Dynamic Performance Improvement of Automatic Voltage Regulator System Using Computation Evolutionary Algorithms

Abstract

Synchronous generators have been widely used to provide electricity for most customers. One of the most significant criteria that should be stabilized over the normal and abnormal operation of the synchronous generator is the terminal voltage of the synchronous generator. Automatic voltage regulators (AVRs) are control circuits dedicated to stabilizing the terminal voltage of the synchronous generator. However, such these control circuits only manifest some deficiencies during steady-state and transient responses.

Various control systems have been proposed to enhance the output response of AVR. The Proportional-Integral-Derivative (PID) controller is a control system that has been used to improve the terminal voltage of the synchronous generator. However, the most challenging technique with this controller is how to tune these parameters properly. Some strategies have been devoted to fine-tuning of PID.

The main contribution of this thesis is to enhance the output response of the AVR control system employed with a PID controller using various optimization techniques. In addition to the deterministic techniques that have been suggested to obtain fine-tuning of PID controller, meta-heuristic algorithms are proposed in this thesis to investigate the optimal design of PID controller which includes Whale Optimization Algorithm (WOA), Water Cycle Algorithm (WCA), and Moth-Flame Optimization (MFO) so as to enhance the output response of AVR control system. To ensure the effectiveness of these proposed algorithms with the AVR control system, a comparison is performed between these algorithms and Genetic Algorithm (GA) executing the same