Research Article Open Access

Comparison of Different Control Strategies in GA-Based Optimized UPFC Controller in Electric Power Systems

Seyed Abbas Taher1, Reza Hematti1 and Majid Nemati1
  • 1 ,
American Journal of Engineering and Applied Sciences
Volume 1 No. 1, 2008, 45-52

DOI: https://doi.org/10.3844/ajeassp.2008.45.52

Submitted On: 15 May 2008 Published On: 31 March 2008

How to Cite: Taher, S. A., Hematti, R. & Nemati, M. (2008). Comparison of Different Control Strategies in GA-Based Optimized UPFC Controller in Electric Power Systems . American Journal of Engineering and Applied Sciences, 1(1), 45-52. https://doi.org/10.3844/ajeassp.2008.45.52

Abstract

This study presents a study of the application of a Unified Power Flow Controller (UPFC) to control power transmission, generator terminals voltage and better damping of Low Frequency Oscillation (LFO) in Single-Machine Infinite-Bus (SMIB) power system. The UPFC integrates properties of both shunt and series compensations and can effectively alter power system parameters in a way that increases power transfer capability and stabilizes system. In practice systems use simple Proportional Integral (PI) controllers for control of UPFC. However, since the PI control parameters are usually tuned based on classical or trial-and-error approaches, they are incapable of obtaining a good dynamic performance for a wide range of operation conditions. To address this problem, in this research an optimization approach, based on the Genetic Algorithms (GA) method is proposed for the design of UPFC controllers (power-flow controller, DC-voltage regulator and generator terminals voltage controller) and also supplementary damping controller for increase damping of power system oscillations is developed. A SMIB power system installed with a UPFC is considered for case study. Several linear time-domain simulation tests visibly show the effectiveness and validity of proposed method in control of power transmission, terminal voltage of generator and enhance of LFO damping.

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Keywords

  • Flexible AC transmission systems
  • power system oscillations
  • unified power flow controller
  • genetic algorithms