Open AccessQuantitative short‐term voltage stability analysis of power systems integrated with DFIG‐based wind farms
Author(s) -
Qin Boyu,
Li Hengyi,
Zhang Xuemin,
Ding Tao,
Ma Ke,
Mei Shengwei
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2019.1701
Subject(s) - control theory (sociology) , electric power system , stability (learning theory) , doubly fed electric machine , term (time) , voltage , induction generator , fault (geology) , wind power , computer science , ac power , power (physics) , engineering , control engineering , control (management) , physics , quantum mechanics , artificial intelligence , machine learning , seismology , geology , electrical engineering
With the growing penetration of doubly‐fed induction generator (DFIG)‐based wind farms (WFs) in power systems, short‐term voltage stability problem has become more prominent. This study proposes a new approach for post‐fault short‐term voltage stability analysis by establishing a quantitative relationship between the system states/outputs and external disturbances. The concept of the integral‐integral estimate, which is equivalent to input‐to‐state stability, was adopted to perform quantitative analysis at the subsystem level, and practical algorithms were developed to study the local input‐to‐state/output stability properties of subsystems. System‐level quantitative analysis was achieved through the proposed criterion considering the stability properties of subsystems and their connections. The proposed method reveals the dynamic responses of the system under external disturbances and quantifies the size of the external disturbance that the system can tolerate, thus facilitating the operation of the power system integrated with DFIG‐based WFs. The short‐term voltage stability of a test power system was analysed using the proposed quantitative stability analysis approach, and the results were verified through time‐domain simulations.