Review Article: Significant Parameters in Building Energy Simulation

Main Article Content

Daranee Jareemit
Natthaumporn Inprom


A simulation model has been widely used to investigate and predict the energy performance of buildings. However, to achieve more accurate energy result, the input data in the simulation model should be obtained from field measurements. Collecting field measurements is a very time intensive activity. With this limitation, in this work we summarized results of parameters most influential on energy results from 44 papers performing energy simulation model for determining the potential of energy saving and improving the model accuracy in various building types including offices, single rooms, homes, multi-family buildings, and other commercial buildings. It is found that the parameters with influence on energy performance were dissimilar to the parameter that the modelers used for adjusting the model accuracy and determining energy saving. Set point temperature had a large impact on energy results for office and home, while shading and occupancy schedule significantly impacted the energy results for multi-family building and other commercial buildings, respectively. At present, the number of sensitivity analysis related to building energy performance is limited. Future studies should increase a number of sensitivity analysis of building energy performance for different building types.


Download data is not yet available.

Article Details

Review Article


Anonwattanakarn, P. (2006). แนวทางการปรับปรุงการประหยัดพลังงานสำหรับบ้านเดี่ยวในโครงการจัดสรร [Guidelines for improving energy efficiency of detached houses in sub-divisional projects]. Master of Architecture Thesis, Thammasat University, Pathumthani, Thailand.

Aerts, D., Minnen, J., Glorieux, I., Wouters, I. & Descamps, F. (2014). A method for the identification and modelling of realistic domestic occupancy sequences for building energy demand simulations and peer comparison. Building and Environment, 75, 67–78.

Alangar, I., Heidarinejad, M. & Srebric, J. (2014). A Sensitivity analysis of energy simulation accuracy for arenovated healthcare building. Journal of Solar Energy Engineering 125(3), 1-9.

American Society of Heating, Refigeration and Air-Conditioning Engineering [ASHRAE]. (2002). ASHRAE Guideline 14-2002 for measurement of energy and Demand Savings. American Society of Heating, Refrigeration and Air Conditioning Engineers. Atlanta, GA: Author.

American Society of Heating, Refigeration and Air-Conditioning Engineering [ASHRAE]. (2009). Chapter 19 Energy Estimating and Modeling Methods. In ASHRAE Handbook Fundamental (pp. 19.1–19.37). Atlanta, GA: Author.

Azar, E. & Menassa, C. C. (2012). A comprehensive analysis of the impact of occupancy parameters in energy simulation of office buildings. Energy and Buildings, 55, 841–853.

Ballarini, I. & Corrado, V. (2012). Analysis of the building energy balance to investigate the effect of thermal insulation in summer conditions. Energy and Buildings, 52, 168–180.

Blight, T. S. & Coley, D. A. (2013). Sensitivity analysis of the effect of occupant behavior on the energy consumption of passive house dwellings. Energy and Buildings, 66, 183–192.

Capozzoli, A., Mechri, H. & Corrado, V. (2009). Impacts of architectural design choices on building energy performance application of uncertainty and sensitivity techniques. In Building Performance Simulation Association (IBPSA) conference (pp. 1000–1007). Glasgow, Scotland.

Carson, G. C. (1992). Input-output sensitivity of building energy simulations. ASHRAE Transactions, 98(1992), 618–626.

Chiewnantawong, S. (2004).การออกแบบบ้านแถวเพื่อใช้พลังงานอย่างมีประสิทธิภาพ [Townhouse design with energy efficiency]. Master of Architecture Thesis, Chulalongkorn University, Bangkok, Thailand.

Chulsukon,P., Haberl, J. & Sylvestster, K. (2002). Development and analysis of a sustainable low energy house in a hot and humid climate. Proceedings of the Thirteenth Symposium on Improving Building Systems in Hot and Humid Climates, Houston, TX, May 20-22, 2002, 1-13.

Corrado, V. & Mechri, H. E. (2009). Uncertainty and sensitivity analysis for building energy rating. Journal of Building Physics, 33(2), 125–156.

De Wilde, P. & Tian, W. (2010). Predicting the performance of an office under climate change: A study of metrics, sensitivity and zonal resolution. Energy and Buildings, 42(10), 1674–1684.

De Almeida Ferreira Tavares, P. F. & de Oliveira Gomes Martins, A. M. (2007). Energy efficient building design using sensitivity analysis—A case study. Energy and Buildings, 39(1), 23–31.

Dell’Isola, A. & CVS, S. J. K. F. (2003). Life cycle costing for facilities. Kingston, MA: RSMeans.

Firth, S. K., Lomas, K. J. & Wright, A. J. (2010). Targeting household energy-efficiency measures using sensitivity analysis. Building Research & Information, 38(1), 25–41.

Garcia Sanchez, D., Lacarrière, B., Musy, M. & Bourges, B. (2014). Application of sensitivity analysis in building energy simulations: Com-bining first-and second-order elementary effects methods. Energy and Buildings, 68, Part C, 741–750.

Guerra-Santin, O. & Itard, L. (2010). Occupants’ behaviour: determinants and effects on residential heating consumption. Building Research & Information, 38(3), 318–338.

Habara, H., Tasue, R. & Shimoda, Y. (2013, August). Survey on the occupant behavior relating to window and air conditioner operation in the residential buildings. Proceedings of BS2013:13th Conference of International Building Per-formance Simulation Association, Chambéry, France, August 26-28, 2013, 1-7.

Hamby, D. M. (1994). A review of techniques for parameter sensitivity analysis of environmental models.Environmental Monitoring and Assessment, 32(2), 135–154.

Hamby, D. M. (1995). A comparison of sensitivity analysis techniques. Health Physics, 68(2), 195–204.

Heiselberg, P., Brohus, H., Hesselholt, A., Rasmussen, H., Seinre, E. & Thomas, S. (2009). Applicationof sensitivity analysis in design of sustainable buildings. Renewable Energy, 34(9), 2030–2036.

Hemsath, T. L. & Alagheband Bandhosseini, K. (2015). Sensitivity analysis evaluating basic building geometry’s effect on energy use. Renewable Energy, 76, 526–538.

Heo, Y., Augenbroe, G., Graziano, D., Muehleisen, R. T. & Guzowski, L. (2015). Scalable methodology for large scale building energy improvement: Relevance of calibration in model-based retrofit analysis. Building and Environment, 342-350.

Heo, Y., Choudhary, R. & Augenbroe, G. A. (2012). Calibration of building energy models for retrofit analysis under uncertainty. Energy and Buildings, 47, 550–560.

Hirsch, J. (2010). eQuest Introductory Tutorial, version 3.64. Camarillo, CA: N.P.

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.

Hughes, M., Palmer, J., Cheng, V. & Shipworth, D. (2014). Global sensitivity analysis of England’s housingenergy model. Journal of Building Performance Simulation, 1–12.

Hygh, J. S., DeCarolis, J. F., Hill, D. B. & Ranjithan, S. R. (2012). Multivariate regression as an energy assessment tool in early building design. Building and Environment, 57, 165–175.

Kittichanthira, P. (2010). ประสิทธิภาพการประหยัดพลังงานของอุปกรณ์กันแดดแบบผนัง 2 ชั้น: กรณีศึกษาอาคารพัก อาศัยในกรุงเทพมหานคร [Energy saving from double-skin shading devices of residential in Bangkok]. Master of Architecture Thesis, Chulalongkorn University, Bangkok, Thailand.

Lam, J. C. & Hui, S. C. M. (1996). Sensitivity analysis of energy performance of office buildings. Building and Environment, 31(1), 27–39.

Malasri, E. (1996). การประหยัดพลังงานที่ใช้ในระบบปรับอากาศบ้านพักอาศัย [Energy conservation in air-conditioning system in residential housings]. Master of Science Thesis, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand.

Malhotra, M. (2006). An analysis of maximum residential energy-efficiency in hot and humid climates. Master Thesis, Texas A&M University. Retrieved from

Malhotra, M. & Haberl, J. (2006). An analysis of building envelope upgrade for residential energy efficiency in hot and humid climates. Second National IBPSA-USA Conference SimBuild 2006, Cambridge, MA, August 2-4, 2006, 200-209. Retrieved from

Masuda, H. & Claridge, D. E. (2014). Statistical modeling of the building energy balance variable for screening of metered energy use in large com-mercial buildings. Energy and Buildings, 77, 292–303.

Mechri, H. E., Capozzoli, A. & Corrado, V. (2010). Use of the ANOVA approach for sensitive building energy design. Applied Energy, 87(10), 3073–3083.

Murray, S. N. & O’Sullivan, D. T. J. (2012). An optimization methodology and sensitivity analysis of existing building retrofits. Proceedings of First Building Simulation and Optimization Conference Loughborough, UK, September 10-11, 2012, 110-116.

On-ngam, K. (2011). การศึกษาเปรียบเทียบวัสดุเปลือกอาคารสำหรับบ้านพักอาศัยในเชิงการประหยัดพลังงานและราคา[The comparative study of materials for residential building envelope in terms of energy saving and cost]. Independent Study Master of Architecture (Building Innovation), Kasetsart University, Bangkok, Thailand.

Padunghus, C. (2007). การศึกษาการปรับสภาพแวดล้อมบ้านจัดสรร เพื่อการประหยัดพลังงานในเครื่องปรับอากาศ[A study of a change in housing landscape for energy saving in an air conditioning]. Independent Study Master of Sciences (Renewable Energy), Naresuan University, Phitsanulok, Thailand.

Pereira, W., Bögl, A. & Natschläger, T. (2014). Sensitivity analysis and validation of an Energy Plus Model of a house in upper Austria. Energy Procedia, 62, 472–481.

Petr, K., Filip, J., Karel, K. & Jan, H. (2007). Technique of uncertainty and sensitivity analysis for sustainable building energy systems performance calculations. Prodeedings of the 10th IBPSA Building Simulation Conference, 3-5 September, 629-636. Beijing: Tsinghua University.

Saltelli, A. (2002). Sensitivity analysis for importance assessment. Risk Analysis: An Official Publication of the Society for Risk Analysis, 22(3), 579–590.

Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana M. & Tarantola, S. (2008). Global sensitivity analysis: The primer. Chichester, England; Hoboken, NJ: Wiley-Interscience.

Silva, A. S. & Ghisi, E. (2014). Uncertainty analysis of user behavior and physical parameters in residential building performance simulation. Energy and Buildings, 76, 381–391.

Siribangkeadpol, P. (2000). การศึกษาอิทธิพลของภูมิอากาศต่อการออกแบบบ้านพักอาศัยเพื่อการประหยัดพลังงาน[The study of the influence of the climate on the design of energy conservation house]. Master of Engineering Thesis (Energy Management Technology), King Mongkut’s University of Technology Thonburi, Bangkok, Thailand.

Soebarto, V. I. & Williamson, T. J. (2001). Multi-criteria assessment of building performance: theory and implementation. Building and Environment, 36(6), 681–690.

Song, J., Wei, L., Sun, Y. & Tian, W. (2004). Implementation of Meta-modelling for Sensitivity Analysis in Building Energy Analysis. Presented at the eSim 2004, Canada. Retrieved from

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.

Taepipatpong, K. (2010). การศึกษาวัสดุและอัตราส่วนพื้นที่ช่องเปิดต่อพื้นที่ผนังอาคารเพื่อการลดการใช้พลังงานใน อาคารพักอาศัย [The study of materials and window to wall ratio for reducing energy consumption of residential buildings]. Master of Architecture Thesis, Thammasat University, Pathumthani, Thailand.

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

Tabtimtong, S. (2010). การวิเคราะห์การประหยัดพลังงานในเครื่องปรับอากาศสำหรับบ้านพักอาศัย [Analysis of energy-saving of air conditioners for living home]. Master of Science Thesis (Electrical Engineering), King Mongkut’s University of Technology Thonburi, Bangkok, Thailand.

Turner, C. & Frankel, M. (2008). Energy performance of LEED for new construction | U.S. Green Building Council (Final Report), p. 42. Vancouver, WA: New Building Institute. Retrieved from

Yasue, R., Habara, H., Nakamichi, A. & Shimoda, Y. (2013). Modeling the occupant behavior relating to window and air conditioner operation based on survey results. Proceedings of BS2013: 13th Conference of International Building Performance Simulation Association, Chambéry, France, August 26-28, 2013, 1415-1458.

Yildiz, Y., Korkmaz, K., Göksal özbalta, T. & Durmus Arsan, Z. (2012). An approach for developing sensitive design parameter guidelines to reduce the energy requirements of low-rise apartment buildings. Applied Energy, 93, 337–347.

Yudelson, J. (2010). Green existing buildings. New York, NY: McGraw-Hill.

Westphal, O. S. & Lamberts, R. (2005). Building simulation calibration using sensitivity analysis abstract.Proceedings of Ninth International IBPSA Conference Montréal, Canada, August 15-18, 2005, 1331-1338.

Wilde, P. de & Tian, W. (2009). Identification of key factors for uncertainty in the prediction of the thermal performance of an office building under climate change. Building Simulation, 2(3), 157–174.

Wimolwatvatee, A. (2004). แนวทางการออกแบบปรับปรุงบ้านเอื้ออาทร เพื่อสภาวะน่าสบายและการใช้พลังงานอย่างมี ประสิทธิภาพ [Design guidelines for improving thermal comfort and energy efficiency of Baan Eur Ah-Torn]. Master of Architecture Thesis, Chulalongkorn University, Bangkok, Thailand.