Adaptive neuro-fuzzy control of renewable interfacing inverter to maintain smooth power flow and non-linear unbalanced load compensation simultaneously

This paper presents a novel adaptive neuro-fuzzy control approach for the renewable interfacing inverter. The main objective is to achieve smooth power flow and non-linear unbalance load compensation simultaneously, where the conventional proportional-integral (PI) controller may fail due to the rapid change in the dynamics of the highly non-linear system. The combined capability of neuro-fuzzy controller in handling the uncertainties and learning from the processes is proved to be advantageous while controlling the inverter under fluctuating operating conditions. The inverter is able to compensate the harmonics, reactive power and current imbalance of a 3-phase 4-wire non-linear load with generated renewable power injection in to the grid simultaneously. The proposed system is developed and tested in MATLAB/SimPowerSystem(SPS) environment. The simulation results under dynamic operating conditions are provided to demonstrate the effectiveness of proposed control strategy.