SHADOW EFFECT ON PHOTOVOLTAIC POTENTIALITY ANALYSIS USING 3D CITY MODELS

Abstract

Due to global warming, green-house effect and various other drawbacks of existing energy sources, renewable energy like Photovoltaic system is being popular for energy production. The result of photovoltaic potentiality analysis depends on data quality and parameters. Shadow rapidly decreases performance of the Photovoltaic system and it always changes due to the movement of the sun. Solar radiation incident on earth's atmosphere is relatively constant but the radiation at earth's surface varies due to absorption, scattering, reflection, change in spectral content, diffuse component, water vapor, clouds and pollution etc. In this research, it is being investigated that how efficiently real-time shadow can be detected for both direct and diffuse radiation considering reflection and other factors in contrast with the existing shadow detection methods using latest technologies and what is the minimum quality of data required for this purpose. Of course, geometric details of the building geometry and surroundings directly affect the calculation of shadows. In principle, 3D city models or point clouds, which contain roof structure, vegetation, thematically differentiated surface and texture, are suitable to simulate exact real-time shadow. This research would develop an automated procedure to measure exact shadow effect from the 3D city models and a long-term simulation model to determine the produced energy from the photovoltaic system. In this paper, a developed method for detecting shadow for direct radiation has been discussed with its result using a 3D city model to perform a solar energy potentiality analysis.