Open AccessMulti‐criterion integrated method for low‐frequency oscillation‐type identification
Author(s) -
Sun Ming,
Chen Lei,
Xu Xialing,
Min Yong,
Xu Youping,
Li Kai
Publication year - 2018
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.8353
Subject(s) - oscillation (cell signaling) , low frequency oscillation , control theory (sociology) , flowchart , computer science , electric power system , harmonic , waveform , power (physics) , physics , control (management) , acoustics , artificial intelligence , genetics , quantum mechanics , biology , programming language , telecommunications , radar
Low‐frequency oscillation is one of the major threats to power system security. Online analysis and control decision system for low‐frequency oscillation is in urgent need. Natural oscillation and forced oscillation are two types of low‐frequency oscillation. Different oscillation types need different treatment measures. Thus oscillation‐type identification is an important part of the defense system. A new multi‐criteria integrated method for identifying low‐frequency oscillation type is proposed. It has multiple criteria and overcomes the shortcomings of the previous single‐criterion method which has low accuracy. It chooses harmonic content, characteristic index of starting oscillation waveform, and the startup‐stage intrinsic damping ratio together with noise response damping ratio as criteria. The flowchart of the method is provided. The effectiveness of the multi‐criteria integrated method is verified by real‐power grid simulation cases. The results show that the method can reliably distinguish the low‐frequency oscillation type and is practical in the real‐power system.