Abstract
An increase in energy demands and positive public acceptance of clean energy resources have contributed to a growing need for using solar energy in cities. Solar photovoltaic (PV) deployment relies on suitable locations with high solar energy potential. In the urban context, building rooftops are often considered one of the most available locations for solar PV installation. This work demonstrates a new geospatial-method for spatiotemporal modeling and mapping solar energy potential based on a high-resolution (0.2 m) digital surface model (DSM) and solar radiation dataset. The proposed method identifies building rooftops with a high solar energy potential by using the Solar Analyst (SA) model. The results show that 93.5% of the rooftop area has high solar energy potential in the study area. The annual averaged sum of solar irradiation values is estimated to be 1.36 MWh/m2. In addition, the study showed that sloped rooftops facing to the north received up to 30% more incoming solar radiation than other rooftops with different geometry and orientation. The results are validated using recorded energy output data from four existing solar PV systems in the study area. The return on the initial investment of PV systems installation is estimated to be from four to five years.
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