Optimal Fuel Consumption using Multilevel Inverter-based ANFIS RSC Control Strategy on Wind-Driven DFIG, DG, and Solar PV Array

In this article, a 7-level cascaded Multi-Level Inverter (MLI) and Adaptive neuro-fuzzy inference system (ANFIS) controller are used to optimize fuel consumption of a Diesel Generator (DG) with renewable sources of Wind-driven power Double fed induction generator (DFIG), solar PV array, and Battery energy storage system in a microgrid. The purpose is to produce this microgrid system with a multilevel inverter, employing nearest-level control to lower overall harmonic distortions and reduce bulk filters. It especially combines solar and wind renewable sources, which leads to an increase in output power and voltage. The ANFIS controls wind speed to develop torque with their respective references to improve dynamic performance with generated signals of pulse width modulation (PWM) logic for the Rotor side converter (RSC). Modified perturb and Observe algorithms are used in this Maximum power point tracking (MPPT) for maximum power in the wind and solar output with fewer or no oscillations. Using MATLAB software microgrid is designed and a simulation is done. A transient improvement throughout a large wind speed range can be accomplished by utilizing an ANFIS controller.