On-Line Optimal Power Flow Using Evolutionary Programming Techniques

Authors

  • M.I. Mosaad
  • M.M. El Metwally
  • A.A. El Emary
  • F.M. El Bendary

Keywords:

On-Line Optimal Power Flow, Particle Swarm Optimization and Artificial Neural Network

Abstract

This paper aims to solve On-Line Optimal Power Flow (ON-OPF) to minimize fuel cost using Evolutionary Programming Techniques. The solution of that optimization problem is based on using the Particle Swarm Optimization (PSO) technique for each loading condition with minimum fuel cost. All previous obtained results are used as a database for training an Artificial Neural Network (ANN) to obtain an on line solution (decision) to control output power of each generating unit at different loading conditions while satisfying minimum fuel cost.

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How to Cite

Mosaad, M., El Metwally, M., El Emary, A., & El Bendary, F. (2015). On-Line Optimal Power Flow Using Evolutionary Programming Techniques. Science & Technology Asia, 15(1), 20–28. Retrieved from https://ph02.tci-thaijo.org/index.php/SciTechAsia/article/view/41305

Issue

Vol.15 No.1 (January-March 2010)

Section

Articles