrid algorithm based on phasor measurement unit (PMU) data at the common interconnection point of wind farm while other parameters are fixed to aggregated or typical values is proposed. The robustness and adaptability of the equivalent model of PMSG wind farm under different wind speeds, wake effects, and when some PMSG are off-line or wind speed is unknown are analyzed. The global searching ability to find the optimum point of the proposed improved GLPSO is also validated.

Key words： Permanent magnet synchronous generators(PMSG) equivalent model of wind farm trajectory sensitivity parameter identification genetic learning particle swarm optimization hybrid algorithm

Received: 17 July 2019

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TM614

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	Zhang Jian
	He Yigang

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Zhang Jian,He Yigang. Parameters Identification of Equivalent Model of Permanent Magnet Synchronous Generator Wind Farm Based on Analysis of Trajectory Sensitivity[J]. Transactions of China Electrotechnical Society, 2020, 35(15): 3303-3313.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.190879 OR https://dgjsxb.ces-transaction.com/EN/Y2020/V35/I15/3303

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