Performance Evaluation of EHO and GWO Optimization Techniques for PI Controller Tuning of Boost Converter in Photovoltaic based Microgrid

Boost converters are essential for microgrid systems, facilitating the systematic integration of renewable energy systems and also ensuring efficient energy conversion and reducing voltage mismatches that may occur due to faults, leading to instability and issues in power quality. Closed loop Proportionalintegral (PI) control of the boost converter is crucial to moderate the terminal output voltage of the boost converter according to the application. The main aim of this manuscript is to optimize these PI values to have a more efficient boost converter operation for microgrids. Optimization techniques like elephant herding optimization (EHO) and grey wolf optimization (GWO) have been investigated to obtain a better value of the PI controller for boost converter control and compared with PI controller values obtained by traditional auto tuning. The step response analysis to compare the rise times, peak times, and peak values is performed to have a better comparison between these techniques. Rise time and peak time are approximately 10% and 8% less in the case of GWO compared to EHO, much higher in the case of auto tuning. Also, a comparison regarding different error indices like integral absolute error (IAE), integral of squared error (ISE), and integral time absolute error (ITAE) has been made among these optimization techniques along with the traditional autotuning method through simulation, which will pave the way to choosing a better optimization technique to have an efficient PI controller value and, in turn, an efficient operation of the boost converter for microgrid applications.