Application of ANN for MPP Algorithm of PV Brushless DC-Motor Powered Water Pumping System

In this article, an Artificial Neural Network (ANN)-based maximum power point tracking (MPPT) approach is presented for a photovoltaic (PV) powered brushless DC-motor for a water pumping structure. The ANN model offers control gain for the MPPT regulator. It estimates the duty ratio of a DC-DC boost converter to achieve maximum power generation from solar photovoltaic (SPV) modules. The velocity is managed by the voltage source inverter (VSI) of the BLDC motor. using pulse width modulator (PWM) and a DC-link voltage regulator. Simulation investigations are performed utilizing the SimulinkiMATLAB environment. The effectiveness of the suggested ANN-based MPPT technique is examined in terms of current, voltage and torque ripples, efficiency and MPP settling time to prove its feasibility and effectiveness. simulation results demonstrate that ANN system could quickly track the peak power of the SPV under a variety of radiation conditions.