An Enriched Automated PV Registry: Combining Image Recognition and 3D Building Data

NeurIPS 2020

An Enriched Automated PV Registry: Combining Image Recognition and 3D Building Data

Dec 06, 2020
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While photovoltaic (PV) systems are installed at an unprecedented rate, reliable information on an installation level remains scarce. As a result, automatically created PV registries are a timely contribution to optimize grid planning and operations. This paper demonstrates how aerial imagery and three-dimensional building data can be combined to create an address-level PV registry, specifying area, tilt, and orientation angles. We demonstrate the benefits of this approach for PV capacity estimation. In addition, this work presents, for the first time, a comparison between automated and officially-created PV registries. Our results indicate that our enriched automated registry proves to be useful to validate, update, and complement official registries. Speakers: Benjamin Rausch, Kevin Mayer, Marie-Louise Arlt, Gunther Gust, Philipp Staudt, Christof Weinhardt, Dirk Neumann, Ram Rajagopal

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