MATLAB Implementation of ANN Based MPPT Applied to Solar PV Powered Water Pumping System Using BLDC
Introduction
We explore the implementation of an Artificial Neural Network (ANN) based Maximum Power Point Tracking (MPPT) system applied to a solar photovoltaic (PV) powered water pumping system using a Brushless DC (BLDC) motor.
System Overview
The proposed system consists of:
A solar PV panel
A DC-DC boost converter
A three-phase voltage inverter
A BLDC motor for water pumping
The ANN MPPT receives solar radiation and cell temperature as inputs to determine the reference voltage at the maximum power point.
Key Components and Design
The BLDC motor specifications include:
Rated voltage: 48V
Rated power: 500W
Rated speed: 3000 RPM
The motor design is informed by standard manufacturer specifications, including torque constants and resistance values.
Control Mechanism
The system uses a PA controller to generate the duty cycle needed for the DC-DC converter.
The output from the H sensor and voltage measurements is processed to maintain the desired operational voltage, ensuring the motor operates efficiently.
Simulation and Results
The system is simulated in MATLAB with varying radiation conditions.
At different irradiance levels (1000W/m² and 500W/m²), the system successfully maintains the converter voltage at 60V while adjusting the power output and rotor speed of the BLDC motor, demonstrating effective power tracking capabilities.
Conclusion
This MATLAB implementation of an ANN-based MPPT for a solar PV powered water pumping system highlights the efficiency and adaptability of the system under varying solar conditions.
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