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Curtain walls are believed to be “energy sinks” because of their low thermal performance, however, the integration of energy generating technologies such as photovoltaic (PV) panels may enable converting curtain walls to “plus-energy” curtain walls. The “plus-energy” curtain wall is defined as the energy generated by the curtain wall façade exceeds the energy consumption of a perimeter zone office. To design plus-energy curtain walls, design parameters of curtain walls are prioritized by sensitivity analysis and the most critical design parameters corresponding to specific energy efficient measures that bring major energy benefits with minor modifications are identified.

An office unit with five adiabatic faces and one exterior façade completed with curtain walls is developed as the energy model in EnergyPlus. The indoor environmental parameters are set based on ASHRAE energy standard.

In this study, global sensitivity analysis is conducted to prioritize the energy impact of ten design parameters, U-value of glazing, solar heat gain coefficient of glazing, visible transmittance of glazing, U-value of spandrel panel, U-value of frame, window wall ratio, infiltration, depth of overhang, inclination of overhang, and effective efficiency of photovoltaic panels. The three most significant design parameters are identified for four orientations. Plus-energy curtain wall configurations at different window-to-wall ratio (WWR) and orientations are identified according to the total sensitivity indices. The significance of this study is to provide design recommendations of plus-energy curtain wall configurations under different WWRs and orientations, which are not covered in the current design guidelines.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Thesis (Masters)
Authors:Lam, Tze Chun Angel
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Building Engineering
Date:17 August 2015
Thesis Supervisor(s):Fazio, Paul and Ge, Hua
Keywords:Curtain walls; Building envelopes; Building energy performance; Building simulations; Sensitivity analysis; Uncertainty analysis; Analysis of Variance
ID Code:980447
Deposited On:02 Nov 2015 15:59
Last Modified:18 Jan 2018 17:51


Alam, M., Singh, H., & Limbachiya, M. C. (2011). Vacuum Insulation Panels (VIPs) for building construction industry – A review of the contemporary developments and future directions. Applied Energy, 88(11), 3592–3602.

Apostolakis, G. (1990). The concept of probability in safety assessments of technological systems. Science, 250(4986), 1359–1364.

Archer, G. E. B., Saltelli, A., & Sobol, I. M. (1997). Sensitivity measures,anova-like Techniques and the use of bootstrap. Journal of Statistical Computation and Simulation, 58(2), 99–120.

ASHRAE. (2002). ASHRAE Guideline 14-2002 Measurement of Energy and Demand Savings. American Society of Heating, Refrigerating, and Air-Conditioning Engineers.

ASHRAE. (2010). ANSI/ASHRAE Standard 55:2010 Thermal Environmental Conditions for Human Occupancy. American Society of Heating, Refrigerating, and Air-Conditioning Engineers.

ASHRAE. (2011a). Advanced Energy Design Guide for Small to Medium Office Buildings. American Society of Heating, Refrigerating and Air-Conditioning Engineers.

ASHRAE. (2011b). ANSI/ASHRAE/IES Standard 90.1-2011 -- Energy Standard for Buildings Except Low-Rise Residential Buildings. American Society of Heating, Refrigerating, and Air-Conditioning Engineers.

Attia, S., Gratia, E., De Herde, A., & Hensen, J. L. M. (2012). Simulation-based decision support tool for early stages of zero-energy building design. Energy and Buildings, 49, 2–15.

Attia, S., Hamdy, M., O’Brien, W., & Carlucci, S. (2013). Assessing gaps and needs for integrating building performance optimization tools in net zero energy buildings design. Energy and Buildings, 60, 110–124.

Barnett, A. M., Rand, J. A., Hall, R. B., Bisaillon, J. C., Delledonne, E. J., Feyock, B. W., … Sims, P. E. (2001). High current, thin silicon-on-ceramic solar cell. Solar Energy Materials & Solar Cells, 66, 45–50.

Bieda, B. (2010). Decision support systems based on the economic feasibility assessment for Municipal Solid Waste (MSW) Management under Uncertainty using SimLab® toolpack. In Procedia - Social and Behavioral Sciences 2 (Vol. 2, pp. 7609–7610). Sixth International Conference on Sensitivity Analysis of Model Output.

Bratley, P., & Fox, B. L. (1988). ALGORITHM 659: implementing Sobol’s quasirandom sequence generator. ACM Transactions on Mathematical Software, 14(1), 88–100.

Carmody, J., Selkowitz, S., Lee, E. S., & Arasteh, D. (2004). Window Systems for High-Performance Buildings. W. W. Norton & Company.

Chaiyapinunt, S., Phueakphongsuriya, B., Mongkornsaksit, K., & Khomporn, N. (2005). Performance rating of glass windows and glass windows with films in aspect of thermal comfort and heat transmission. Energy and Buildings, 37(7), 725–738.

Chan, K., Saltelli, A., & Tarantola, S. (1997). Sensitivity Analysis of Model Output: Variance-Based Methods Make the Difference. In Proceedings of the 29th conference on Winter simulation Conference (pp. 261–268).

Chow, T. T., Li, C., & Lin, Z. (2010). Innovative solar windows for cooling-demand climate. Solar Energy Materials and Solar Cells, 94(2), 212–220.

CIBSE. (2004). CIBSE TM35 Environmental Performance Toolkit for Glazed Façades. The Chartered Institution of Building Services Engineers.

Climate. (2015). climate.weather.gc.ca. Retrieved from http://climate.weather.gc.ca/climateData/almanac_e.html?timeframe=4&Prov=QC&StationID=30165&Year=2001&Month=6&Day=2

Crawley, D. B., Hand, J. W., Kummert, M., & Griffith, B. T. (2008). Contrasting the capabilities of building energy performance simulation programs. Building and Environment, 43(4), 661–673.
Didonato, A. R., & Morris, A. H. (1992). Significant digit computation of the incomplete beta function ratios. ACM Transactions on Mathematical Software, 18(3), 360–373.

DOE. (2013a). EnergyPlus engineering reference: the reference to EnergyPlus calculations.

DOE. (2013b). EnergyPlus Input Output Reference: The Encyclopedic Reference to EnergyPlus Input and Output.

Duffie, J. a., & Beckman, W. a. (1994). Solar Engineering of Thermal Processes (4th ed.). Wiley.

Dussault, J.-M., Gosselin, L., & Galstian, T. (2012). Integration of smart windows into building design for reduction of yearly overall energy consumption and peak loads. Solar Energy, 86(11), 3405–3416.

Frey, H. C., & Patil, S. R. (2002). Identification and review of sensitivity analysis methods. Risk Analysis, 22(3), 553–578.

Ge, H. (2002). Study on overall thermal performance of metal curtain walls. PhD Thesis, Concordia University.

Geoffrey, V. M., Bruyère, I., & De Herde, A. (2007). Impact of control rules on the efficiency of shading devices and free cooling for office buildings. Building and Environment, 42(2), 784–793.

Gilijamse, W. (1995). Zero-energy houses in the Netherlands. In Building Simulation ‘95 (pp. 276–283). Madison, Wisconsin, USA.

Gopinathan, K. K. (1991). Solar radiation on variously oriented sloping surfaces. Solar Energy, 47(3), 173–179.

Gunerhan, H., & Hepbasli, A. (2007). Determination of the optimum tilt angle of solar collectors for building applications. Building and Environment, 42(2), 779–783.

Gutherz, J. M., & Schiler, M. E. (1991). A Passive Solar Heating System for the Perimeter Zone of Office Buildings. Energy Sources, 13(1), 39–54.

Hamby, D. M. (1994). A review of techniques for parameter sensitivity analysis of environmental models. Environmental Monitoring and Assessment, 32(2), 135–54.

Hanna, S. R. (1993). Uncertainties in Air Quality Model Predictions. Transport and Diffusion in Turbulent Fields, Springer N, 3–20.

Hausladen, G. (2008). ClimateSkin: Concepts for Building Skins That Can Do More with Less Energy. Birkhäuser GmbH.

Helton, J. C., & Burmaster, D. E. (1996). Guest editorial: treatment of aleatory and epistemic uncertainty in performance assessments for complex systems. Reliability Engineering & System Safety, 54(2), 91–94.

Hochberg, Y., & Tamhane, A. C. (2009). Multiple Comparison Procedures (1st ed.). Wiley.

Hoes, P., Hensen, J. L. M., Loomans, M. G. L. C., de Vries, B., & Bourgeois, D. (2009). User behavior in whole building simulation. Energy and Buildings, 41(3), 295–302.

Hopfe, C. J., & Hensen, J. L. M. (2011). Uncertainty analysis in building performance simulation for design support. Energy and Buildings, 43(10), 2798–2805.

Iman, Ronald L., and W. J. C. (1982). A distribution-free approach to inducing rank correlation among input variables. Communications in Statistics-Simulation and Computation 11, 3, 311–334.

Jelle, B. P., Hynd, A., Gustavsen, A., Arasteh, D., Goudey, H., & Hart, R. (2012). Fenestration of today and tomorrow: A state-of-the-art review and future research opportunities. Solar Energy Materials and Solar Cells, 96(7465), 1–28.

Kasinalis, C., Loonen, R. C. G. M., Cóstola, D., & Hensen, J. L. M. (2014). Framework for assessing the performance potential of seasonally adaptable façades using multi-objective optimization. Energy and Buildings, 79, 106–113.

Kim, J. T., & Kim, G. (2010). Advanced External Shading Device to Maximize Visual and View Performance. Indoor and Built Environment, 19(1), 65–72.

Kiureghian, A. Der, & Ditlevsen, O. (2009). Aleatory or epistemic? Does it matter? Structural Safety, 31(2), 105–112.

Lam, T. C., Ge, H., & Fazio, P. (2014). Study of different glazing modelling approaches in assessing energy performance of curtain wall systems using EnergyPlus. In eSIM 2014 Conference Proceedings. International Building Performance Simulation Association.

Lee, E. S., & Tavil, A. (2007). Energy and visual comfort performance of electrochromic windows with overhangs. Building and Environment, 42(6), 2439–2449.

Lee, I. Y. T. (2010). High Performance Window Systems and their Effect on Perimeter Space Commercial Building Energy Performance. Master Thesis, University of Waterloo.

Lewis, G. (1987). Optimal tilt of solar collectors. Solar & Wind Technology, 4(3), 407–410.

Lorenzo, E. (2011). Energy Collected and Delivered by PV Modules. Handbook of Photovoltaic Science and Engineering (Forth). Wiley.

Macdonald, I. A. (2002). Quantifying the Effects of Uncertainty in Building Simulation. PhD Thesis, University of Strathclyde.

Machairas, V., Tsangrassoulis, A., & Axarli, K. (2014). Algorithms for optimization of building design: A review. Renewable and Sustainable Energy Reviews, 31, 101–112.

Manz, H., & Menti, U. P. (2012). Energy performance of glazings in European climates. Renewable Energy, 37(1), 226–232.

Marszal, A. J., Heiselberg, P., Bourrelle, J. S., Musall, E., Voss, K., Sartori, I., & Napolitano, A. (2011). Zero Energy Building - A review of definitions and calculation methodologies. Energy and Buildings, 43(4), 971–979.

Meewissen, A. M. H., & Cooke, R. M. (1994). Report 94-28 Tree dependent random variables. Delft University of Technology.

Montgomery, D. C. (2012). Design and Analysis of Experiments (8th ed.). Wiley.

Morris, M. D. (1987). Two-stage factor screening procedures using multiple grouping assignments. Communications in Statistics - Theory and Methods, 16(10), 3051–3067.

Nasrollahi, F. (2013). Architectural Energy Efficiency (7th ed.). Universitätsverlag der TU Berlin.

Nielsen, M. V., Svendsen, S., & Jensen, L. B. (2011). Quantifying the potential of automated dynamic solar shading in office buildings through integrated simulations of energy and daylight. Solar Energy, 85(5), 757–768.

Nielsen, T. R., Duer, K., & Svendsen, S. (2000). Energy performance of glazings and windows. Solar Energy, 69(SUPPLEMENT 6), 137–143.

Noguchi, M., Athienitis, A., Delisle, V., Ayoub, J., & Berneche, B. (2008). Net Zero Energy Homes of the Future : A Case Study of the ÉcoTerra House in Canada. In Renewable Energy Congress (pp. 2008–2112). Glasgow,Scotland.

Ott, R. L. (2008). An Introduction to Statistical Methods and Data Analysis (6th ed.). Duxbury Press.

Pace, L. A. (2012). Beginning R: An introduction to statistical programming. Apress.

Parida, B., Iniyan, S., & Goic, R. (2011). A review of solar photovoltaic technologies. Renewable and Sustainable Energy Reviews, 15(3), 1625–1636.

Peter, L., Justin, W., & Mahabir, B. (2010). A comparison of window modeling methods in EnergyPlus 4.0. In Fourth National Conference of IBPSA-USA New (pp. 177–184). New York City, New York: SimBuild 2010.

Poirazis, H., Blomsterberg, Å., & Wall, M. (2008). Energy simulations for glazed office buildings in Sweden. Energy and Buildings, 40(7), 1161–1170.

Prasad, D., & Snow, M. (2014). Designing with solar power: a source book for building integrated photovoltaics (BiPV).
Roberts, S., & Guariento, N. (2009). Building Integrated Photovoltaics: A Handbook (First). Birkhäuser Basel.

Rosta, S., Hurt, R., Boehm, R., & Hale, M. J. (2008). Performance of a Zero-Energy House. Journal of Solar Energy Engineering, 130(2), 021006.

Roy, R., Hinduja, S., & Teti, R. (2008). Recent advances in engineering design optimisation: Challenges and future trends. CIRP Annals - Manufacturing Technology, 57(2), 697–715.

Saltelli, A., Chan, ‎K., & Scot, ‎E. M. (2000). Sensitivity Analysis. Wiley.

Saltelli, A., Ratto, M., Andres, T., Francesca Campolongo, J. C., Gatelli, D., Saisana, M., & Tarantola, S. (2008). Global sensitivity analysis: the primer. John Wiley & Sons.

Shen, H., & Tzempelikos, A. (2012). Daylighting and energy analysis of private offices with automated interior roller shades. Solar Energy, 86(2), 681–704.

Silva, P. C. da, Leal, V., & Andersen, M. (2012). Influence of shading control patterns on the energy assessment of office spaces. Energy and Buildings, 50, 35–48.

Singh, G. K. (2013). Solar power generation by PV (photovoltaic) technology: A review. Energy, 53, 1–13.

Spitz, C., Mora, L., Wurtz, E., & Jay, A. (2012). Practical application of uncertainty analysis and sensitivity analysis on an experimental house. Energy and Buildings, 55, 459–470.

Stein, M. (1987). Large sample properties of simulations using Latin hypercube sampling. Technometrics 29, 2, 143–151.
Tawada, Y., & Yamagishi, H. (2001). Mass-production of large size a-Si modules and future plan. Solar Energy Materials and Solar Cells, 66(1-4), 95–105.

Thalfeldt, M., Pikas, E., Kurnitski, J., & Voll, H. (2013). Façade design principles for nearly zero energy buildings in a cold climate. Energy and Buildings, 67, 309–321.

Tian, W. (2013). A review of sensitivity analysis methods in building energy analysis. Renewable and Sustainable Energy Reviews, 20, 411–419.

Torcellini, P., Pless, S., & Deru, M. (2006). Zero Energy Buildings : A Critical Look at the Definition Preprint. In N. R. E. Laboratory (Ed.), ACEEE Summer Study. Pacific Grove, California.

Tzempelikos, A., & Athienitis, A. K. (2007). The impact of shading design and control on building cooling and lighting demand. Solar Energy, 81(3), 369–382.

Van Buren, K. L., Atamturktur, S., & Hemez, F. M. (2014). Model selection through robustness and fidelity criteria: Modeling the dynamics of the CX-100 wind turbine blade. Mechanical Systems and Signal Processing, 43(1-2), 246–259.

Van der Zwaan, B. (2003). Prospects for PV: A learning curve analysis. Solar Energy, 74(1), 19–31.

West, S. (2001). Improving the sustainable development of building stock by the implementation of energy efficient , climate control technologies. Building and Environment, 36(2001), 281–289.

Yang, J., Banerjee, A., & Guha, S. (2003). Amorphous silicon based photovoltaics - From earth to the “final frontier.” Solar Energy Materials and Solar Cells, 78(1-4), 597–612.
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