Open AccessFrequency‐domain modelling and stability analysis of a DFIG‐based wind energy conversion system under non‐compensated AC grids: impedance modelling effects and consequences on stability
Author(s) -
Zhang Chen,
Cai Xu,
Molinas Marta,
Rygg Atle
Publication year - 2019
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2018.5527
Subject(s) - control theory (sociology) , nyquist stability criterion , nyquist plot , electrical impedance , stability (learning theory) , frequency domain , correctness , doubly fed electric machine , computer science , voltage , engineering , mathematics , ac power , algorithm , physics , control (management) , parametric statistics , statistics , electrical engineering , electrode , quantum mechanics , artificial intelligence , machine learning , electrochemistry , computer vision , dielectric spectroscopy
Impedance‐based frequency‐domain method is an effective tool for the stability assessment of a doubly fed induction generator (DFIG) system. Several impedance models have been proposed recently; however, these models are usually associated with model reductions since the complexity in achieving a detailed DFIG model. This may lead to unreliable stability results under certain conditions, and a clarification of this modelling effect is lacking in the literature. Therefore, this study aims to address this issue by developing a detailed DFIG impedance model. To achieve this target, a modular modelling technique is proposed instead of the conventional linearisation by parts, for which the components of a DFIG system are modelled as multi‐port modules. Through this method, the detailed DFIG model together with four types of reduced‐order models can be derived efficiently. The detailed DFIG model is verified by the measured frequency responses in PSCAD™/EMTDC™, along with its correctness in Nyquist‐based stability analysis. Subsequently, four types of the reduced‐order models are compared with the detailed one in terms of Nyquist plots, so that their performance and effectiveness for stability analysis are clarified. Besides, conclusions regarding the reduced‐order models are also verified by time‐domain simulations.