New Performance Modeling Techniques for Photovoltaic Modules and Different Types of Wind Turbines

Abstract

Abstract This paper presents new modeling techniques for evaluating the performance of photovoltaic (PV) panels, vertical-axis wind turbines (VAWT), and horizontal-axis wind turbines (HAWT). Two methods are implemented to evaluate and simulate the designed models based on actual data points from various manufacturing manuals. The first technique is based on curve fitting while the artificial neural network (ANN) is the second method. The developed models can predict the operating performance characteristics of PV, VAWT and HAWT based only on the demand power. Hence, it can easily assist the designer to select a suitable unit before the installation process. The PV model can predict the short circuit current, open circuit voltage, voltage and current at maximum power, module efficiency and the module cost for a power range from 5W to 350W per module. Moreover, the wind turbine models can predict the cut-in wind speed, rated speed, rotor diameter, rotor speed, hub height and the turbine cost for a power range of 0.1kW to 100kW for VAWT and from 0.5kW to 8000kW for HAWT. The results show that the ANN method provides a higher match with the actual data compared to the curve fitting method. The models are conducted via Matalb/Simulink.