Development of Low Cost Intelligent Tracking System Realized on FPGA Technology for Solar Cell Energy Generation

Abstract

This paper presents a development of low-cost intelligence tracking system for Solar (PV) cell energy generation. As well known, the electrical energy as power source is used in several electrical devices and applications. However, the conventional electrical energy has produced from fuels that makes it costly and increasing the pollution level around the world. Solar energy generation has gained significantly attention due to its properties of providing clean energy and replenishing the electrical energy. Nevertheless, the solar energy still considered as high cost technology and produced losses in the solar cell power. Therefore, the proposed low-cost intelligence tracking system is aimed to adjust the PV cell direction toward a sunlight with minimizing the losses in the solar energy generation. The proposed intelligence tracking system is modelled based on PSO algorithm and designed using MATLAB and SIMULINK Software. The PSO Algorithm is useful in utilizing and managing the neural networks to steer the directions and speed of intelligence tracking system. Then the proposed model is implemented on low cost FPGA board circuit. The performance of the proposed model is analysed using MATLAB software. This proposed model would benefit the solar energy applications.