Researchers at Ecole Polytechnique Fédérale de Lausanne (EPFL) in Switzerland are using machine learning algorithms, geographical information systems, and physical models to estimate the overall photovoltaic (PV) potential of Swiss rooftops to help the country transition to a low-carbon energy system.
The algorithms account for parameters such as the size of each roof, its orientation, and whether the building is in a city center or a more isolated location.
The researchers found solar PV panels could be fitted to 55% of Switzerland's total rooftop area, but even if panels were installed only on mainly south-facing rooftops, they still could provide more than 40% of the country’s electricity demand.
From EPFL (Switzerland)
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Abstracts Copyright © 2020 SmithBucklin, Washington, DC, USA
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