Solar Powered Brushless DC Motor enhanced by Maximum Power Point Tracking Algorithm and Artificial Neural Network

Abstract

Solar energy is a sole form of renewable energy sources that has a high demand of utilization for copious environmental benefits. The varied benefits include its sustainability and inexhaustible nature due its natural source of energy unlike the finite sources of non-renewable sources of energy. It's usage also eliminates the need for and additional power generation which has lead to the fast promotion of solar powered based systems. Being generated from a natural source of energy, it is a clean, non-polluting and of great abundance in nature that makes solar energy used for multitude applications. Maximum Power Point Tracking (MPPT) techniques are employed in Photovoltaic(PV) systems for optimizing the solar PV panels and for maximum power extraction. Among the different MPPT algorithms developed, the Incremental Conductance(InC) is conventionally used for its numerous advantages over the other algorithms. In this project, a Brushless DC motor is proposed rather than the conventional DC motor which is driven by the power delivered by the solar panel and extracting this power efficiently by using Incremental Conductance (InC) algorithm and Artificial Neural Network (ANN).