Intelligent control of islanded AC microgrids based on adaptive neuro-fuzzy inference system

In inverter-based AC microgrids, active power sharing between Distributed Generation (DG) units is achieved by introducing a droop frequency control for the inverter. The purpose of the secondary controller is to regulate the frequency deviation caused by the primary controller while maintaining the droop characteristic of active power sharing among DG units. In this paper, Adaptive Neuro-Fuzzy Inference System (ANFIS) is employed to effectively control frequency and power sharing among DG units in a 100% renewable based microgrid while working in different areas of the operating points. Rules and configuration of ANFIS are introduced to handle the complexity of larger microgrids. The effectiveness of the proposed method is demonstrated in two case studies. The simulation results suggest that the proposed ANFIS controller, compared to the conventional controllers, is able to satisfy the power sharing among DG units while better regulating the frequency.

Automated summary

In this paper, an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is used to achieve frequency and power sharing among DG units in inverter-based AC microgrids, demonstrating its effectiveness. The results of two case studies show that the proposed ANFIS controller can better regulate frequency and meet the power sharing requirements among DG units compared to conventional controllers.