A hierarchical methodology for the mesoscale assessment of building integrated roof solar energy systems

• Published in: Renewable energy 2011-11, Vol.36 (11), p.2992-3000
• Main Authors: Jo, J.H., Otanicar, T.P.
• Format: Article
• Language: English
• Subjects: Applied sciences; Building integrated renewable energy; buildings; cities; climate change; computer simulation; Electric potential; Energy; Energy modeling; Exact sciences and technology; Geographic information systems; Green-house-gas emissions; image analysis; Methodology; Object oriented; Photovoltaic cells; Remote sensing; Renewable energy; Solar cells; solar energy; Solar energy systems; Urban energy consumption; urbanization
• ISSN: 0960-1481; 1879-0682
• DOI: 10.1016/j.renene.2011.03.038

Buildings and other engineered structures that form cities are responsible for a significant portion of the global and local impacts of climate change. Consequently, the installation of building integrated renewable energy sources such as photovoltaic or solar thermal systems on building rooftops is being widely investigated. Although the advantages for individual buildings have been studied, as yet there is little understanding of the potential benefits of urban scale implementation of such systems. Here we report the development of a new methodology for assessing the potential capacity and benefits of installing rooftop photovoltaic systems in an urbanized area. Object oriented image analysis and geographical information systems are combined with remote sensing image data to quantify the rooftop area available for solar energy applications and a renewable energy computer simulation is included to predict the potential benefits of urban scale photovoltaic system implementation. The new methodology predicts energy generation potential that can be utilized to meet Arizona’s Renewable Portfolio Standard 2025 renewable energy generation requirements. ► New method assesses the potential capacity of urban-scale rooftop PV systems. ► Object oriented image analysis is combined with geographical information systems. ► 10% of the total electricity demand can be met by the proposed PV systems.