A Comprehensive Comparison Between Boost and Buck-Boost Converters in Solar MPPT With ANN

Abstract

Solar energy is one of the most promising energy sources that can meet the ever-increasing demand for electricity in the world. But due to the lower efficiency of solar photovoltaic (PV) cells and dependency on environmental conditions, it is necessary to track the Maximum Power Point (MPP) of the solar PV system. Hence, different Maximum Power Point Tracking (MPPT) methods are implemented with solar PV systems but one of the main problems associated with maximum power point tracking methods is the designing of a DC-DC converter. This paper depicts a detailed comparison between the performance of a Boost Converter and Buck-Boost converter for the maximum power point tracking of a solar PV system with Artificial Neural Network (ANN) because ANN based MPPT model provides remarkably fast tracking speed and higher efficiency. To understand the designing of a suitable DC-DC converter for MPPT with ANN, for different values of the passive elements in the converter, the response of the DC-DC converters are represented through comparison. All the test results and graphs of this paper were conducted in MATLAB/Simulink environment. The outcome of the simulations will provide a clear conception to the future researchers to predict the behaviours of the mentioned converters and design the most efficient converter accordingly for solar MPPT.