中国电力 ›› 2019, Vol. 52 ›› Issue (9): 102-109.DOI: 10.11930/j.issn.1004-9649.201803161

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基于轨迹灵敏度的同步发电机参数辨识

张伟骏1, 陈文龙2, 黄霆1, 苏清梅1, 林芳1, 林济铿2   

  1. 1. 国网福建省电力有限公司电力科学研究院, 福建 福州 350007;
    2. 同济大学 电子与信息工程学院, 上海 201804
  • 收稿日期:2018-03-26 修回日期:2019-02-13 出版日期:2019-09-05 发布日期:2019-09-19
  • 作者简介:张伟骏(1990-),男,硕士,工程师,从事机网协调技术研究,E-mail:14158755@qq.com;陈文龙(1994-),男,硕士研究生,从事电力系统仿真及参数辨识研究,E-mail:634072204@qq.com;黄霆(1976-),男,硕士,高级工程师,从事机网协调技术研究、电力系统仿真分析研究,E-mail:huangtingmail@126.com

Parameter Identification Method of Synchronous Generator Based on Trajectory Sensitivity

ZHANG Weijun1, CHEN Wenlong2, HUANG Ting1, SU Qingmei1, LIN Fang1, LIN Jikeng2   

  1. 1. State Grid Fujian Electric Power Research Institute, Fuzhou 350007, China;
    2. College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China
  • Received:2018-03-26 Revised:2019-02-13 Online:2019-09-05 Published:2019-09-19

摘要: 为提高同步发电机暂态及次暂态参数辨识精度,提出了一种基于轨迹灵敏度的同步发电机参数辨识方法。首先确定了基于轨迹灵敏度的辨识数据区间选取方法,将量测的发电机参数的轨迹灵敏度作为指标,根据该指标的衰减程度,选取暂态及次暂态参数信息含量较大的量测数据作为辨识数据,以提高相应参数的辨识精度;其次采用抗差优化模型作为机组参数辨识优化模型,以提高参数辨识模型的抗干扰能力。算例验证了所提方法的有效性。

关键词: 同步发电机, 参数辨识, 轨迹灵敏度, 辨识数据区间选取, 抗差优化模型

Abstract: In order to improve the identification accuracy of transient and sub-transient parameters of synchronous generators, a parameter identification method is proposed for synchronous generator based on trajectory sensitivity. Firstly, the method for selecting the data intervals is determined based on the trajectory sensitivity, and the measured trajectory sensitivity of the generator parameters is used as an index. According to the attenuation degree of the index, the measured data with more information of transient and sub-transient parameters are selected and used as the identification data so as to improve the identification accuracy of the corresponding parameters. And then, the robust optimization model is used as the optimization model of generator parameter identification to improve the anti-jamming ability of the parameter identification model. Case study has proved the effectiveness of the proposed method.

Key words: synchronous generator, parameter identification, trajectory sensitivity, data interval selection for identification, robustness optimization model

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