Open AccessSynchronised ambient data‐driven electromechanical oscillation modes extraction for interconnected power systems using the output‐only observer/Kalman filter identification method
Author(s) -
Wang Lixin,
Yang Deyou,
Cai Guowei,
Ma Jin,
Tian Jie,
Wang Bo
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.2020.0025
Subject(s) - kalman filter , control theory (sociology) , oscillation (cell signaling) , electric power system , impulse (physics) , computer science , engineering , power (physics) , physics , artificial intelligence , genetics , control (management) , quantum mechanics , biology
Ambient‐based oscillation modes extraction is an effective means of monitoring the small signal stability of a power system on‐line. In this study, a data‐driven approach based on output‐only observer/Kalman filter identification (O 3 KID) combined with the eigensystem realisation algorithm (ERA) was proposed to extract electromechanical modes (frequency, damping ratio and mode shape) from synchronised ambient data. As a key for extracting a reduced‐order state matrix using the ERA, the Markov parameters (impulse responses) are first estimated by employing O 3 KID on multi‐channel ambient data. O 3 KID makes it possible to identify the modes with the ERA using only output ambient data, while ensuring the reliability of the extractions of frequencies, damping ratios and mode shapes. The performance of the proposed method was evaluated by employing the IEEE 16‐generator 5‐area system and measured data from a real power system. The estimation results in all cases as well as comparison results with the RDT‐ERA method and NExT‐ERA method indicate that the O 3 KID‐ERA method is a promising method for ambient data‐driven electromechanical oscillation modes extraction.