Solar energy replacing conventional non-renewable energy has been widely implemented around the world. Currently, one of the most challenging problems is how to improve the efficiency of producing solar energy. Before installing solar panels, assessing where solar panels should be placed can significantly benefit panel performance. This study aims to conduct a site selection analysis for solar panel installation using Geographical Information Systems (GIS). The University of Waterloo main campus and the City of Waterloo were selected as study areas for micro-scale and macro-scale, respectively. The focus of the micro-scale analysis is on building rooftop installations, while the macro-scale analysis considers ground-mounted installation at the city-level.
Knowledge about solar gains incident on different land cover types (e.g., urban and farmland) is useful for assessing potential solar energy installation sites in a local area. In this study, Light Detection and Ranging (LIDAR) data were applied to automatically derive accumulated solar radiation energy under clear-sky and overcast conditions at the micro-scale level from which ideal sites for solar panel placement on building rooftops were determined. Macro-scale solar radiation maps were based on Digital Elevation Model (DEM) data using ArcGIS software. Optimal ground-mounted solar panel installation sites were determined using a multi-criteria analysis approach that considered various environmental and socioeconomic factors. A questionnaire survey was distributed to select solar power companies in Southern Ontario to assess current solar panel installation practices, which were then used to better inform and modify the GIS multi-criteria approach. Finally, a feasibility assessment was performed with ground truth information to verify selected sites.
Identifer | oai:union.ndltd.org:WATERLOO/oai:uwspace.uwaterloo.ca:10012/7960 |
Date | 26 September 2013 |
Creators | Li, Dongrong |
Source Sets | University of Waterloo Electronic Theses Repository |
Language | English |
Detected Language | English |
Type | Thesis or Dissertation |
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