The overall aim of the project was to apply high quality experimental datasets for model validation of the energy and environmental performance of full-scale buildings. Specific objectives were to develop a robust validation methodology, to co-ordinate empirical validation experiments and modelling (as Task Leader in the International Energy Agency EBC Annex 58 project “Reliable building energy performance characterisation based on full scale dynamic measurements”), to analyse the resulting measured and predicted datasets, and to improve analysis techniques for identifying discrepancies between measured and predicted energy performance data.
Simulation programs are routinely used to predict the energy and environmental performance of buildings, yet there is a marked lack of high quality experimental data to attest to their accuracy. Useful datasets have been developed in this project, by leading a Task within a large International Energy Agency project, and developments made in analysing resulting measurements and predictions.
The project was undertaken with the knowledge that there is a marked lack of high quality datasets from real buildings (as opposed to test cells) suitable for validating the dynamic thermal simulation programs that are commonly used in predicting the energy and environmental performance of buildings. The datasets and experimental specification developed in this project are considered to be of high quality and arguably the best currently available for empirical validation based on real buildings. The experiment was undertaken by an experienced experimental team using a well-instrumented test facility. In addition, there was a high level of engagement from modellers world-wide (over 20 sets of modelling predictions; 16 organisations; 12 different programs, both research and commercial), with the developed specification being implemented and thoroughly tested. A comprehensive archive has been published of the experimental datasets and specification documents. This is available for others to test their existing programs and for developers of new programs such as those being developed.
Apart from the detailed final IEA report that has now successfully completed internal and external review, a number of papers have been published on the validation methodology, specification and analysis of measurements against predictions. Others are in preparation.
The validation study has already proved useful for modellers, by allowing certain modelling teams to identify modelling deficiencies, for another modeller team to test their program in development, and for use in training students in modelling techniques. ASHRAE (American Society of Heating, Refrigerating, and Air-Conditioning Engineers) Standard 140 committee has expressed a strong interest in using the dataset and specification documentation. A presentation was made to the Standard 140 committee in June 2015. There is now a major new project in the USA to develop further empirical validation datasets.
The datasets generated in the project have also been used to test advanced sensitivity analysis techniques (journal paper) and for developing new techniques for model validation and calibration (PhD thesis).
|Effective start/end date||8/10/12 → 7/09/15|
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):