Abstract
A large-scale study for validating building energy simulation programs against measured data was undertaken within IEA EBC Annex 71 "Building energy performance assessment based on optimized in-situ measurements" as a more complex and realistic successor of the dataset created previously in IEA EBC Annex 58. The validation method consists of a set of high quality measurement data and a precise documentation of all boundary conditions. This enables a user to create a complete model of the different validation scenarios. The results of this model can be compared to the real measurement data. Because of the detailed modelling, the remaining deviations should indicate the limitations of the tool under investigation. The definition of the scenarios consists of extensive weather data and a detailed description of the building geometry, components compositions, thermal bridges, air tightness, ventilation, etc. In addition to the previous Annex 58 dataset this experiment contains synthetic users with internal heat and moisture gains, operated doors and windows and underfloor heating with an air source heat pump. This paper sets out the experimental design, a key element in ensuring a useful experimental dataset.
Original language | English |
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Article number | 22003 |
Number of pages | 9 |
Journal | E3S Web of Conferences |
Volume | 172 |
DOIs | |
Publication status | Published - 30 Jun 2020 |
Event | 12th Nordic Symposium on Building Physics, NSB 2020 - Tallinn, Estonia Duration: 6 Sept 2020 → 9 Sept 2020 https://nsb2020.org/ |
Funding
The German author would like to acknowledge support from the German Federal Ministry Economic Affairs and Energy for funding the experiment and additional parts of the work described in this publication under the reference number 03ET1509A.
Keywords
- whole building
- validation
- simulation programs
- synthetic users
- heating systems
- experimental design
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OccDem - a program to generate statistically-based occupancy and occupant-driven electrical demand profiles.
Flett, G. H. (Creator) & Kelly, N. (Contributor), University of Strathclyde, 2 Mar 2021
DOI: 10.15129/ec5a8dc0-def2-4a07-bf53-a8deefcfcc99
Dataset