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Research Article · Free to read · Published 30 September 2008

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

Seyed Abbas Taher, Reza Hematti, Ali Abdolalipour & Seyed Hadi Tabei

American Journal of Applied Sciences, Volume 5, Issue 9, pp. 1167–1174 · doi.org/10.3844/ajassp.2008.1167.1174

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Abstract

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.

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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. https://doi.org/10.3844/ajassp.2008.1167.1174

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Optimal Decentralized Load Frequency Control Using HPSO Algorithms in Deregulated Power SystemsAmerican Journal of Applied Sciences · Volume 5, Issue 9 · pp. 1167–1174 · © Science PublicationsDownload