Title: An adaptive power system stabiliser based on fuzzy and swarm intelligence

Authors: M.A. Awadallah, H.M. Soliman

Addresses: Department of Electrical Power and Machines, Faculty of Engineering, University of Zagazig, Zagazig 44111, Egypt. ' Electrical Engineering Department, Faculty of Engineering, Cairo University, Giza 12613, Egypt

Abstract: Well-damped transient response of power systems signifies a vital control task. The paper presents a design methodology of an adaptive power system stabiliser (PSS) to achieve such task by targeting certain damping ratio and settling time. A standard simple-structure controller is used with the plant, which includes the synchronous generator and exciter, and the overall transfer function is derived in terms of the PSS parameters. A multi-objective optimisation function is formulated in order to force the damping ratio and settling time of the system to desired values. Particle swarm optimisation (PSO) is applied to independently obtain the PSS parameters which minimise such objective function at selected load points covering a wide range of operation. The data obtained from PSO represent the training data of an adaptive neuro-fuzzy inference system (ANFIS), which could give the PSS parameters at any load within a wide region of operating conditions. Testing of the proposed PSS shows that the desired performance indices could be fulfilled from light load to over load under both lagging and leading power factor conditions.

Keywords: adaptive control; power system stabilisers; PSS; particle swarm optimisation; PSO; neuro-fuzzy systems; neural networks; fuzzy control; power systems; damping ratio; settling time; ANFIS; adaptive inference systems.

DOI: 10.1504/IJMIC.2008.021775

International Journal of Modelling, Identification and Control, 2008 Vol.5 No.1, pp.55 - 65

Published online: 03 Dec 2008 *

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