Research Article Open Access

Optimal Decentralized Load Frequency Control Using HPSO Algorithms in Deregulated Power Systems

Seyed Abbas Taher1, Reza Hematti1, Ali Abdolalipour1 and Seyed Hadi Tabei1
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Load Frequency Control (LFC) is one the most important issues in electrical power system design/operation and is becoming much more significant recently with increasing size, changing structure and complexity in interconnected power systems. In practice LFC systems use simple Proportional-Integral (PI) or Integral (I) controllers. However, since the PI or I control parameters are usually tuned based on classical or trial-and-error approaches, they are incapable of obtaining good dynamic performance for various load changes scenarios in multi-area power system. For this reason, in this study the PI and I control parameters are tuned based on Hybrid Particle Swarm Optimization (HPSO) algorithm method for LFC control in two-area power system. Because HPSO is an optimization method, therefore, in the uncertainty area of controller parameters, finds the best parameters for controller and obtained controller is an optimal controller. A two-area power system example is given to illustrate proposed methods. To show effectiveness of proposed method and compare the performance of optimized PI and I type controllers, several time-domain simulation for various load changes scenarios are presented. Simulation results emphasis on the better performance of optimized PI controller in compared to optimized I controller in LFC.

American Journal of Applied Sciences
Volume 5 No. 9, 2008, 1167-1174


Submitted On: 12 December 2007 Published On: 30 September 2008

How to Cite: Taher, S. A., Hematti, R., Abdolalipour, A. & Tabei, S. H. (2008). Optimal Decentralized Load Frequency Control Using HPSO Algorithms in Deregulated Power Systems . American Journal of Applied Sciences, 5(9), 1167-1174.

  • 33 Citations



  • Load Frequency Control (LFC)
  • Hybrid Particle Swarm Optimization (HPSO)
  • decentralized control
  • deregulated power systems