Voltage Stabilization Control for Microgrid with Asymmetric Membership Function-Based Wavelet Petri Fuzzy Neural Network

Voltage stabilization is an important task for the microgrid power control. The long transient response of voltage caused by the grid transition from the grid-connected mode to the islanded mode or the power variations would deteriorate the operation of the voltage protective relay. This would lead to the difficulty of integration for the renewable energy and the storage system. To solve this problem, the asymmetric membership function based wavelet petri fuzzy neural network (AMFWPFNN) controller is proposed for the voltage stabilization control of storage system in this paper to provide fast response speed and mitigate the transient impact. To investigate the performance of the proposed microgrid controller and examine the compliance with the settings in IEC Std. 60255, Cimei Island in Taiwan is studied. Through the hardware in the loop (HIL) mechanism built with OPAL-RT real-time simulator, the effectiveness of proposed controller can be verified.