A Resilience-Oriented Bidirectional ANFIS Framework for Networked Microgrid Management

This study implemented a bidirectional artificial neuro-fuzzy inference system (ANFIS) to solve the problem of resilience in synchronized and islanded grid mode/operation (during normal operation event catastrophic disaster, respectively). Included this setup are photovoltaics, wind turbines, batteries, smart load management. Solar panels, battery-charging supercapacitors just few sustainable energy sources ANFIS coordinates. The first step process was development mode-specific control algorithm address system’s current behavior. Relative will take over greatly boost during times crisis, power savings, routine operations. A converter connects battery order keep DC link stable allow displacement due changes generation consumption. When combined with algorithm, PV can be used meet precise needs. means it safeguard from extreme conditions such as overcharging or discharging. is optimized for an island environment perform designed. efficiency life batteries both improve. Improvements inverter’s functionality attributed use synchronous reference frame transformation control. Based on available solar power, state charge (SOC), anticipated fuzzy rule-based over. Furthermore, compared ANFIS. uses MATLAB/Simulink demonstrate robustness under test.