Designing multiple inverter systems with evolutionary multiobjective optimisation

Given the growth of microgrids and decentralised power, heterogeneous multi-inverter systems are becoming increasingly prevalent. Despite this, little is known about the interactive effects of such systems and how best to control them. In response, this work examines the use of traditional droop control and a contemporary multiobjective optimisation technique for automatically adapting parameters for a specified load profile in a heterogeneous ten-inverter system. Results indicate that the multiobjective approach offers a range of parameter sets that each outperform the manual droop settings with respect to both voltage sag and ripple objectives.