Power system stabilizer design using hybrid multi-objective particle swarm optimization with chaos

Mahdiyeh Eslami, Hussain Shareef, Azah Mohamed

Research output: Contribution to journalArticlepeer-review

45 Citations (Scopus)


A novel technique for the optimal tuning of power system stabilizer (PSS) was proposed, by integrating the modified particle swarm optimization (MPSO) with the chaos (MPSOC). Firstly, a modification in the particle swarm optimization (PSO) was made by introducing passive congregation (PC). It helps each swarm member in receiving a multitude of information from other members and thus decreases the possibility of a failed attempt at detection or a meaningless search. Secondly, the MPSO and chaos were hybridized (MPSOC) to improve the global searching capability and prevent the premature convergence due to local minima. The robustness of the proposed PSS tuning technique was verified on a multi-machine power system under different operating conditions. The performance of the proposed MPSOC was compared to the MPSO, PSO and GA through eigenvalue analysis, nonlinear time-domain simulation and statistical tests. Eigenvalue analysis shows acceptable damping of the low-frequency modes and time domain simulations also show that the oscillations of synchronous machines can be rapidly damped for power systems with the proposed PSSs. The results show that the presented algorithm has a faster convergence rate with higher degree of accuracy than the GA, PSO and MPSO.

Original languageEnglish
Pages (from-to)1579-1588
Number of pages10
JournalJournal of Central South University of Technology (English Edition)
Issue number5
Publication statusPublished - Oct 2011
Externally publishedYes


  • Chaos
  • Particle swarm optimization
  • Passive congregation
  • Penalty function
  • Power system stabilizer

ASJC Scopus subject areas

  • General Materials Science
  • Mechanics of Materials
  • Mechanical Engineering


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