Evaluation of Prescriptive Indicators for Building Performance - A Ranking Based Approach

Abstract:

In recent discussions on the evaluation methodology of different aspects of building performance, the idea of so-called prescriptive indicators was proposed. These indicators are simple benchmark values of a building, and do not require any complex calculation or simulation. They are regularly based on certain design parameters pertaining to geometric or semantic aspects of the building, such as compactness and mean weighted U-value. Their purpose – amongst others – is to equip building planners with a very quick method to estimate the performance of their building designs in early design stages and to categorize its performance. Moreover, such prescriptive indicators could be considered an alternative concept to the current practice of energy certification in Europe. The energy certificate calculation methodologies in most countries did increase in complexity in the past years. As a result, the issuing of energy certificates has become a time-consuming and cumbersome process. Moreover, the quality of results of energy certificates became questioned in recent years due to uncertainties connected to input data assumptions and widely interpretable guidelines regarding the issuing. Prescriptive indicators, if their derivation is properly documented, can at least mitigate the issue regarding issuing guidelines due to their simple character. A important research question, however, is the relation between key performance indicators, which are the results of energy certification or building performance simulation, and prescriptive indicators. This contribution suggests a methodology based on rank comparison that might help to identify prescriptive indicators that are similar in their sensitivity on design changes as certain key performance indicators are.

• Periodical: Applied Mechanics and Materials (Volume 887)
• Pages: 172-180
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.887.172
• Online since: January 2019
• Authors: Ulrich Pont*, Ardeshir Mahdavi
• Keywords: Building Performance Evaluation, Pearson Correlation, Prescriptive Indicators, Ranking, Spearman Rank Correlation

References

[1] EPBD, Energy Performance of Buildings Directive 2002/91/EC of the European Parliament and of the Council of 16 December 2002 on the energy performance of buildings, Directive 2002/91/EC, Belgium: Official European Union Journal.

DOI: 10.1017/cbo9780511610851.032

[2] EPBD, Energy Performance of Buildings Directive 2010/31/EU of the European Parliament and of the Council of 19 Mai 2010 on the energy performance of buildings - recast, Directive 2010/31/EU, Belgium: Official European Union Journal.

DOI: 10.1017/cbo9780511664885.046

[3] OIB Guideline 6 – Energieeinsparung und Wärmeschutz, 03/2015. Österreichisches Institut für Bautechnik OIB – available via www.oib.or.at (last accessed June 2017).

[4] Austrian Standardization Institute (ASI) – ÖNORM B 8110-standard series (parts 1-7): Thermal insulation in building construction.

[5] B. Sommer, U. Pont. Entwicklung einer strukturierten und fehlerminimierten Datenaufbereitung und Dokumentation für Energieausweise (EDEN). Berichte aus Energie- und Umweltforschung 24/2017. Available online via: https://nachhaltigwirtschaften.at/resources/sdz_pdf/berichte/endbericht_2017-24_eden.pdf.

[6] U. Pont, O. Proskurnina, M. Taheri, A. Mahdavi, B. Sommer, M. Sommer-Nawara, and G. Adam. Acquisition and processing of input data for building certification: An approach to increase the reproducability of energy certificates; in: Proceedings of the 11th European Conference on Product and Process Modelling,, S.E. Christodoulou, R.J. Scherer (Ed.); Balkema, (2016), ISBN: 9781138032804; S. 243 - 250.

DOI: 10.4028/www.scientific.net/amm.887.212

[7] B. Sommer, U. Pont, G. Adam, K. Bollinger, A. Kropf, A. Mahdavi, O. Proskurnina, M. Sommer-Nawara, and M. Taheri; Der Einfluss von Default-Werten auf die Ergebnisse von Bestandsenergieausweisen; invited Lecture at 10 Jahre Energieausweis - Rückblick, Ausblick, Erfahrungen aus der Praxis, Wie geht es weiter?, St. Pölten, Lower Austria 14.04.(2016).

DOI: 10.1007/978-3-8348-2181-2_12

[8] QualiCheck-Plattform. http://qualicheck-platform.eu/ (last checked: Aug 2017).

[9] E. Panzhauser. Wärmeschutz im Wohnbau, Wien (1979).

[10] A. Mahdavi and B. Gurtekin. Shapes, Numbers, Perception: Aspects and Dimensions of the Design-Performance Space. 2002. in: Design and Decision Support Systems in Architecture,, (2002), ISBN: 90-6814-141-4; pp.291-300.

[11] W. Pessenlehner and A. Mahdavi. Building morphology, transparence, and energy performance. in: Building Simulation,, (2003), ISBN: 90-386-1566-3 pp.1025-1032.

[12] M. Marković. The potential of descriptive building quality specifications as an alternative to the detailed calculation. Masterthesis, TU Wien, Vienna, Austria, supervised by A. Mahdavi and U. Pont.

[13] M. Marković, U. Pont, A. Mahdavi The potential of descriptive building quality specifications as an alternative to the detailed calculation. Talk at enviBuild 2017, Vienna, Austria, 07. And 08.September (2017).

[14] M. Alhayek. Prescriptive Indicators for usage in Palestine – Approaches to cooling demand (Working title). Master thesis to be finished, TU Wien, Vienna, Austria, supervised by A. Mahdavi and U. Pont (2018).

[15] A. Wadi. Prescriptive Indicators for usage in Palestine – Approaches to heating demand and overheating tendencies (Working title). Master thesis to be finished, TU Wien, Vienna, Austria, supervised by A. Mahdavi and U. Pont (2018).

[16] U. Pont, N. Ghiassi, S. Fenz, J. Heurix, and A. Mahdavi, SEMERGY: Application of Semantic Web Technologies in Performance-Guided Building Design Optimization; www.itcon.org - Journal of Information Technology in Construction, 20 (2015), Special Issue; pp.107-120.

DOI: 10.1201/b17396-38

[17] SEMERGY – available via www.semergy.net (last accessed Aug 2017).

[18] S. Glawischnig. An urban monitoring system for large-scale building energy assessment; Dissertation; Evaluated by A. Mahdavi, S. Dustdar; TU Wien, Institute for Architectural Sciences, Dept. Building Physics and Building Ecology 2016; Rigorosum: 18.03.(2016).

[19] N. Ghiassi. An Hourglass Approach to Urban Energy Computing. Dissertation; Evaluators: A. Mahdavi, H. Rechberger, D. Saelens, J. Page, S. Dustdar; TU Wien, Institute for Architectural Sciences, Dept. Building Physics and Building Ecology 2016; Rigorosum: 15.12.(2017).

[20] U. Pont, D. Latzer, R. Giffinger, and A. Mahdavi. Assessing Energy profiles of urban neighborhoods: A streamlined GIS-based approach. Talk at enviBuild 2017, Vienna, Austria, 07. And 08.September (2017).

DOI: 10.4028/www.scientific.net/amm.887.264

[21] C. Spearman. The proof and measurement of association between two things. American Journal of Psychology. 15: 72–101. 1904.

DOI: 10.2307/1412159

[22] W.W. Daniel. Spearman rank correlation coefficient, in Applied Nonparametric Statistics (2nd ed.). Boston: PWS-Kent. p.358–365. ISBN 0-534-91976-6.

[23] Laerd statistics https://statistics.laerd.com/statistical-guides/spearmans-rank-order-correlation-statistical-guide.php (last accessed in Aug 2017).

[24] Leitfaden zur OIB Guideline 6 – Energieeinsparung und Wärmeschutz, 03/2015. Österreichisches Institut für Bautechnik OIB – available via www.oib.or.at (last accessed June 2017).