Optimal sizing of pv lighting system using genetic algorithms: Application to a site in south algeria

Abstract

Uncertain renewable energy supplies, load demands, and nonlinear characteristics of some components of photovoltaic (PV) systems make the design problem not easy to solve by classical optimization methods, especially when relevant meteorological data are not available. To overcome this situation, modern methods based on artificial intelligence techniques have been developed for sizing PV systems. In this study, a method for sizing PV lighting systems has been presented; this method is based on genetic algorithms. The method allows determining optimum PV generator size and optimum storage battery capacity that permit minimum system cost with total autonomy of the system. The method has been applied to a PV lighting system with orientation due south and inclination angles from 0 to 90 in Adrar city (south Algeria). Because measured data for the location chosen were not available, a year of synthetic hourly meteorological data of this location, generated by the PVSYST software, have been used in thesimulation.