Optimal Droop Control of Distributed Inverters in a Microgrid Under Autonomous Mode Based on Differenial Evolution

The optimal control issue of a microgrid under autonomous mode is more challenging than grid-connected mode because it needs to design some efficient control loops to maintain voltage and frequency at their nominal values even if some sudden changes occur in loads, generations and topology. This paper presents an optimal droop control method for the distributed inverters in a microgrid under autonomous mode based on real-coded differential evolution (DE). The integral time absolute error between the reference voltage and real output voltage and the total harmonic distortion of output voltage are weighted as the fitness used in DE. The effectiveness of the proposed DE-based droop control method is demonstrated by the comparative simulation results of genetic algorithm-based, particle swarm optimization-based methods.