Page 146 - 《中国电力》2026年第3期

第 59 卷 第 3 期 Vol. 59, No. 3
2026 年 3 月 ELECTRIC POWER Mar. 2026

引用格式：王宇, 王彤, 王潇桐. 基于多时间尺度故障过程分区的 DFIG 参数分层递进式辨识策略[J]. 中国电力, 2026, 59(3): 142−155.
Citation: WANG Yu, WANG Tong, WANG Xiaotong. Hierarchical progressive identification strategy for DFIG parameters based on multi-
timescale fault process partitioning[J]. Electric Power, 2026, 59(3): 142−155.

基于多时间尺度故障过程分区的 DFIG

参数分层递进式辨识策略

王宇，王彤，王潇桐

(新能源电力系统全国重点实验室（华北电力大学），北京 102206)

Hierarchical progressive identification strategy for DFIG parameters based on

multi-timescale fault process partitioning
WANG Yu, WANG Tong, WANG Xiaotong

(State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources (North China Electric
Power University), Beijing 102206, China)

Abstract: To address the parameter identification problem of This work is supported by National Natural Science Foundation
black-box models for doubly-fed induction generator (DFIG) of China (No.52277096).
wind turbines under multiple operating conditions, this paper Keywords: doubly-fed induction generator; hierarchical
proposes a hierarchical progressive parameter identification progressive identification strategy; electromagnetic transient
strategy based on the partitioning of multi-timescale fault model; differential evolution algorithm; trajectory sensitivity
process. Firstly, the model structure and parameters to be
摘 要：针对多工况下双馈风电机组黑盒模型参数辨识
identified are determined according to the dynamic response
问题，提出基于多时间尺度故障过程分区的分层递进式
characteristics of the black-box model. Subsequently, the
参数辨识策略。首先，基于黑盒模型动态响应特性确定
sensitivity of parameters across different time scales is
了模型结构及待辨识参数。其次，通过摄动理论量化分
quantitatively analyzed using perturbation theory, and a
析了不同时间尺度参数灵敏度，依据不同阶段主导参数
hierarchical progressive identification method is established
响应特性建立了层次化递进式辨识方法。然后，通过不
according to the dominant parameter response characteristics in 同层级参数响应差异化特性，利用差分进化方法实现了
different operational stages. Furthermore, by leveraging the 多参数自适应辨识。最后，建立了适用不同厂家不同型
differential response characteristics of parameters across 号的白盒模型参数辨识方法，结果表明：所提出的分层
hierarchical levels, the differential evolution method is adopted 递进式辨识策略对不同工况和型号的具有适用性和鲁棒
to realize adaptive identification of multiple parameters. 性，与传统参数辨识方法相比，所提辨识方法具有更好
Finally, a white-box model parameter identification method 的快速性和准确性。
applicable to various manufacturers and models is developed. 关键词：双馈风力发电机；分层递进式辨识策略；电磁
Comparative results show that the proposed hierarchical 暂态模型；差分进化法；轨迹灵敏度
progressive identification strategy has good applicability and DOI：10.11930/j.issn.1004-9649.202507006

robustness under different operating conditions and for different
models. Additionally, comparisons results with traditional 0 引言
parameter identification methods also demonstrate that the
proposed approach exhibits superior rapidity and accuracy. 近年来，在高比例可再生能源和高比例电力
电子设备并网的背景下，电力系统稳定性分析需
收稿日期：2025−07−03； 修回日期：2026−01−11。 要更高精度的仿真模型 [1-2] ，但传统机电暂态模型
基金项目：国家自然科学基金资助项目（52277096）。 已经无法满足“双高”电力系统仿真要求。双馈

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