A new fuzzy sliding mode controller for load frequency control of large hydropower plant using particle swarm optimization algorithm and Kalman estimator

Abstract

SUMMARY The load frequency control (LFC) is very important in power system operation and control for supplying sufficient, reliable, and high-quality electric power. The conventional LFC uses an integral controller. In this paper, a new control system based on the fuzzy sliding mode controller is proposed for controlling the load frequency of nonlinear model of a hydropower plant, and this control system is compared with the proportional–integral controller and the conventional sliding mode controller. To regulate the membership functions of fuzzy system more accurately, the particle swarm optimization algorithm is also applied. Moreover, because of the unavailability of the control system variables, a nonlinear estimator is suggested for estimating and identifying the system state variables. This estimator provides the physical realization of the method and will reduce the costs of implementation. The proposed control method is performed for the LFC of hydropower plant of Karoon-3 in Shahrekord, Iran. The simulation results show the capability of the controller system in controlling local network frequency. Copyright © 2011 John Wiley & Sons, Ltd.