
Real‐time identification of electromechanical oscillations through dynamic mode decomposition
Author(s) -
Berizzi Alberto,
Bosisio Alessandro,
Simone Riccardo,
Vicario Andrea,
Giannuzzi Giorgio,
Pisani Cosimo,
Zaottini Roberto
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.2020.0202
Subject(s) - dynamic mode decomposition , phasor , electric power system , computer science , robustness (evolution) , grid , real time computing , identification (biology) , power (physics) , chemistry , botany , machine learning , biology , biochemistry , physics , geometry , mathematics , quantum mechanics , gene
The increasing penetration of inverter‐based resources is affecting the overall power system security, so that effective tools are needed to provide system awareness and identify the most suited countermeasures. To tackle this problem, real‐time monitoring and assessment of transmission grids based on synchrophasor measurements have drawn the attention of many researchers over the last decade, thanks to the high temporal resolution of data provided by phasor measurement units. In this study, a new version of the dynamic mode decomposition (DMD) is proposed as a tool for the real‐time identification of electromechanical oscillations. This approach is able to provide information on the dynamic characteristics (frequency and damping) and the spatial correlation (mode shape) of the modes identified. Besides, an improved criterion is used to track and discern the dominant modes. The effectiveness of the DMD method has been tested on the two‐area Kundur system and validated using data from a real event on the European synchronous grid, giving promising results. Thanks to its reliability and robustness, the DMD is now implemented in the Terna (the Italian transmission system operator) Wide Area Measurement System in use in the control room.