Frequency Control of Hybrid Power Systems by Optimized Adaptive Fuzzy Controllers

Abstract

Increasing power demand and gradual addition of intermittent renewable generating sources to the conventional grid cause a serious drawback in modern power system like frequency instability. This primarily motivates to do further research on the issue of power system frequency control by applying Artificial Intelligence (AI) techniques and novel controllers to manage the Load Frequency Control (LFC). An intelligent LFC mechanism maintains the power system dynamic stability by diminishing peak overshoot/undershoot and settling time of frequency deviation for numerous system disturbances.The performance of the LFC scheme is governed by the controller structure and AI techniques. In this context, novel modified AI techniques and new controller structures are proposed. Modified Salp Swarm Algorithm (mSSA), Sine adapted Whale Optimization Algorithm (SiWOA), Sine Cosine adapted Harris Hawks Optimization (SCaHHO)technique and a modified Moth Flame Optimization (mMFO) technique are the soft computing techniques proposed in the thesis. In order to handle the complexity of modern power system, the role of intelligent controller is also foremost. So,manyintelligentcontrol approaches like Fractional Order Adaptive Fuzzy Proportional Integral Derivative controller with Filter (FOAFPIDF), Adaptive Fuzzy Proportional Integral Derivativecontroller (AFPID), Adaptive Fuzzy Proportional Integral Derivative-I (AFPID-I) controller, Adaptive Fuzzy Proportional Integral Derivative-II (AFPID-II)controller and Fractional Order Fuzzy Precompensated Proportional Derivative Proportional Integral (FO-FPPDPI)controller is proposed in this research work.Several Hybrid Power System (HPS) structures and interconnected two area conventional power system are considered for the validation of newly proposed LFC schemes. newlineA modified salp swarm algorithm technique is suggested for optimal tuning of an intelligent load frequency controller using FOAFPIDF.