Optimization variation for multiple heuristic approaches in solar tracking

Abstract

The solar tracker, a device that keeps PV or photo-thermal panels in an optimum position perpendicular to the solar radiation during daylight hours, increases the collected energy and can be considered as one of the economical renewable energy in generating electricity. The current trend in solar concentrator tracking system is to use an open-loop local controller that computes the direction of the solar vector based on geographical location and time. It is not accurate because it has error from computing the intensity variation. Literature suggested that the photovoltaic panels could produce maximum power if the panels have angle of inclination zero degree to the sun position. In this research, genetic algorithm is one of the optimization techniques used to maximize the performance of solar tracking system. Research shows that among the heuristic approaches within 50 generation, Genetic Algorithm reaches the best fitness value at 0.01706 with optimum voltage 10.05V. © (2011) Trans Tech Publications, Switzerland.