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Achieving informed decision-making for net zero energy buildings design using building performance simulation tools

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  • Architecture and Human Behavior
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Abstract

Building performance simulation (BPS) is the basis for informed decision-making of Net Zero Energy Buildings (NZEBs) design. This paper aims to investigate the use of building performance simulation tools as a method of informing the design decision of NZEBs. The aim of this study is to evaluate the effect of a simulation-based decision aid, ZEBO, on informed decision-making using sensitivity analysis. The objective is to assess the effect of ZEBO and other building performance simulation tools on three specific outcomes: (i) knowledge and satisfaction when using simulation for NZEB design; (ii) users’ decision-making attitudes and patterns, and (iii) performance robustness based on an energy analysis. The paper utilizes three design case studies comprising a framework to test the use of BPS tools. The paper provides results that shed light on the effectiveness of sensitivity analysis as an approach for informing the design decisions of NZEBs.

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References

  • Achten K, De Coninck R, Verbeeck G, Van der Veken J (2009). Analyzing the economic feasibility of permutations of energy-saving measures with batch simulations and Pareto optimization. In: Proceedings of the 11th International IBPSA Conference (BS2009), Glasgow, Scotland, pp. 660–667.

  • ANSI (2001). ANSI/INCITS 354-2001: Common Industry Format (CIF) for Usability Test Reports. Washington, DC: American National Standards Institute.

    Google Scholar 

  • ASHRAE (2008). ASHRAE Vision 2020 Ad Hoc Committee. Available at http://www.ashrae.org/doclib/20080226_ashraevision2020.pdf. Accessed Oct. 1, 2011.

  • Athienitis A, Attia S, et al. (2010). Strategic design, optimization, and modelling issues of net-zero energy solar buildings. Paper presented at the International Conference on Solar Heating, Cooling and Buildings (EuroSun 2010), Graz, Austria.

  • Attia S (2011). ZEBO Tutorial Video 1. Available at http://www.youtube.com/watch?v=zJLYzuL7yjg. Accessed Sept. 2011.

  • Attia S (2012a). Optimisation for zero energy building design: Interviews with twenty eight international experts. Available at http://www-climat.arch.ucl.ac.be/s_attia/Attia_Optimisation%20Interviews2012.pdf. Accessed Jun. 1, 2012.

  • Attia S (2012b). A tool for design decision making—Zero energy residential buildings in hot humid climates. PhD Thesis, Department of Architecture, Universite Catholique de Louvain, Belgium.

    Google Scholar 

  • Attia S, De Herde A (2010). Sizing photovoltaic systems during early design: A decision tool for architects. In: Proceedings of SOLAR 2010, Phoenix, USA.

  • Attia S, De Herde A (2011a). Early design simulation tools for net zero energy buildings: A comparison of ten tools. In: Proceedings of the 12th International IBPSA Conference (BS2011), Sydney, Australia, pp. 94–101.

  • Attia S, De Herde A (2011b). Design decision tool for zero energy buildings. In: Proceedings of 27th Conference on Passive and Low Energy Architecture (PLEA 2011), Louvain-la-Neuve, Belgium, pp. 77–82.

  • Attia S, Hamdy M, Samaan M, De Herde A, Hensen JLM (2011). Towards strategic use of BPS tools in Egypt. In: Proceedings of the 12th International IBPSA Conference (BS2011), Sydney, Australia, pp. 40–47.

  • Attia S, Evrard A, Gratia E (2012a). Development of benchmark models for the Egyptian residential buildings sector. Applied Energy, 94: 270–284.

    Article  Google Scholar 

  • Attia S, Gratia E, De Herde A, Hensen JLM (2012b). Simulation-based decision support tool for early stages of zero-energy building design. Energy and Building, 49: 2–15.

    Article  Google Scholar 

  • Attia S, Hensen JLM, Beltrán L, De Herde A (2012c). Selection criteria for building performance simulation tools: Contrasting architects’ and engineers’ needs. Journal of Building Performance Simulation, 5: 155–169.

    Article  Google Scholar 

  • Attia S, Wanas O (2012). The Database of Egyptian Building Envelopes (DEBE): A database for building energy simulations. Paper presented in SimBuild 2012, Madison, USA.

  • Bambardekar S, Poerschke U (2009). The architect as performer of energy simulation in the early design stage. In: Proceedings of the 11th International IBPSA Conference (BS2009), Glasgow, Scotland, pp. 1306–1313.

  • Bogenstätter U (2000). Prediction and optimization of life-cycle costs in early design. Building Research & Information, 28: 376–386.

    Article  Google Scholar 

  • Charron R, Athienitis A, Beausoleil-Morrison I (2006). Tools for the design of zero energy solar homes. ASHRAE Transactions, 112(2): 285–295.

    Google Scholar 

  • Charles PP, Thomas CR (2009). Four approaches to teaching with building performance simulation tools in undergraduate architecture and engineering education. Journal of BuildingPerformance Simulation, 2: 95–114.

    Article  Google Scholar 

  • DesignBuilder (2011a). DesignBuilder v.2.3.5.036.

  • DesignBuilder (2011b). DesignBuilder. Available at http://www.designbuilder.co.uk. Accessed Jan. 1, 2011.

  • DOE (2011a). EnergyPlus. Available at http://apps1.eere.energy.gov/buildings/energyplus. Accessed Jan. 1, 2011.

  • DOE (2011b). Building energy software tools directory. Available at http://apps1.eere.energy.gov/buildings/tools_directory. Accessed Jan. 1 2011.

  • Donn MR (2004). Simulation of imagined realities: Environmental design decision support tools in architecture. PhD Thesis, Victoria University of Wellington, New Zealand.

    Google Scholar 

  • EU (2009). Report on the proposal for a directive of the European Parliament and of the Council on the energy performance of buildings (recast), European Parliament. (COM(2008)0780-C6-0413/2008-2008/0223(COD))

  • Georges L, Massart C, Van Moeseke G, De Herde A (2012). Environmental and economic performance of heating systems for energy-efficient dwellings: Case of passive and low-energy single-family houses. Energy Policy, 40: 452–464.

    Article  Google Scholar 

  • Givoni B (1992). Comfort, climate analysis and building design guidelines. Energy and Buildings, 18: 11–23.

    Article  Google Scholar 

  • Hamza N, Horne M (2007). Educating the designer: An operational model for visualizing low-energy architecture. Building and Environment, 42: 3841–3847.

    Article  Google Scholar 

  • Hansen H (2007). Sensitivity analysis as a methodical approach to the development of design strategies for environmentally sustainable buildings. PhD Dissertation, Department of Architecture and Design, Aalborg University, Denmark.

    Google Scholar 

  • Hayter SJ, Torcellini PA, Hayter RB, Judkoff R (2001). The energy design process for designing and constructing high-performance buildings. In: Proceedings of the 7th REHVA World Congress and Clima 2000/Naples 2001 Conference, Naples, Italy.

  • Hopfe C (2009). Uncertainty and sensitivity analysis in building per- formance simulation for decision support and design optimization. PhD Dissertation, Technical University of Eindhoven, The Netherlands.

    Google Scholar 

  • IEA (2008). IEA SHC Task 40/ECBCSAnnex 52, Towards net zero energy solar buildings. Available at http://www.iea-shc.org/task40/index.html. Accessed Oct. 10, 2009.

  • ISO (1998). ISO 9241-11:1998, Ergonomic requirements for office work with visual display terminals (VDTs)—Part II: Guidance on usability. Geneva: International Organization for Standardization.

    Google Scholar 

  • ISO (2006). ISO/IEC 25062: 2006, Software engineering—Software product quality requirements and evaluation—Common industry format for usability test reports. Geneva: International Organization for Standardization.

    Google Scholar 

  • Kolokotsa D, Rovas D, Kosmatopoulos E, Kalaitzakis K (2011). A roadmap towards intelligent net zero- and positive-energy buildings. Solar Energy, 85: 3067–3084.

    Article  Google Scholar 

  • Kurnitski J, Saari A, Kalamees T, Vuolle M, Niemelä J, Tark T (2011). Cost optimal and nearly zero (nZEB) energy performance calculations for residential buildings with REHVA definition for nZEB national implementation. Energy and Buildings, 43: 3279–3288.

    Article  Google Scholar 

  • Lewis JR (1991). Psychometric evaluation of an after-scenario questionnaire for computer usability studies: The ASQ. SIGCHI Bulletin, 23: 78–81.

    Article  Google Scholar 

  • Petersen S, Svendsen S (2010). Method and simulation program informed decisions in the early stages of building design. Energy and Buildings, 42: 1113–1119.

    Article  Google Scholar 

  • Pless S, Torcellini P, Macey P (2012). Controlling capital costs in high performance office buildings: 15 best practices for overcoming cost barriers in project acquisition, design, and construction. NREL Commercial Buildings Research Group.

  • Mahdavi A, El-Bellahy A (2005). Effort and effectiveness considerations in computational design evaluation: A case study. Building and Environment, 40: 1651–1664.

    Article  Google Scholar 

  • Marszal AJ, Heiselberg P, Bourrelle JS, Musall E, Voss K, Sartori I, Napolitano A (2011). Zero energy building—A review of definitions and calculation methodologies. Energy and Buildings, 43: 971–979.

    Article  Google Scholar 

  • Marszal AJ, Heiselberg P (2011). Life cycle cost analysis of a multi-storey residential Net Zero Energy Building in Denmark. Energy, 36: 5600–5609.

    Article  Google Scholar 

  • Morbitzer C (2003). Towards the integration of simulation into the building design process. PhD Dissertation, Department of Mechanical Engineering, University of Strathclyde, UK.

    Google Scholar 

  • Mourshed M (2006). Interoperability-based optimization of architectural design. PhD Dissertation, Civil and Environmental Engineering at the National University of Ireland, Ireland.

    Google Scholar 

  • Milne M (2011). Climat Consultant 5. Available at http://www.energy-design-tools.aud.ucla.edu.

  • Renard F, Nourricier S, Pietrantonio MD, Feldheim V (2008). Technical-economic analysis of the cost-effectiveness of energy saving investments for residential buildings. Technical Report, Service Public de Wallonie, DG04, Final Report.

  • Riether G, Butler T (2008). Simulation space: A new design environment for architects. In: Proceedings of the 26th eCAADe Conference, Antwerp, Belgium.

  • RMI (2011). Rocky Mountain Institute. Available at http://bembook.ibpsa.us/index.php?title=Main_Page. Accessed Jun. 1, 2012.

  • Sartori I, Napolitano A, Voss K (2012). Net zero energy buildings: A consistent definition framework. Energy Buildings, 48: 220–232.

    Article  Google Scholar 

  • Shaviv E (1999). Integrating energy consciousness in the design process. Automation in Construction, 8: 463–472.

    Article  Google Scholar 

  • Tullis T, Albert B (2008). Measuring the User Experience: Collecting, Analyzing, and Presenting Usability Metrics. Burlington, USA: Morgan Kaufmann.

    Google Scholar 

  • Weytjens L, Attia S, Verbeeck G, De Herde A (2010). A comparative study of the “architect-friendliness” of six building performance simulation tools. In: Proceedings of Sustainable Buildings 2010 Euregion, Maastricht, the Netherlands.

  • Zeiler W (2011). Case studies on NZEB: Dutch experience with schools. In: Proceedings of REHVA Annual Conference Towards Net Zero Energy Buildings and Building Labelling, Tallinn, Estonia.

  • Zhang Y, Korolija I (2010). Performing complex parametric simulations with jEPlus. In: Proceedings of the 9th SET Conference, Shanghai, China.

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Attia, S., De Herde, A., Gratia, E. et al. Achieving informed decision-making for net zero energy buildings design using building performance simulation tools. Build. Simul. 6, 3–21 (2013). https://doi.org/10.1007/s12273-013-0105-z

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