Multivariable Controller Design for Unified Power Flow Controller Using Evolutionary Optimization Algorithms

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Abstract: This paper discusses the design of a multivariable control for unified power flow controller using evolutionary optimization algorithms. It utilizes two biologically inspired optimization algorithms; the particle swarm optimization algorithm and biogeography optimization algorithms, to obtain the optimal set for the controllers of the UPFC. The UPFC is to control the active power flow through the line, regulate the AC bus voltage, regulate the DC link voltage, and damp the low frequency oscillations in the network through a set of PI controllers and a two stage lead lag compensator respectively. The obtained controllers are then verified through time domain simulation for different variable control to assess the capability of this multivariable control scheme.

WSEAS Transactions on Systems and Control, ISSN / E-ISSN: 1991-8763 / 2224-2856, Volume 16, 2017, Art. #30

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S. A. Al-Mawsawi, A. Haider, S. A. Al-Qallaf, "Multivariable Controller Design for Unified Power Flow Controller Using Evolutionary Optimization Algorithms," WSEAS Transactions on Systems and Control, vol. 16, pp. 277-287, 2017, DOI:
S. A. Al-Mawsawi, A. Haider, S. A. Al-Qallaf. Multivariable Controller Design for Unified Power Flow Controller Using Evolutionary Optimization Algorithms. WSEAS Transactions on Systems and Control. 2017;16:277-287.
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