A new modeling technique based on performance data for photovoltaic modules and horizontal axis wind turbines. Issue 3 (June 2018)

• Record Type: Journal Article
• Authors: Sharaf Eldean, Mohamed A; El Shahat, Adel; Soliman, AM
• Is Part Of: Wind engineering. Volume 42:Issue 3(2018)
• Page Start: 209
• Page End: 229
• Publication Date: 2018-06
• Subjects: Photovoltaic -- artificial neural networks -- wind turbines -- modeling and simulation -- MATLAB–Simulink; Wind-pressure -- Periodicals; Winds -- Periodicals; Wind power -- Periodicals; Engineering meteorology -- Periodicals; Pression du vent; Vents; Énergie éolienne; Météorologie appliquée; Engineering meteorology; Wind power; Wind-pressure; Winds; Periodicals; 621.4505
• DOI: 10.1177/0309524X17737052
• Languages: English
• ISSNs: 0309-524X

Abstract

This article proposes new methods of modeling and simulation of photovoltaic and horizontal wind turbine systems. The photovoltaic and horizontal wind turbines are modeled by the use of actual data sheets listed in the lookup table model. Moreover, artificial neural network numerical technique is used to simulate and evaluate the designed systems. The implemented work may help the designer and investor to elect a specified photovoltaic module and/or the horizontal wind turbine according to the demanded power load, thence predicting the operating conditions before the establishment process. The results show good matching with the actual data for the photovoltaic and horizontal wind turbine systems.