Load frequency control in deregulated power system with renewable energy sources: Hybrid GOA‐SNN technique

Abstract

This paper proposes a hybrid technique for load frequency control (LFC) in an inter‐connected deregulated power‐system. The proposed method is the combination of a gannet optimization algorithm (GOA) and spiking neural network (SNN), hence, it is named as GOA‐SNN technique. The objective of the proposed method is to minimize frequency deviations within the power system (PS). By lessening the frequency‐deviation and tie‐line power variation, this approach ensures system frequency‐control under the effect of load disturbances. The GOA method is utilized to generate the set of control signals of the controller. The SNN method is used to predict the optimum gain parameter of the controller. By then the proposed method is run in MATLAB software and evaluated their performance with various existing approaches. The proposed method shows better results than other existing methods, such as Ant Lion Optimization (ALO), particle swarm optimization (PSO), and Salp Swarm Algorithm (SSA). The GOA‐SNN approach shows a low Area control error is 0.48% and a high efficiency is 96% compared with other existing approaches.