Abstract
A dynamic multi-swarm particle swarm optimizer (DMS-PSO) (This research is partially supported by National Natural Science Foundation of China (Grant No.61473266), and China Postdoctoral Science Foundation (Grant No. 2013M541990)) is implemented to tune the gain settings of PI controllers for an autonomous hybrid energy system consisting of wind-turbine, solar photovoltaic, diesel engine, and fuel cell generator, as well as an aqua electrolyzer and energy storage system. The system performance has been verified under three different conditions using experimental data. Simulation results show that the DMS-PSO achieves better suppression of frequency fluctuation than basic particle swarm optimizer and differential evolution algorithm.
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