A Novel Cooperative Control Technique for Hybrid AC/DC Smart Microgrid Converters

Abstract

This study proposes a novel technique of cooperative control for a distributed hybrid DC/AC Microgrid (MG) by designing a digital Infinite Impulse Response (IIR) filter-based Proportional-Resonant (PR) current controller. This controller adopts an Adaptive Neuro Fuzzy Inference System (ANFIS) trained by Particle Swarm Optimization (PSO) to control inverter output current while tracking Maximum Power Point (MPP). A hybrid ANFIS-PSO extracts maximum power from both inverter and boost converter-based solar Photovoltaics (PVs) systems quickly and with zero oscillation tracking. The proposed PR controller cancels harmonics while achieving high gain at the resonant frequency (grid frequency). The PR controller offers quick reference signal tracking, grid frequency drift adaptation, easy system design, and no steady-state error. Moreover, this investigation features a PR controller frequency-domain analysis. The proposed technique smooths voltage and improves steady-state and transient responses. Cooperative control is implemented on an IEEE 14-bus MG with distributed communication. The findings indicate that the proposed control technique can regulate MG voltage to obtain a more stable voltage profile. The adopted MG, made up of dispersed resources, is crucial for assessing power flow and quality indicators in a smart power grid. Finally, numerical simulation results are utilized to verify the recommended technique.

Keywords

• IEEE 14-bus MG
• proportional resonant controller
• inverters
• digital filters
• DC/DC converter
• adaptive neuro fuzzy inference system