Cuk Converter to charge a battery employing ANN Controller based MPPT

Authors: Pooja Naresh Bhatt, Hemant Mehar, Manish Sahajwani

Certificate: View Certificate

Abstract

Solar energy has become an emerging topic for the renewable energy world. The effective utilization of the solar panel and the constant power for small system to big energy system is required. Therefore, it becomes imperative that maximum power should be derived from solar PV panels via Maximum Power Point Tracking (MPPT) which in turn increases its efficiency. In this paper, a PV model has been used to simulate actual PV arrays behavior, and then a Maximum Power Point tracking method using Artificial Neural Network (ANN) is proposed in order to control the on goings of the Cuk Converter. Simulation results show that MPPT method has been carried out which has shown the effectiveness of artificial neural networks controller to draw much energy and fast response against change in working conditions

Introduction

One of the major concerns in the power sector is the day-to-day increasing power demand but the unavailability of enough resources to meet the power demand using the conventional energy sources. Demand has increased for renewable sources of energy to be utilized along with conventional systems to meet the energy demand. It is also required that constant voltage be supplied to the load irrespective of the variation in solar irradiance and temperature. So it is necessary to couple the PV array with a buck boost converter. This converter that has an output voltage magnitude that is either greater than or less than the input voltage magnitude. The system can be used to supply constant stepped up/stepped down voltage to dc loads.