<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In view of the relatively large energy consumption of national building stocks, many cities and municipalities start to prepare energetic building stock models to monitor energy efficiency and plan policies at city or regional scales. In many cases, data on individual buildings is not available. A usual approach to this is the “archetype” approach – classifying the building stock into energetic types (archetypes). This classification is usually based on non-energetic properties available in digital cadastres (construction type, year of construction etc.) and can be a large source of error. We present our research into the difficulties and pitfalls associated with such an approach using the city of Hamburg as an example. In the end, we compare the modelled estimates with consumption data at three different levels to evaluate model performance.</p></abstract>

In view of the relatively large energy consumption of national building stocks, many cities and municipalities start to prepare energetic building stock models to monitor energy efficiency and plan policies at city or regional scales. In many cases, data on individual buildings is not available. A usual approach to this is the “archetype” approach – classifying the building stock into energetic types (archetypes). This classification is usually based on non-energetic properties available in digital cadastres (construction type, year of construction etc.) and can be a large source of error. We present our research into the difficulties and pitfalls associated with such an approach using the city of Hamburg as an example. In the end, we compare the modelled estimates with consumption data at three different levels to evaluate model performance.

Assigning Energetic Archetypes to a Digital Cadastre and Estimating Building Heat Demand. An Example from Hamburg, Germany

Environmental and Climate Technologies

This work is licensed under the Creative Commons Attribution 4.0 International License.

In view of the relatively large energy consumption of national building stocks, many cities and municipalities start to prepare energetic building stock models...

Assigning Energetic Archetypes to a Digital Cadastre and Estimating Building Heat Demand. An Example from Hamburg, Germany

Online veröffentlicht: 22. Apr. 2020

Seitenbereich: 233 - 253

DOI: https://doi.org/10.2478/rtuect-2020-0014

Schlüsselwörter
energetic archetypes, UBEMs (Urban building energy models), urban heat demand

© 2020 Ivan Dochev et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Assigning Energetic Archetypes to a Digital Cadastre and Estimating Building Heat Demand. An Example from Hamburg, Germany

Online veröffentlicht: 22. Apr. 2020

Seitenbereich: 233 - 253

DOI: https://doi.org/10.2478/rtuect-2020-0014

Schlüsselwörterenergetic archetypes, UBEMs (Urban building energy models), urban heat demand

© 2020 Ivan Dochev et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
energetic archetypes, UBEMs (Urban building energy models), urban heat demand