A novel approach for power system stabilizer control parameter selection: a case-study on two-area four-machine system
This paper proposes a power system stabilizer (PSS) with optimal controller parameters for damping low-frequency power oscillations in the power system. A novel meta-heuristic, weighted grey wolf optimizer (WGWO) has been proposed, it is a variant of the grey wolf optimizer (GWO). The proposed WGWO...
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Veröffentlicht in: | Archives of Electrical Engineering (Online) 2022, Vol.71 (2), p.397-407 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This paper proposes a power system stabilizer (PSS) with optimal controller parameters for damping low-frequency power oscillations in the power system. A novel meta-heuristic, weighted grey wolf optimizer (WGWO) has been proposed, it is a variant of the grey wolf optimizer (GWO). The proposed WGWO algorithm has been executed in the selection of controller parameters of a PSS in a multi-area power system. A two-area fourmachine test system has been considered for the performance evaluation of an optimally tuned PSS. A multi-objective function based on system eigenvalues has been minimized for obtained optimal controller parameters. The damping characteristics and eigenvalue location in the proposed approach have been compared with the other state-of-the-art methods, which illustrates the effectiveness of the proposed approach. |
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ISSN: | 2300-2506 1427-4221 2300-2506 |
DOI: | 10.24425/aee.2022.140718 |