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A Comprehensive Review of Power System Stabilizers

Author

Listed:
  • Adrian Nocoń

    (Faculty of Electrical Engineering, Silesian University of Technology, 44-100 Gliwice, Poland)

  • Stefan Paszek

    (Faculty of Electrical Engineering, Silesian University of Technology, 44-100 Gliwice, Poland)

Abstract

This paper presents a current literature review (from the years 2017–2022) on issues related to the application of power system stabilizers (PSSs) for damping electromechanical swings in power systems (PSs). After the initial selection of papers found in the databases used, over 600 publications were qualified for this review, of which 216 were subjected to detailed analysis. In the review, issues related to the following problems are described: applications of classic PSSs, applications of new stabilizer structures based on new algorithms (including artificial intelligence), development of new methods for tuning PSSs, and operation of PSSs in PSs with high power generation by renewable sources. Describing individual papers, the research methods used by the authors (simulations, measurement methods, and a combination of both) are specified, attention is paid to the waveforms presented in the papers, and reference is made to the types of PSs in which PSSs (large multimachine, reflecting real systems, smaller standard multimachine New-England type, and simplest single-machine) operate. The tables contain detailed comments on the selected papers. The final part of the review presents general comments on the analyzed papers and guidelines for future PS stability studies.

Suggested Citation

  • Adrian Nocoń & Stefan Paszek, 2023. "A Comprehensive Review of Power System Stabilizers," Energies, MDPI, vol. 16(4), pages 1-32, February.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1945-:d:1069771
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    References listed on IDEAS

    as
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    6. Tawfik Guesmi & Badr M. Alshammari & Yasser Almalaq & Ayoob Alateeq & Khalid Alqunun, 2021. "New Coordinated Tuning of SVC and PSSs in Multimachine Power System Using Coyote Optimization Algorithm," Sustainability, MDPI, vol. 13(6), pages 1-18, March.
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