Optimal Tilt Angle for PV Modules Using the Neural-Genetic Algorithm Considering Mathematical Model of the Solar Orbit and Position

Abstract

This paper presents a method which combines an artificial neural network and a genetic algorithm (ANNGA) in determining the tilt angle for photovoltaic (PV) modules. First, a Taguchi experiment was used to perform an efficient experimental design and analyze the robustness of the tilt angles for fixed south-facing PV modules. Following, the results from the Taguchi experiment were used as the learning data for an artificial neural network (ANN) model that could predict the tilt angles at discrete levels. Finally, a genetic algorithm method was applied to obtain a robust tilt angle setting of the tilt angle of PV modules with continuous variables. The objective is to maximize the electrical energy of the modules. In this study, three Taiwanese areas were selected for analysis. The position of the sun at any time and location was predicted by the mathematical procedure of Julian dating; then, the solar irradiation was obtained at each site under a clear sky. To confirm the computer simulation results, experimental system are conducted for determining the optimum tilt angle of the modules. The results show that the seasonal optimum angle is 26.4 (deg.) for February-March-April; -9.47(deg.) for May-June-July, 21.32(deg.) for August-September-October and 53.13(deg.) from November-December-January in the Taiwan area.