Determination of Optimal Q-V Droop Controller Parameters for Three-Phase Modular UPS System Based on Genetic Algorithm (GA)

Abstract

This paper presents an optimized reactive power-voltage (Q-V) droop controller parameters for three-phase modular uninterruptible power supply (UPS) based on genetic algorithm (GA). The main objective of this paper is to minimize the voltage regulation error when there are changes in loads. In addition to select the control parameters carefully to promote the performance of the system against disturbances. This is substantial to attain power sharing between different UPS units to balance sudden disturbances that happen when there are changes in loads. We propose a discrete proportional-integral controller which compares the output voltage with the reference value given by the droop control loops then generates suitable voltage vector signal to pulse-width modulation (PWM) inverter. The fitness function for the optimization problem is formulated by considering the sum of square errors in voltage. This fitness function converges to local minima during the iterative operation of the genetic algorithm. Thus, the optimal parameters of the voltage droop control can be discovered with great probability. Simulation of two parallel-connected three-phase UPS units are carried out using MATLAB/SIMULINK R2018a. Comparison between the conventional trial and error tuning methods and GA optimization is performed. The results show that GA succeeded to minimize the output voltage root mean square error (RMSE) and to enhance the power sharing capability when there is variation in loads.