Power control based on particle swarm optimization of grid-connected inverter for hybrid renewable energy system

• Three PSO-based PI controllers for a grid-connected inverter were presented.
• Two online PSO-based PI controllers were compared with an offline PSO-tuned PI.
• The HRES and the inverter were evaluated under power changes and grid voltage sags.
• Online ITAE-based PSO reduced ITAE (current THD) by 15.24% (5.32%) versus offline one.

This paper is focused on the study of particle swarm optimization (PSO)-based PI controllers for the power control of a grid-connected inverter supplied from a hybrid renewable energy system. It is composed of two renewable energy sources (wind turbine and photovoltaic – PV – solar panels) and two energy storage systems (battery and hydrogen system, integrated by fuel cell and electrolyzer). Three PSO-based PI controllers are implemented: (1) conventional PI controller with offline tuning by PSO algorithm based on the integral time absolute error (ITAE) index; (2) PI controllers with online self-tuning by PSO algorithm based on the error; and (3) PI controllers with online self-tuning by PSO algorithm based on the ITAE index. To evaluate and compare the three controllers, the hybrid renewable energy system and the grid-connected inverter are simulated under changes in the active and reactive power values, as well as under a grid voltage sag. The results show that the online PSO-based PI controllers that optimize the ITAE index achieves the best response.