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An automated model for rooftop PV systems assessment in ArcGIS using LIDAR

1 John & Willie Leone Department of Energy and Mineral Engineering, The Pennsylvania State University, University Park, PA 16802, United States;
2 Department of Geography, The Pennsylvania State University, University Park, PA 16802, United States

Special Issues: Remote sensing and Geoinformation Technology to Explore and Predict Renewable Energy Potential

As photovoltaic (PV) systems have become less expensive, building rooftops have come to be attractive for local power production. Identifying rooftops suitable for solar energy systems over large geographic areas is needed for cities to obtain more accurate assessments of production potential and likely patterns of development. This paper presents a new method for extracting roof segments and locating suitable areas for PV systems using Light Detection and Ranging (LIDAR) data and building footprints. Rooftop segments are created using seven slope (tilt), ve aspect (azimuth) classes and 6 different building types. Moreover, direct beam shading caused by nearby objects and the surrounding terrain is taken into account on a monthly basis. Finally, the method is implemented as an ArcGIS model in ModelBuilder and a tool is created. In order to show its validity, the method is applied to city of Philadelphia, PA, USA with the criteria of slope, aspect, shading and area used to locate suitable areas for PV system installation. The results show that 33.7% of the buildings footprints areas and 48.6% of the rooftop segments identi ed is suitable for PV systems. Overall, this study provides a replicable model using commercial software that is capable of extracting individual roof segments with more detailed criteria across an urban area.
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Keywords GIS; LIDAR; rooftop segmentation; photovoltaic systems; site suitability

Citation: Mesude Bayrakci Boz, Kirby Calvert, Je rey R. S. Brownson. An automated model for rooftop PV systems assessment in ArcGIS using LIDAR. AIMS Energy, 2015, 3(3): 401-420. doi: 10.3934/energy.2015.3.401


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Copyright Info: 2015, Mesude Bayrakci Boz, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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