An Adaptive Controller Design using Duelist Optimization Algorithm for an Interconnected Power System

A Controller is generally considered as a continuous and discrete mode of execution by a huge sample period that may result in degenerated dynamic performance or system instability. Nowadays, the maximum penetration in thermal, wind, hydropower systems has decreased the power system inertia that leads to rapid frequency response and higher frequency deviation followed by contingencies and requires rapid load frequency control. The goal of load frequency control (LFC) is to achieve zero steady-state errors in frequency deviations and minimize unscheduled tie-line power flows among the interconnected areas. The study of the literature reveals that a lot of research has been carried out in this area to achieve the desired objectives using different approaches. This manuscript proposes an optimization algorithm called Duelist Optimization Algorithm (DOA) in a three area interconnected power system consisting of thermal, wind, and hydro generating systems. The proposed system introduces an adaptive PID fuzzy controller whose parameters are optimized by the DOA algorithm. The Duelist Optimization algorithm is used to optimally tune the parameters of the controller in order to keep the system frequency deviation within the threshold limit, and maintain the power balance among the control areas during load variations. The proposed method is simulated in MATLAB / Simulink environment for the estimation of its performance and then compared with some of the existing techniques such as Artificial Bee Colony (ABC) optimization algorithm, Bacteria Foraging Optimization (BFO), and Particle Swarm Optimization (PSO) algorithm. The simulation result established the suprerioty of the proposed method over the other methods.