The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Citation
Articles | Volume XLII-4/W14
https://doi.org/10.5194/isprs-archives-XLII-4-W14-17-2019
https://doi.org/10.5194/isprs-archives-XLII-4-W14-17-2019
23 Aug 2019
 | 23 Aug 2019

A SCALABLE APPROACH FOR SPATIO-TEMPORAL ASSESSMENT OF PHOTOVOLTAIC ELECTRICITY POTENTIALS FOR BUILDING FAÇADES OF ENTIRE CITIES

C. Braun

Keywords: Renewable energy, Photovoltaic Potential, Building Fac¸ades, Smart City

Abstract. This paper describes results on the development of a completely FOSS-based approach assessing the electricity production potential by building façade PV. To estimate solar irradiation the hemispherical view-shed approach described by (Fu, 1999) was used. Combining it with an approach to dissect walls into regular 3D hyper-points (1-meter spacing) the sun visibility and the sky viewshed throughout the year are calculated. This results in global irradiation per hyper-point. To estimate the economic potential of each façade element an economic model was developed. This is driven by technical parameters of the installation, such as module efficiency, installation and maintenance costs, figures about payback tariffs and envisaged module lifetime. The overall result is a city-wide PV suitability and economic potential map of every building façade.

The processing is based on a city model in CityGML format using the 3DCityDB database and the spatial processing functionalities of PostGIS. A set of Python scripts has been developed as a central control instance and manage parallel processing of queries against the database to achieve scalability and improved performance. We run a case study with approximately 7000 single façade elements which are processed. Since we implemented a parallel computation of the façades running on an 80-core dedicated server machine, the completion for an entire city of about 3 million hyper-points points uses a decent amount of time for the given size of the data set. The chosen approach is highly scalable, robust and can be easily implemented through standard tools and libraries.