Effective Control of Voltage and Frequency in Microgrid Using Adjustment of PID Coefficients by Metaheuristic Algorithms

Abstract

Controlling of voltage and frequency in the microgrid is a challenging issue and many controllers are suggested for this purpose. Proportional-Integral-Derivative (PID) controller is simple and efficient when its coefficients are optimally adjusted. Recently, evolutionary algorithms are used to optimally adjust the PID coefficients. In this paper, four evolutionary algorithms, particle swarm optimization, genetic algorithm, imperialist competitive algorithm and selfish herd optimization, are applied to set the PID controller coefficients and tested in the frequency and voltage control of the microgrid. Settling time, overshoot and stability margin are three main factors in the control response of PID which are considered for generating the fitness function to be optimized in terms of the PID coefficients. The proposed microgrid includes inverter-based distributed generators and different loads. Load change and different faults may cause the degradation of frequency and voltage where using of the PID controller leads to better control of these parameters. Simulation results show the efficiency of all four algorithms where particle swarm optimization performance is better than other three algorithms. Experimental results also verify the simulation results discussed in the paper.