Coupling BIM and detailed modelica simulations of HVAC systems in a common data environment

References

• Andriamamonjy, A. 2018. “Automated Workflows for Building Design and Operation using OpenBIM and Modelica.” PhD thesis, KU Leuven.
   Google Scholar
• Andriamamonjy, A., D. Saelens, and R. Klein. 2018. “An Auto-deployed Model-based Fault Detection and DiagnosisApproach for Air Handling Units Using BIM and Modelica.” Automation in Construction96:508–526. https://doi.org/10.1016/j.autcon.2018.09.016.
   Web of Science ®Google Scholar
• Andriamamonjy, A., D. Saelens, and R. Klein. 2018. “An Automated IFC-based Workflow for Building Energy Performance Simulation with Modelica.” Automation in Construction 91:166–181. https://doi.org/10.1016/j.autcon.2018.03.019.
   Web of Science ®Google Scholar
• Averfalk, H., T. Benakopoulos, I. Best, F. Dammel, C. Engel, R. Geyer, O. Gudmundsson, et al. 2021. “Low-Temperature District Heating Implementation Guidebook.” Final Report. Technical report, IEA DHC. http://publica.fraunhofer.de/dokumente/N-640204.html.
   Google Scholar
• Balaji, B., A. Bhattacharya, G. Fierro, J. Gao, J. Gluck, D. Hong, A. Johansen, et al. 2018. “Brick: Metadata Schema for Portable Smart Building Applications.” Applied Energy 226 (2017): 1273–1292. https://doi.org/10.1016/j.apenergy.2018.02.091.
   Google Scholar
• Benakopoulos, T., R. Salenbien, D. Vanhoudt, and S. Svendsen. 2019. “Improved Control of Radiator Heating Systems with Thermostatic Radiator Valves Without Pre-Setting Function.” Energies 12 (17): 3215. https://doi.org/10.3390/en12173215.
   Web of Science ®Google Scholar
• Benakopoulos, T., M. Tunzi, R. Salenbien, and S. Svendsen. 2021. “Strategy for Low-temperature Operation of Radiator Systems Using Data From Existing Digital Heat Cost Allocators.” Energy231:1209281. https://doi.org/10.1016/j.energy.2021.120928.
   Web of Science ®Google Scholar
• Bew, M., and M. Richards. 2008. “BIM Maturity Model.” In Construct IT Autumn 2008 Members' Meeting.
   Google Scholar
• Blockwitz, T., M. Otter, J. Akesson, M. Arnold, C. Clauss, H. Elmqvist, M. Friedrich, et al. 2012. “Functional Mockup Interface 2.0: The Standard for Tool independent Exchange of Simulation Models.” In Proceedings of the 9th International MODELICA Conference, September 3-5, Munich, Germany, Vol. 76, 173–184. https://doi.org/10.3384/ecp12076173.
   Google Scholar
• BuildingSmart. 2023a. “Industry Foundation Classes (IFC).” https://www.buildingsmart.org/standards/bsi-standards/industry-foundation-classes/. (visited on 2023-02-23).
   Google Scholar
• BuildingSmart. 2023b. “Model View Definition (MVD) – An Introduction.” https://technical.buildingsmart.org/standards/ifc/mvd/. (visited on 2023-02-23).
   Google Scholar
• Bum Kim, J., W. Jeong, M. J. Clayton, J. S. Haberl, and W. Yan. 2015. “Developing a Physical BIM Library for Building Thermal Energy Simulation.” Automation in Construction 50:16–28. https://doi.org/10.1016/j.autcon.2014.10.011.
   Web of Science ®Google Scholar
• Danfoss. 2014. Data Sheet – Thermostatic Sensors Type RA 2000.
   Google Scholar
• De Wilde, P.2014. “The Gap Between Predicted and Measured Energy Performance of Buildings: A Framework for Investigation.” Automation in Construction 41:40–49.https://doi.org/10.1016/j.autcon.2014.02.009.
   Web of Science ®Google Scholar
• Djunaedy, Ery, K. van den Wymelenberg, Brad Acker, and Harshana Thimmana. 2011. “Oversizing of HVAC System: Signatures and Penalties.” Energy and Buildings 43 (2-3): 468–475. https://doi.org/10.1016/j.enbuild.2010.10.011.
   Web of Science ®Google Scholar
• Doty, S. 2010. “Part–load HVAC Efficiency.” Energy Engineering 107 (3): 6–28. https://doi.org/10.1080/01998591009709874.
   Google Scholar
• Guyon, G. 1997. “Role of the Model User in Results Obtained From Simulation Software Program.” International Building Simulation Conference 5: 377–384.
   Google Scholar
• Hosseini, S. M., R. Shirmohammadi, A. Kasaeian, and F. Pourfayaz. 2021. “Dynamic Thermal Simulation Based on Building Information Modeling: A Review.” International Journal of Energy Research 45 (10): 14221–14244. https://doi.org/10.1002/er.6740.
   Web of Science ®Google Scholar
• IBPSA. 2016. IBPSA Project 1. https://ibpsa.github.io/project1/index.html.
   Google Scholar
• Imam, S., D. A. Coley, and I. Walker. 2017. “The Building Performance Gap: Are Modellers Literate?” Building Services Engineering Research and Technology 38 (3): 351–375. https://doi.org/10.1177/0143624416684641.
   Web of Science ®Google Scholar
• International Organization for Standardization. 2018. ISO 19650-1: Organization and Digitization of Information About Buildings and Civil Engineering Works, Including Building Information Modelling (BIM)–Information Management Using Building Information Modelling–Part 1: Concepts and Principles. https://www.iso.org/standard/68078.html.
   Google Scholar
• International Organization for Standardization. 2020a. ISO 23386: Building Information Modelling and Other Digital Processes Used in Construction – Methodology to Describe, Author and Maintain Properties in Interconnected Data Dictionaries. https://www.iso.org/standard/75401.html.
   Google Scholar
• International Organization for Standardization. 2020b. ISO 23387: Building Information Modelling (BIM) – Data Templates for Construction Objects Used in the Life Cycle of Built Assets – Concepts and principles, https://www.iso.org/standard/75403.html.
   Google Scholar
• Jorissen, F., G. Reynders, R. Baetens, D. Picard, D. Saelens, and L. Helsen. 2018. “Implementation and Verification of the IDEAS Building Energy Simulation Library.” Journal of Building Performance Simulation 11 (6): 669–688. https://doi.org/10.1080/19401493.2018.1428361.
   Web of Science ®Google Scholar
• Lawrence Berkeley National Laboratory. 2021. Lawrence Berkeley National Laboratory – Simulation Research Group. Spawn of EnergyPlus, https://lbl-srg.github.io/soep/.
   Google Scholar
• Lu, Y., Z. Wu, R. Chang, and Y. Li. 2017. “Building Information Modeling (BIM) for Green Buildings: A Critical Review and Future Directions.” Automation in Construction 83:134–148. https://doi.org/10.1016/j.autcon.2017.08.024.
   Web of Science ®Google Scholar
• Mathew, P., Steve Greenberg, David Frenze, Michael Morehead, Dale Sartor, and William Starr. 2005. “Using Measured Equipment Load Profiles to ‘Right-Size’ HVAC Systems and Reduce Energy Use in Laboratory Buildings.” HPAC Engineering 1–14. https://www.osti.gov/biblio/929009.
   Google Scholar
• Mattsson, S. E., and H. Elmqvist. 1997. “Modelica – An International Effort to Design the Next Generation Modeling Language.” IFAC Proceedings Volumes 30 (4): 151–155. https://doi.org/10.1016/s1474-6670(17)43628-7.
   Google Scholar
• Menezes, A. C., A. Cripps, D. Bouchlaghem, and R. Buswell. 2012. “Predicted Vs. Actual Energy Performance of Non-domestic Buildings Using Post-occupancy Evaluation Data to Reduce the Performance Gap.” Applied Energy 97:355–364. https://doi.org/10.1016/j.apenergy.2011.11.075.
   Web of Science ®Google Scholar
• Mills, E. 2011. “Building Commissioning: A Golden Opportunity for Reducing Energy Costs and Greenhouse Gas Emissions in the United States.” Energy Efficiency 4 (2): 145–173. https://doi.org/10.1007/s12053-011-9116-8.
   Web of Science ®Google Scholar
• Müller, D., M. Lauster, A. Constantin, M. Fuchs, and P. Remmen. 2016. “Aixlib – an Open-Source Modelica Library Within the IEA-EBC Annex 60 Framework.” In Proceedings of the CESBP Central European Symposium on Building Physics and BauSIM, 3–9.
   Google Scholar
• Nall, Daniel H. 2015. “Rightsizing HVAC Equipment.” ASHRAE Journal 57 (1): 48–51.
   Web of Science ®Google Scholar
• Newsham, Guy R., S. Mancini, and B. J. Birt. 2009. “Do LEED-certified Buildings Save Energy? Yes, But….” Energy and Buildings 41 (8): 897–905. https://doi.org/10.1016/j.enbuild.2009.03.014.
   Web of Science ®Google Scholar
• Nytsch-Geusen, C., J. Huber, M. Ljubijankic, and J. Rädler. 2013. “Modelica BuildingSystems – Eine Modellbibliothek Zur Simulation Komplexer Energietechnischer Gebäudesysteme.” Bauphysik35 (1): 21–29. https://doi.org/10.1002/bapi.201310045.
   Google Scholar
• Nytsch-Geusen, C., A. Inderfurth, W. Kaul, K. Mucha, J. Rädler, M. Thorade, and C. Ribas Tugores. 2017. “Template Based Code Generation of Modelica Building Energy Simulation Models.” In Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, Vol. 132, 199–207. Linköping University Electronic Press. https://doi.org/10.3384/ecp17132199.
   Google Scholar
• Rasmussen, M. H., M. Lefrançois, G. F. Schneider, and P. Pauwels. 2020. “BOT: The Building Topology Ontology of the W3C Linked Building Data Group.” Semantic Web 12 (1): 143–161. https://doi.org/10.3233/SW-200385.
   Web of Science ®Google Scholar
• Seidenschnur, M., A. Kücükavci, E. V. Fjerbæk, K. Michael Smith, P. Pauwels, and C. Anker Hviid. 2022. “A Common Data Environment for HVAC Design and Engineering.” Automation in Construction 142:104500. https://doi.org/10.1016/j.autcon.2022.104500.
   Web of Science ®Google Scholar
• Seidenschnur, M., A. Kücükavci, E. Visby Fjerbæk, K. Michael Smith, and C. Anker Hviid. 2023. “A Common Data Environment with an EnergyPlus Microservice for Post-Occupancy Evaluation of the Energy Performance Gap.” [Manuscript Submitted for Publication].
   Google Scholar
• Terkaj, W., G. Ferdinand Schneider, and P. Pauwels. 2017. “Reusing Domain Ontologies in Linked Building Data: The Case of Building Automation and Control.” CEUR Workshop Proceedings, 2050.
   Google Scholar
• Wetter, M., P. Ehrlich, A. Gautier, M. Grahovac, P. Haves, J. Hu, A. Prakash, D. Robin, and K. Zhang. 2022. “OpenBuildingControl: Digitizing the Control Delivery From Building Energy Modeling to Specification, Implementation and Formal Verification.” Energy 238:121501. https://doi.org/10.1016/j.energy.2021.121501.
   Web of Science ®Google Scholar
• Wetter, M., W. Zuo, T. S. Nouidui, and X. Pang. 2014. “Modelica Buildings Library.” Journal of Building Performance Simulation 7 (4): 253–270. https://doi.org/10.1080/19401493.2013.765506.
   Web of Science ®Google Scholar
• Wilcox, S., and W. Marion. 2008. “Users Manual for TMY3 Data Sets (Revised).” Technical Report May, National Renewable Energy Laboratory (NREL), Golden, CO.
   Google Scholar
• Xiao, F., and S. Wang. 2009. “Progress and Methodologies of Lifecycle Commissioning of HVAC Systems to Enhance Building Sustainability.” Renewable and Sustainable Energy Reviews 13 (5): 1144–1149. https://doi.org/10.1016/j.rser.2008.03.006.
   Web of Science ®Google Scholar
• Zhang, R., and T. Hong. 2017. “Modeling of HVAC Operational Faults in Building Performance Simulation.” Applied Energy 202:178–188. https://doi.org/10.1016/j.apenergy.2017.05.153.
   Web of Science ®Google Scholar