Experimental studies on efficiency enhancement of the parabolic solar collector combined with mirrors using the artificial neural network

Abstract

ABSTRACT Solar energy has become the most promising renewable energy nowadays. To achieve best possible performance from a solar system, the photovoltaic panel is required to absorb maximum radiation in the possible effective way. More the radiation on panel results in more amount of electricity. The primary goal of the paper is to increase the amount of radiation using mirror and auto tracking arrangement to allow more rays to be concentrated on a small area, i.e. on a photovoltaic panel by introducing a new platform made in a shape of parabolic which is adjusted to follow the sun. Mirrors are going to be attached on a flat shaped frame with the PV panel at an angle of 120°, during the day for the purpose of reflection of maximum amount of radiation on the PV cells. Artificial neural network control is proposed to decide the exact maximum power point while tracking the sun. Due to the mirror effect all the rays will be concentrated on a small area of the photovoltaic panel which is fixed at the focus of the parabola. The nearest position while receiving direct sunlight is considered as the input taken from the database. This process minimises the number of motors for starting and results in reduced quantity of loss of energy in different weather conditions. The comparison has been studied for a fixed PV panel and this new PV panel with mirror and results are tabulated. The results show an increase of 32% in average efficiency by using the mirror and tracking system using the artificial neural networks technique.