Two Different Approaches of Applying ANFIS Based MPPT for a PV Water Pumping System with a SEPIC Converter

Abstract

The main objective of this work is to enhance the performance of the Photovoltaic water pumping system to cover the water requirement in rural areas. To do so, it is important to make sure that the PV array produces its maximum power at all times, which can be influenced by external condition (mainly the temperature and irradiation). Hence, we are employing the Adaptive Neuro-Fuzzy Inference System based MPPT in two ways. The ANFIS controller is considered more accurate and efficient as it uses an artificial neural network to learn from training data and generate fuzzy rules based on that data. Both approaches of ANFIS are used to control the duty cycle of the SEPIC converter, which connects the PV panel to the DC motor feeding the water pump. The system combining the PV panel, the SEPIC converter, the controller and the DC motor, is designed and simulated under MATLAB/Simulink. The performance of the proposed methods is tested under various meteorological conditions.