Open AccessWide‐area measurement system‐based model‐free approach of post‐fault rotor angle trajectory prediction for on‐line transient instability detection
Author(s) -
Huang Dan,
Yang Xiuyuan,
Chen Shuyong,
Meng Tao
Publication year - 2018
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.2017.1523
Subject(s) - control theory (sociology) , electric power system , transient (computer programming) , robustness (evolution) , trajectory , computer science , fault (geology) , rotor (electric) , power (physics) , artificial intelligence , engineering , control (management) , physics , astronomy , seismology , geology , operating system , mechanical engineering , biochemistry , chemistry , quantum mechanics , gene
In order to achieve adequate time for emergency control against transient instability, a scheme to predict the post‐fault rotor angle trajectory based on the grey Verhulst self‐memory model is provided. The proposed scheme is model free and only uses wide‐area measurement system data to provide timely, reliable information about the transient rotor angle stability. Moreover, the scheme is model‐parameter‐adaptive and takes full consideration of the non‐linearity as well as uncertainty of power systems. Firstly, the grey Verhulst self‐memory prediction model is presented to cope with the strong non‐linear and non‐autonomous nature of the power system. Secondly, the equal dimension and new information data model as well as the rolling prediction method are adopted to improve adaptability and robustness of prediction. Investigations with the IEEE‐39 bus system and NCE China power system indicate that the proposed prediction scheme gives better prediction performance compared with the other two prediction methods, i.e. grey Verhulst prediction and auto‐regressive prediction. Furthermore, combined with equal area criterion based on the severely disturbed generator pair, the proposed prediction scheme is conducted to detect transient instability. Simulation results indicate that the proposed prediction scheme is effective for prediction of transient stability.