Robust multi-machine power system stabilizer design using bio-inspired optimization techniques and their comparison

Dhanraj Chitara, P. K. Singhal, S. L. Surana, Gulshan Sharma, R. C. Bansal

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

This paper reports a comparative study among four bio-inspired meta-heuristic techniques i.e. Sooty-Tern Optimization (STO), Grey Wolf Optimization (GWO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) to tune the robust Power System Stabilizer (PSS) parameters of the multi-machine power system. These approaches are successfully tested on two bench-mark systems: sixteen-machine, sixty-eight-bus New England Extended Power Grid (NEEPG) and three-machine, nine-bus Western System Coordinating Council (WSCC). The efficacy of planned PSS via STO and GWO is validated by extensive non-linear simulations, eigenvalue analysis, and performance indices for numerous operating conditions under decisive perturbations, and outcomes are matched with those of GA and PSO techniques. In addition, the robustness is also tested for these algorithms. The results indicate that the PSS design using STO and GWO improves the small-signal stability and damping performance for mitigating inter-area and local area modes of low-frequency oscillations compared to GA and PSO.

Original languageEnglish
Article number109615
JournalInternational Journal of Electrical Power and Energy Systems
Volume155
DOIs
Publication statusPublished - Jan 2024

Keywords

  • Grey Wolf Optimization
  • Low-frequency Oscillations
  • Power System Stabilizer
  • Sooty-Tern Optimization

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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