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

• URL: http://arxiv.org/abs/2012.03690v1
• Date: Mon, 7 Dec 2020 13:45:08 GMT
• Title: An Enriched Automated PV Registry: Combining Image Recognition and 3D Building Data
• Authors: Benjamin Rausch, Kevin Mayer, Marie-Louise Arlt, Gunther Gust, Philipp Staudt, Christof Weinhardt, Dirk Neumann, Ram Rajagopal
• Abstract summary: This paper demonstrates how aerial imagery and three-dimensional building data can be combined to create an address-level PV registry. Our results indicate that our enriched automated registry proves to be useful to validate, update, and complement official registries.
• Score: 6.127530266825379
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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