A MPPT-based ANN controller applied to PV pumping system

This paper introduces a maximum power point method (MPPT) based on an artificial neural network (ANN) and a scanning algorithm. The proposed MPPT is applied to pumping system. The system is composed of solar generator, boost converter and centrifugal pump load driven by a DC motor. A complete simula...

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Bibliographic Details
Main Authors: Bouselham, L., Hajji, M., Hajji, B., Bouali, H.
Format: Conference Proceeding
Language:English
Subjects:
Artificial Neural Network (ANN)
Artificial neural networks
Brushless motors
Global Maximum Power Point (GMPP)
Mathematical model
Maximum power point trackers
MPPT
Partial Shading Conditions
PV Pumping System
Time factors
Torque
Training
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Summary:This paper introduces a maximum power point method (MPPT) based on an artificial neural network (ANN) and a scanning algorithm. The proposed MPPT is applied to pumping system. The system is composed of solar generator, boost converter and centrifugal pump load driven by a DC motor. A complete simulation of the system is developed in MATLAB/SIMULINK under different weather conditions. The results obtained verify that the ANN controller shows a significant improvement in the power extraction performance especially in terms of tracking efficiency, when compared with modified Perturb and observe controller, and consequently the quantity of the pumped water gained by the ANN method is higher.
ISSN:2380-7393
DOI:10.1109/IRSEC.2016.7983918