Load frequency control of interconnected power systems using hybrid algorithm based particle swarm and grey wolf optimizers

Abstract

This study introduces a new hybrid optimization technique into the research field of load frequency control. The new technique is a hybrid technique that combines two metaheuristic-based algorithms: Particle Swarm Optimizer (PSO) and Grey Wolf Optimization (GWO). This new technique facilitates the selection of the best gain values of the controller used in the power system under study. The controller utilized in this study is the classical proportional-integral-derivative (PID) controller. This classical controller is selected in this study to make a reliable comparison with other applied techniques. The study's main goal is to retain the system frequency and tie-line power within permissible limits after applying a load disturbance to one of the system areas. The system under test is built as a three area network with thermal power generation units. The hybrid PSO-GWO (HPSOGWO) algorithm is applied to the system under test. The results obtained are verified by comparing them with other techniques, including the bacterial foraging technique (BFOA) and harmony search technique (HS). The results show that the HPSOGWO algorithm can preserve the frequency and tie-line power within the permissible bounds faster and with better transient specifications than that obtained using the other algorithms under comparison. The three area system is simulated in MATLAB environment for an easier interface.