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U. Pont, O. Proskurnina, M. Taheri, A. Kropf, B. Sommer, M. Sommer-Nawara, G. Adam, A. Mahdavi:
"Input Data Quality for Building Energy Certification: Recent Progress in the EDEN Project";
Talk: Vienna Young Scientists Symposium 2016, Vienna; 2016-06-09 - 2016-06-10; in: "Proceedings of Vienna Young Scientists Symposium 2016", B. Ullmann, .. TU Wien et al. (ed.); Eigenverlag mit wissenschaftlichem Lektorat / TU Wien, (2016), ISBN: 978-3-9504017-2-1; Paper ID ARP13, 2 pages.

This contribution documents recent progress of the 3rd-party funded EDEN project (Entwicklung einer strukturierten und fehlerminierten Datenaufbereitung und Dokumentation für Energieausweise, FFG-Grant 850101), which explores uncertainties and quality of input data assumptions for building energy certificates. The European Union introduced building energy certification about 15 years ago [1]. Each European state was requested to add energy certificates to their national legislation. Correspondingly, in Austria energy certificates are stipulated by law since 2006[2]. Additionally, a set of rules and guidelines were published [3]. These encompass, rules for calculation, minimum thermal quality of building components for new buildings, and maximum permissible heating demand for new buildings and major retrofits. Moreover, default values for existing building constructions of unknown assembly are included based on the year of construction. However, the existing guidelines do not comprehensively address the input data collection process and the derivation of Key Performance Indicators. Due to different practical approaches in certification and interpretation of guidelines, as well as prevailing uncertainties regarding input data and corresponding assumptions, the explanatory power of energy certificates is reduced. Moreover, regular observations show that buildings are certified differently (different results regarding key performance indicators) by different certificate issuers, even if the same set of input data was utilized. Lacking reproducibility is highly problematic, given that building permits and retrofit subsidy grants are often based on the results of energy certificates [4]. Two major objectives are pursued in the project: i) Performing a sensitivity analysis on different input data assumptions and their effect on resulting key performance indicators within the energy certificate calculation. This encompasses gathering input data that is often prone to errors, and to define a range for the input data variance. Using a sample building database, which includes buildings of different size, usage, and age, the effect of input data variance can be explored comprehensively. ii) Development of a standardized and accurate documentation of input data for energy certificates to ensure a higher degree of reproducibility of energy certificates. Such documentation would improve the legal currency of energy certificates, and reduce errors and manipulation risk.

This contribution documents recent progress of the 3rd-party funded EDEN project (Entwicklung einer strukturierten und fehlerminierten Datenaufbereitung und Dokumentation für Energieausweise, FFG-Grant 850101), which explores uncertainties and quality of input data assumptions for building energy certificates. The European Union introduced building energy certification about 15 years ago [1]. Each European state was requested to add energy certificates to their national legislation. Correspondingly, in Austria energy certificates are stipulated by law since 2006[2]. Additionally, a set of rules and guidelines were published [3]. These encompass, rules for calculation, minimum thermal quality of building components for new buildings, and maximum permissible heating demand for new buildings and major retrofits. Moreover, default values for existing building constructions of unknown assembly are included based on the year of construction. However, the existing guidelines do not comprehensively address the input data collection process and the derivation of Key Performance Indicators. Due to different practical approaches in certification and interpretation of guidelines, as well as prevailing uncertainties regarding input data and corresponding assumptions, the explanatory power of energy certificates is reduced. Moreover, regular observations show that buildings are certified differently (different results regarding key performance indicators) by different certificate issuers, even if the same set of input data was utilized. Lacking reproducibility is highly problematic, given that building permits and retrofit subsidy grants are often based on the results of energy certificates [4]. Two major objectives are pursued in the project: i) Performing a sensitivity analysis on different input data assumptions and their effect on resulting key performance indicators within the energy certificate calculation. This encompasses gathering input data that is often prone to errors, and to define a range for the input data variance. Using a sample building database, which includes buildings of different size, usage, and age, the effect of input data variance can be explored comprehensively. ii) Development of a standardized and accurate documentation of input data for energy certificates to ensure a higher degree of reproducibility of energy certificates. Such documentation would improve the legal currency of energy certificates, and reduce errors and manipulation risk.