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Abstract

Load frequency control (LFC) is one of the important control problems in design and operation of power systems as permanent deviation of frequency from nominal value affects power system operation and reliability. This paper presents a control method based on neural network for LFC of a two-area power system containing re-heat thermal plants. System parameters are assumed to be unknown and the proposed type-2 fuzzy controller is designed online, is adaptive and does not require initial adjustment by the operator. The training method of the type-2 fuzzy controller includes error back-propagation and gradient descent. In this paper, since the dynamics of the system is unknown, it is modelled using multilayer perceptron (MLP) structure, and Jacobian of the system is extracted to determine system model. In order to evaluate the robustness of proposed online adaptive fuzzy type-2 controller (OADF) against parameter changes, a time-variant parameter is added to the system. The performance of the controller is compared with the PI, PID, N-PID, fuzzy-PI and neural network controllers. Simulation results illustrate the improved performance of LFC and its capability to overcome uncertain and time-variant parameters.

Keywords

LFC adaptive type-2 fuzzy control multi-area power system MLP back-propagation and gradient descent

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Online adaptive type-2 fuzzy logic control for load frequency of multi-area power system

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