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ANN Based MPPT Applied To Solar PV Powered Water Pumping System Using BLDC Motor

This work introduces non-electrical input based artificial neural network (ANN) maximum power point tracking (MPPT) technique to the solar PV powered water pumping system using brushless DC (BLDC) motor. The objective is to model a step size independent MPPT using neural network for water pumping application. A DC-DC boost converter is being utilized which is driven by ANN based MPPT to extract maximum power from the solar photovoltaic (SPV) array and also responsible for soft starting of BLDC motor. Pulse width modulated (PWM) control of the voltage source inverter (VSI) using DC link voltage controller is used to control the speed of the BLDC motor. PWM signal is generated using the inbuilt encoder to perform the electronic commutation by hall signal sensing. Performance analysis of a BLDC motor driving pump system is carried out under the MATLAB/Simulink environment and efficiency of the overall system is calculated under various irradiance condition.

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The Course on "MATLAB Modelling of Solar PV system explore about following;
1. MATLAB modelling of Solar PV cell and Solar PV Array Using a mathematical equation.
2. How to find I-V and PV Characteristics of the modelled solar PV array in MATLAB.
3. MATLAB Implementation of Maximum Powerpoint Algorithm for solar PV array with a stand-alone system.
4. MATLAB Implementation of solar MPPT charger controller for a solar PV system.
5. MATLAB Implementation of a grid-connected solar PV system.

MATLAB Files included:
Modelling of Solar PV Array

MPPT control of Solar PV Array

MPPT charger controller

Grid-connected solar PV system

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