Robust Adaptive Load Frequency Controller Based on Reinforcement Learning in an Inter-Connected Power System

Authors

Department of Electrical Engineering, Faculty of Engineering, University of Mohaghegh Ardabili, Ardabil, Iran

Abstract

The aim of this paper is using reinforcement learning for designing of robust and adaptive PID and SMES controllers to load frequency control in a two area thermal power system. Thus, in first setting of PID and SMES controller parameters formulated as an optimization problem and solved using teaching-learning optimization algorithm. Then the simultaneous performance of designed controllers improved using proposed reinforcement learning based controller. Simple and understandable structure and easy to use are distinguished advantages of q-learning based controllers. In order to evaluate the performance of the proposed controller, computer simulations have been done by using MATLAB software. Simulation results verified that the proposed q-learning based controller exhibits much better performance from the conventional optimization based controllers from viewpoint of time domain performance indices like over shoot, under shoot, ITAE, ITSE, and IAE.

Keywords