Downloads
DOI:
https://doi.org/10.47982/jfde.2022.1.06Keywords:
Adaptive building envelope, Empirical validation, Co-simulation, Outdoor test facility, In-situ characterisationAbstract
The thermal performance of adaptive building envelopes can be evaluated using building performance simulation tools. Simulation capabilities and accuracy in predicting the dynamic behaviour of adaptive building envelopes can be enhanced through co-simulation. However, it is unclear how accurately co-simulation can predict the performance of adaptive building envelopes and how the accuracy of adaptive building envelope models created in co-simulation setups can be assessed and validated. Therefore, this study presents new evidence on the empirical validation of co-simulation setups for adaptive building envelopes by establishing an assessment framework to determine the extent to which they can accurately represent the real world. The framework was applied to a case study to validate a co-simulation setup for a blind automation system using monitored data from MATELab, a full-scale outdoor test facility with realistic indoor and outdoor conditions. The validation of the co-simulation model of MATELab resulted in a median CV-RMSE index, a measure of model accuracy, of 5.9%. This indicates that the simulated data points have a small variance relative to the measured data points, showing a good model fit. In the future, modellers from the façade community can use the assessment framework for their co-simulation setups.
How to Cite
Published
Issue
Section
License
Copyright (c) 2022 Esther Borkowski, Alessandra Luna Navarro, Michalis Michael, Mauro Overend, Dimitrios Rova, Rokia Raslan
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors or their institutions retain copyright to their publications without restrictions.
References
American Society of Heating, Refrigerating and Air-Conditioning Engineers. (2014). ASHRAE Guideline 14-2014: Measurement of Energy and Demand Savings. Atlanta, GA, USA: ASHRAE.
American Society of Heating, Refrigerating and Air-Conditioning Engineers. (2017). 2017 ASHRAE Handbook—Fundamentals (SI Edition). ASHRAE.
Asdrubali, F., Baldinelli, G., & Bianchi, F. (2012). A quantitative methodology to evaluate thermal bridges in buildings. Applied Energy, 97, 365–373. https://doi.org/10.1016/j.apenergy.2011.12.054
Attia, S., Bilir, S., Safy, T., Struck, C., Loonen, R., & Goia, F. (2018). Current trends and future challenges in the performance assessment of adaptive façade systems. Energy and Buildings, 179, 165–182. https://doi.org/10.1016/j.enbuild.2018.09.017
Attia, S., Hensen, J., Beltrán, L., & De Herde, A. (2012). Selection criteria for building performance simulation tools: Contrasting architects’ and engineers’ needs. Journal of Building Performance Simulation, 5(3), 155–169. https://doi.org/10.1080/19401493.2010.549573
Big Ladder Software & Rocky Mountain Institute. (2016). Elements. Retrieved from https://bigladdersoftware.com/projects/elements/
Borkowski, E., Donato, M., Zemella, G., Rovas, D., & Raslan, R. (2019). Optimisation Of Controller Parameters For Adaptive Building Envelopes Through A Co-Simulation Interface: A Case Study. Proceedings of Building Simulation 2019: 16th Conference of IBPSA. Rome, Italy.
British Standards Institution. (1999). BS EN 13187:1999: Thermal performance of buildings. Qualitative detection of thermal irregularities in building envelopes. Infrared method. British Standards Institution. Retrieved from https://bsol.bsigroup.com/en/Bsol-Item-Detail-Page/?pid=000000000001569434
British Standards Institution. (2001). BS EN 13829:2001: Thermal performance of buildings. Determination of air permeability of buildings. Fan pressurization method. British Standards Institution. Retrieved from https://bsol.bsigroup.com/en/Bsol-Item-Detail-Page/?pid=000000000019983036
British Standards Institution. (2015). BS EN ISO 6781-3:2015: Performance of buildings. Detection of heat, air and moisture irregularities in buildings by infrared methods. Qualifications of equipment operators, data analysts and report writers. British Standards Institution. Retrieved from https://bsol.bsigroup.com/en/Bsol-Item-Detail-Page/?pid=000000000030259341
British Standards Institution. (2017a). BS EN 15232-1:2017: Energy Performance of Buildings. Impact of Building Automation, Controls and Building Management. Modules M10-4,5,6,7,8,9,10. British Standards Institution.
British Standards Institution. (2017b). BS ISO 19467: 2017: Thermal performance of windows and doors. Determination of solar heat gain coefficient using solar simulator. British Standards Institution. Retrieved from https://bsol.bsigroup.com/en/Bsol-Item-Detail-Page/?pid=000000000030294394
Broman, D., Brooks, C., Greenberg, L., Lee, E., Masin, M., Tripakis, S., & Wetter, M. (2013). Determinate composition of FMUs for co-simulation. Proceedings of the International Conference on Embedded Software (EMSOFT), 1–12. Montréal, Canada: IEEE Press.
Cattarin, G., Causone, F., Kindinis, A., & Pagliano, L. (2016). Outdoor test cells for building envelope experimental characterisation – A literature review. Renewable & Sustainable Energy Reviews, 54, 606–625. https://doi.org/10.1016/j.rser.2015.10.012
Chartered Institution of Building Services Engineers. (2000). Testing Buildings for Air Leakage - CIBSE Technical Memoranda TM23: 2000. Chartered Institution of Building Services Engineers.
Chartered Institution of Building Services Engineers. (2015). CIBSE Guide A: Environmental design. London, UK: Chartered Institution of Building Services Engineers.
Coakley, D., Raftery, P., & Keane, M. (2014). A review of methods to match building energy simulation models to measured data. Renewable and Sustainable Energy Reviews, 37, 123–141. https://doi.org/10.1016/j.rser.2014.05.007
Dassault Systèmes. (2018). Dymola. Lund, Sweden. Retrieved from https://www.3ds.com/productsservices/catia/products/dymola
de Wit, S., & Augenbroe, G. (2002). Analysis of uncertainty in building design evaluations and its implications. Energy and Buildings, 34(9), 951–958. https://doi.org/10.1016/S0378-7788(02)00070-1
Department of Energy. (2018). EnergyPlus v9.0.1 Documentation—Application Guide for EMS. Department of Energy.
Dervishi, S., & Mahdavi, A. (2012). Computing diffuse fraction of global horizontal solar radiation: A model comparison. Solar Energy, 86(6), 1796–1802. https://doi.org/10.1016/j.solener.2012.03.008
Digital Technology Group. (n.d.). DTG weather station.
Duffie, J. A. (2013). Solar Engineering of Thermal Processes (4th ed.). Somerset: John Wiley & Sons, Incorporated.
Erbs, D. G., Klein, S. A., & Duffie, J. A. (1982). Estimation of the diffuse radiation fraction for hourly, daily and monthly-average global radiation. Solar Energy, 28(4), 293–302. https://doi.org/10.1016/0038-092X(82)90302-4
Favoino, F., Fiorito, F., Cannavale, A., Ranzi, G., & Overend, M. (2016). Optimal control and performance of photovoltachromic switchable glazing for building integration in temperate climates. Applied Energy, 178, 943–961. https://doi.org/10.1016/j.apenergy.2016.06.107
Federal Energy Management Program. (2008). M&V Guidelines: Measurement and Verification for Federal Energy Projects (Version 3.0). Retrieved from https://www.hud.gov/sites/documents/DOC_10604.PDF
Goia, F., & Serra, V. (2018). Analysis of a non-calorimetric method for assessment of in-situ thermal transmittance and solar factor of glazed systems. Solar Energy, 166, 458–471. https://doi.org/10.1016/j.solener.2018.03.058
Hafner, I., Rössler, M., Heinzl, B., Körner, A., Breitenecker, F., Landsiedl, M., & Kastner, W. (2012). Using BCVTB for Co-Simulation between Dymola and MATLAB for Multi-Domain Investigations of Production Plants. Proceedings of the 9th International Modelica Conference. Munich, Germany. https://doi.org/10.3384/ecp12076557
Hensen, J., Loonen, R., Archontiki, M., & Kanellis, M. (2015). Using building simulation for moving innovations across the ‘valley of death’. REHVA Journal, 52(3), 58–62.
Hunter, J. D. (2007). Matplotlib: A 2D Graphics Environment. Computing in Science & Engineering, 9(3), 90–95. https://doi.org/10.1109/MCSE.2007.55
International Organization for Standardization Technical Committee 163/SC 2, C. methods. (2008). Energy performance of buildings—Calculation of energy use for space heating and cooling (2nd ed.: 2008-03–01). Geneva: ISO.
Jensen, S. Ø. (1995). Validation of building energy simulation programs: A methodology. Energy and Buildings. https://doi.org/10.1016/0378-7788(94)00910-C
Judkoff, R., & Neymark, J. (2006). Model validation and testing: The methodological foundation of ASHRAE Standard 140. ASHRAE Transactions.
Lawrence Berkeley National Laboratory. (2019). BuildingsPy. Retrieved from http://simulationresearch.lbl.gov/modelica/buildingspy/
Lomas, K. J., Eppel, H., Martin, C. J., & Bloomfield, D. P. (1997). Empirical validation of building energy simulation programs. Energy and Buildings, 26(3), 253–275. https://doi.org/10.1016/S0378-7788(97)00007-8
Loonen, R., Favoino, F., Hensen, J., & Overend, M. (2017). Review of current status, requirements and opportunities for building performance simulation of adaptive facades. Journal of Building Performance Simulation, 10(2), 205–223. https://doi.org/10.1080/19401493.2016.1152303
Loonen, R., Trčka, M., Cóstola, D., & Hensen, J. (2013). Climate adaptive building shells: State-of-the-art and future challenges. Renewable and Sustainable Energy Reviews, 25, 483–493. https://doi.org/10.1016/j.rser.2013.04.016
Loutzenhiser, P. G., Maxwell, G. M., & Manz, H. (2007). An empirical validation of the daylighting algorithms and associated interactions in building energy simulation programs using various shading devices and windows. Energy. https://doi.org/10.1016/j.energy.2007.02.005
Luna-Navarro, A., Gaetani, I., Anselmo, F., Law, A., & Overend, M. (2021). The influence of occupant behaviour on the energy performance of single office space with adaptive facades: Simulation versus measured data. Proceedings of Building Simulation Conference 2021. Ghent, Belgium.
Luna-Navarro, A., & Overend, M. (2021). Design and validation of MATELab: A novel full-scale test room for investigating occupant perception to and interaction with façade technologies. Building and Environment, 203, 108092. https://doi.org/10.1016/j.buildenv.2021.108092
Madsen, H., Bacher, P., Bauwens, G., Deconinck, A.-H., Reynders, G., Roels, S., … Lethé, G. (2016). IEA EBC Annex 58, Report of Subtask 3, part 2: Thermal performance characterisation using time series data – statistical guidelines. Leuven, Belgium: KU Leuven. Retrieved from https://www.iea-ebc.org/Data/publications/EBC_Annex_58_Final_Report_ST3b.pdf
Martínez, S., Erkoreka, A., Eguía, P., Granada, E., & Febrero, L. (2019). Energy characterization of a PASLINK test cell with a gravel covered roof using a novel methodology: Sensitivity analysis and Bayesian calibration. Journal of Building Engineering, 22, 1–11. https://doi.org/10.1016/j.jobe.2018.11.010
Modelica Association. (2017). Modelica. Linköping, Sweden. Retrieved from https://www.modelica.org
MODELISAR. (2014). FMI Standard for co-simulation. Retrieved from https://fmi-standard.org
Moinard, S., & G.Guyon. (1999). IEA Task 22: Empirical validation of EDF ETNA and GENEC test-cell models.
National Renewable Energy Laboratory. (2018). EnergyPlus. Golden, CO, USA: DOE. Retrieved from https://github.com/NREL/EnergyPlus
Neymark, J., Judkoff, R., Knabe, G., Le, H.-T., Dürig, M., Glass, A., & Zweifel, G. (2002). Applying the building energy simulation test (BESTEST) diagnostic method to verification of space conditioning equipment models used in whole-building energy simulation programs. Energy and Buildings, 34(9), 917–931. https://doi.org/10.1016/S0378-7788(02)00072-5
Nouidui, T., Lorenzetti, D. M., & Wetter, M. (2020). EnergyPlusToFMU. Berkeley, CA, USA: LBNL. Retrieved from http://simulationresearch.lbl.gov/fmu/EnergyPlus/export/index.html
Office of the Deputy Prime Minister. (2006). Conservation of fuel and power: Approved Document L.
Python Software Foundation. (2020). Python. Wilmington, NC, USA. Retrieved from https://www.python.org/
Roels, S. (2012). Annex 58—Reliable Building Energy Performance Characterisation Based on Full Scale Dynamic Measurements. The International Energy Agency.
Ruiz, G. R., & Bandera, C. F. (2017). Validation of Calibrated Energy Models: Common Errors. Energies, 10(1587), 1–19. https://doi.org/10.3390/en10101587
Saelens, D., & Reynders, G. (2016). Report of Subtask 4b: Towards a characterisation of buildings based on in situ testing and smart meter readings and potential for applications in smart grids.
Sargent, R. G. (2013). Verification and validation of simulation models. Journal of Simulation, 7(1), 12–24. https://doi.org/10.1057/jos.2012.20
Tabadkani, A., Tsangrassoulis, A., Roetzel, A., & Li, H. X. (2020). Innovative control approaches to assess energy implications of adaptive facades based on simulation using EnergyPlus. Solar Energy, 206, 256–268. https://doi.org/10.1016/j.solener.2020.05.087
Taveres-Cachat, E., Favoino, F., Loonen, R., & Goia, F. (2021). Ten questions concerning co-simulation for performance prediction of advanced building envelopes. Building and Environment, 191, 107570-. https://doi.org/10.1016/j.buildenv.2020.107570
Taveres-Cachat, E., & Goia, F. (2020). Co-simulation and validation of the performance of a highly flexible parametric model of an external shading system. Building and Environment, 182, 107111-. https://doi.org/10.1016/j.buildenv.2020.107111
Tian, W. (2013). A review of sensitivity analysis methods in building energy analysis. Renewable & Sustainable Energy Reviews, 20, 411–419. https://doi.org/10.1016/j.rser.2012.12.014
Trčka, M., Wetter, M., & Hensen, J. (2009). An implementation of co-simulation for performance prediction of innovative integrated HVAC systems in buildings. 724–731. Glasgow, Scotland: Lawrence Berkeley National Laboratory.
Yang, J. (2011). Convergence and uncertainty analyses in Monte-Carlo based sensitivity analysis. Environmental Modelling & Software, 26(4), 444–457. https://doi.org/10.1016/j.envsoft.2010.10.007
Zhang, Y. (2012). Use jEPlus as an efficient building design optimisation tool. Presented at the CIBSE ASHRAE Technical Symposium, London, UK. London, UK. Retrieved from http://www.jeplus.org/wiki/lib/exe/fetch.php?media=docs:072v1.pdf