Power Sharing Enhancement of Standalone Microgrid using Primary Control Optimization

This paper introduces a novel optimized droop control employing the Centripetal Force-Gravity Search Algorithm (CF-GSA), a metaheuristic multi-objective evolutionary algorithm. The proposed method aims to enhance droop performance, focusing on power sharing, voltage and frequency stability, and power quality. CF-GSA, specifically designed to address local solution issues common in optimization algorithms, has been demonstrated to be effective and superior through a series of simulations. The simulation results affirm the proposed multi-objective optimization droop control method's capability to rectify issues arising from power sharing errors in isolated AC MGs dealing with high inductive loads and changes in line impedance.