API for automated, fast, and accurate readout of Energy Performance Certificates (EPCs)

Matthias Lehner and Wolfgang Brunauer

ERES from European Real Estate Society (ERES)

Abstract: Energy performance certificates (EPCs) exist for real estate objects in many countries around the world. These documents represent a rich source of real estate information for both residential and commercial properties. Depending on the country, energy performance certificates provide detailed information on energy efficiency and pollutant emissions, as well as a wide variety of other useful data: Information on location, usage profile, year of construction, time of the last change (e.g., year of refurbishment), geometric information (lengths, areas, volumes), temperature-, climate-, heat- and ventilation-related information, information on energy generation and storage as well as information on the validity duration and the issuer. For many applications, it would be desirable to have this data available in a structured, digital form for a large number of properties. For certain applications, for example, to meet legal requirements in the area of environmental, social, and governance (ESG), having this data is mandatory. Reading this data manually from energy performance certificates proves to be very time-consuming, expensive and error-prone: Hundreds of, e.g., numerical values may have to be read out and written down without errors over a period of hours. In order to extract this data easily, quickly, cheaply and with high accuracy, DataScience Service GmbH (DSS), a real estate software company based in Vienna, Austria, has developed an application programming interface (API) that extracts all data of interest from EPCs automatically. Being able to make this data available quickly for a large number of properties opens up many possibilities for answering scientific and engineering questions in real estate economics, urban planning, energy & environmental science, and building physics, and also provides opportunities for developing practical applications in the real estate and energy industry. In this talk, we will provide a brief introduction to the API we developed for the Austrian market, which can be readily extended to support EPCs of other countries depending on market demand.

Keywords: Energy Efficiency; Energy Performance Certificate; EPC; Machine Learning (search for similar items in EconPapers)
JEL-codes: R3 (search for similar items in EconPapers)
Date: 2023-01-01
New Economics Papers: this item is included in nep-ene and nep-env
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