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Volumn 124, Issue , 2014, Pages 325-334

Methods for benchmarking building energy consumption against its past or intended performance: An overview

Author keywords

Building; Energy benchmarking; Overview

Indexed keywords

BUILDINGS; ENERGY CONSERVATION; ENERGY UTILIZATION;

EID: 84897526846     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2014.03.020     Document Type: Review
Times cited : (187)

References (58)
  • 1
    • 84897481090 scopus 로고    scopus 로고
    • IEA, Key world energy statistics
    • IEA, Key world energy statistics; 2009.
    • (2009)
  • 3
    • 61349159364 scopus 로고    scopus 로고
    • Progress and methodologies of lifecycle commissioning of HVAC systems to enhance building sustainability
    • Xiao F., Wang S. Progress and methodologies of lifecycle commissioning of HVAC systems to enhance building sustainability. Renew Sustain Energy Rev 2009, 13:1144-1149.
    • (2009) Renew Sustain Energy Rev , vol.13 , pp. 1144-1149
    • Xiao, F.1    Wang, S.2
  • 6
    • 57649198760 scopus 로고    scopus 로고
    • Review of possibilities and necessities for building lifetime commissioning
    • Djuric N., Novakovic V. Review of possibilities and necessities for building lifetime commissioning. Renew Sustain Energy Rev 2009, 13:486-492.
    • (2009) Renew Sustain Energy Rev , vol.13 , pp. 486-492
    • Djuric, N.1    Novakovic, V.2
  • 7
    • 0039405614 scopus 로고    scopus 로고
    • Simplified energy analysis using the modified bin method - prepared for the American Society of Heating
    • Refrigerating and Air-Conditioning Engineers, ASHRAE, Atlanta, GA; 1983.
    • Knebel DE. Simplified energy analysis using the modified bin method - prepared for the American Society of Heating, Refrigerating and Air-Conditioning Engineers, ASHRAE, Atlanta, GA; 1983.
    • Knebel, D.E.1
  • 8
    • 0034165623 scopus 로고    scopus 로고
    • Energy plus: energy simulation program
    • Crawley D.B., Lawrie L.K., Pedersen C.O., et al. Energy plus: energy simulation program. ASHRAE J. 2000, 42:49-56.
    • (2000) ASHRAE J. , vol.42 , pp. 49-56
    • Crawley, D.B.1    Lawrie, L.K.2    Pedersen, C.O.3
  • 10
    • 0035324636 scopus 로고    scopus 로고
    • Computer-aided building energy analysis techniques
    • Al-Homoud M.S. Computer-aided building energy analysis techniques. Build Environ 2001, 36:421-433.
    • (2001) Build Environ , vol.36 , pp. 421-433
    • Al-Homoud, M.S.1
  • 11
    • 20344363647 scopus 로고    scopus 로고
    • Automated whole building diagnostics
    • Roth K., Llana P., Westphalen D., et al. Automated whole building diagnostics. ASHRAE J 2005, 47:82-84.
    • (2005) ASHRAE J , vol.47 , pp. 82-84
    • Roth, K.1    Llana, P.2    Westphalen, D.3
  • 12
    • 79551573848 scopus 로고    scopus 로고
    • Review of building energy-use performance benchmarking methodologies
    • Chung W. Review of building energy-use performance benchmarking methodologies. Appl Energy 2011, 88:1470-1479.
    • (2011) Appl Energy , vol.88 , pp. 1470-1479
    • Chung, W.1
  • 13
    • 84860223914 scopus 로고    scopus 로고
    • A review on the prediction of building energy consumption
    • Zhao H., Magoules F. A review on the prediction of building energy consumption. Renew Sustain Energy Rev 2012, 16:3586-3592.
    • (2012) Renew Sustain Energy Rev , vol.16 , pp. 3586-3592
    • Zhao, H.1    Magoules, F.2
  • 14
    • 12844271105 scopus 로고    scopus 로고
    • Quantification methods of technical building performance
    • Augenbroe G., Park C. Quantification methods of technical building performance. Build Res Inf 2005, 33:159-172.
    • (2005) Build Res Inf , vol.33 , pp. 159-172
    • Augenbroe, G.1    Park, C.2
  • 15
    • 84857063485 scopus 로고    scopus 로고
    • Calibration of building energy models for retrofit analysis under uncertainty
    • Heo Y., Choudhary R., Augenbroe G.A. Calibration of building energy models for retrofit analysis under uncertainty. Energy Build 2012, 47:550-560.
    • (2012) Energy Build , vol.47 , pp. 550-560
    • Heo, Y.1    Choudhary, R.2    Augenbroe, G.A.3
  • 16
    • 0036497459 scopus 로고    scopus 로고
    • Model-based benchmarking with application to laboratory buildings
    • Federspiel C., Zhang Q., Arens E. Model-based benchmarking with application to laboratory buildings. Energy Build 2002, 34:203-214.
    • (2002) Energy Build , vol.34 , pp. 203-214
    • Federspiel, C.1    Zhang, Q.2    Arens, E.3
  • 17
    • 33749236977 scopus 로고    scopus 로고
    • An energy benchmarking model for ventilation systems of air-conditioned offices in subtropical climates
    • Mui K.W., Wong L.T., Law L.Y. An energy benchmarking model for ventilation systems of air-conditioned offices in subtropical climates. Appl Energy 2007, 84:89-98.
    • (2007) Appl Energy , vol.84 , pp. 89-98
    • Mui, K.W.1    Wong, L.T.2    Law, L.Y.3
  • 18
    • 36549076471 scopus 로고    scopus 로고
    • Contrasting the capabilities of building energy performance simulation programs
    • Crawley D.B., Hand J.W., Kummert M., et al. Contrasting the capabilities of building energy performance simulation programs. Build Environ 2008, 43:661-673.
    • (2008) Build Environ , vol.43 , pp. 661-673
    • Crawley, D.B.1    Hand, J.W.2    Kummert, M.3
  • 19
    • 0032671092 scopus 로고    scopus 로고
    • Automated fault detection and diagnostics for outdoor-air ventilation systems and economizers: methodology and results from field testing
    • Katipamula S., Pratt R., Chassin D., et al. Automated fault detection and diagnostics for outdoor-air ventilation systems and economizers: methodology and results from field testing. ASHRAE Trans 1999, 105:555-567.
    • (1999) ASHRAE Trans , vol.105 , pp. 555-567
    • Katipamula, S.1    Pratt, R.2    Chassin, D.3
  • 20
    • 84897509584 scopus 로고    scopus 로고
    • Automated diagnostics from DDC data - PACRAT.
    • In: Proceedings of the 8th National conference on building commissioning, Kansas City, U.S., May 3-5
    • Santos J, Brightbill L. Automated diagnostics from DDC data - PACRAT. In: Proceedings of the 8th National conference on building commissioning, Kansas City, U.S., May 3-5, 2000.
    • (2000)
    • Santos, J.1    Brightbill, L.2
  • 21
    • 85021237937 scopus 로고    scopus 로고
    • Facility dynamics.
    • Facility dynamics. ; 2013. http://www.facilitydynamics.com/software.html.
    • (2013)
  • 22
    • 3042585649 scopus 로고    scopus 로고
    • Comparative guide to emerging diagnostic tools for large commercial HVAC systems
    • Lawrence Berkeley National Laboratory Report (No. 48629)
    • Friedman H, Piette MA. Comparative guide to emerging diagnostic tools for large commercial HVAC systems, Lawrence Berkeley National Laboratory Report (No. 48629); 2001.
    • (2001)
    • Friedman, H.1    Piette, M.A.2
  • 23
    • 0025519319 scopus 로고
    • A regression-based approach to short-term system load forecasting
    • Papalexopoulos A.D., Hesterberg T.C. A regression-based approach to short-term system load forecasting. IEEE Trans Power Syst 1990, 5:1535-1547.
    • (1990) IEEE Trans Power Syst , vol.5 , pp. 1535-1547
    • Papalexopoulos, A.D.1    Hesterberg, T.C.2
  • 24
    • 84876251690 scopus 로고    scopus 로고
    • Re-evaluation of building cooling load prediction models for use in humid subtropical area
    • Li Z., Huang G. Re-evaluation of building cooling load prediction models for use in humid subtropical area. Energy Build 2013, 62:442-449.
    • (2013) Energy Build , vol.62 , pp. 442-449
    • Li, Z.1    Huang, G.2
  • 25
    • 77951523599 scopus 로고    scopus 로고
    • Black-box models for fault detection and performance monitoring of buildings
    • Jacob D., Dietz S., Komhard S., et al. Black-box models for fault detection and performance monitoring of buildings. J Build Perform Simul 2010, 3:53-62.
    • (2010) J Build Perform Simul , vol.3 , pp. 53-62
    • Jacob, D.1    Dietz, S.2    Komhard, S.3
  • 26
    • 34250884664 scopus 로고    scopus 로고
    • Multiple ARMAX modelling scheme for forecasting air conditioning system performance
    • Yiu J.C., Wang S. Multiple ARMAX modelling scheme for forecasting air conditioning system performance. Energy Convers Manage 2007, 48:2276-2285.
    • (2007) Energy Convers Manage , vol.48 , pp. 2276-2285
    • Yiu, J.C.1    Wang, S.2
  • 27
    • 64849083683 scopus 로고    scopus 로고
    • Applying support vector machine to predict hourly cooling load in the building
    • Li Q., Meng Q., Cai J., et al. Applying support vector machine to predict hourly cooling load in the building. Appl Energy 2009, 86:2249-2256.
    • (2009) Appl Energy , vol.86 , pp. 2249-2256
    • Li, Q.1    Meng, Q.2    Cai, J.3
  • 28
    • 56049088473 scopus 로고    scopus 로고
    • Predicting hourly cooling load in the building: a comparison of support vector machine and different artificial neural networks
    • Li Q., Meng Q., Cai J., et al. Predicting hourly cooling load in the building: a comparison of support vector machine and different artificial neural networks. Energy Convers Manage 2009, 50:90-96.
    • (2009) Energy Convers Manage , vol.50 , pp. 90-96
    • Li, Q.1    Meng, Q.2    Cai, J.3
  • 29
    • 70649112212 scopus 로고    scopus 로고
    • Building cooling load forecasting model based on LS-SVM.
    • Asia-Pacific conference on information processing, Shenzhen, China, July 18-19
    • Li X, Lu J, Ding L et al. Building cooling load forecasting model based on LS-SVM. In: Asia-Pacific conference on information processing, Shenzhen, China, July 18-19, 2009.
    • (2009)
    • Li, X.1    Lu, J.2    Ding, L.3
  • 30
    • 13244270060 scopus 로고    scopus 로고
    • Applying support vector machines to predict building energy consumption in tropical region
    • Dong B., Cao C., Lee S.E. Applying support vector machines to predict building energy consumption in tropical region. Energy Build 2005, 37:545-553.
    • (2005) Energy Build , vol.37 , pp. 545-553
    • Dong, B.1    Cao, C.2    Lee, S.E.3
  • 31
    • 84864212460 scopus 로고    scopus 로고
    • Gaussian process modelling for measurement and verification of building energy savings
    • Heo Y., Zavala V.M. Gaussian process modelling for measurement and verification of building energy savings. Energy Build 2012, 53:7-18.
    • (2012) Energy Build , vol.53 , pp. 7-18
    • Heo, Y.1    Zavala, V.M.2
  • 32
    • 84871712826 scopus 로고    scopus 로고
    • Calibration and uncertainty analysis for computer models - a meta-model based approach for integrated building energy simulation
    • Manfren M., Aste N., Moshksar R. Calibration and uncertainty analysis for computer models - a meta-model based approach for integrated building energy simulation. Appl Energy 2013, 103:627-641.
    • (2013) Appl Energy , vol.103 , pp. 627-641
    • Manfren, M.1    Aste, N.2    Moshksar, R.3
  • 33
    • 2642538304 scopus 로고    scopus 로고
    • Modeling of the space and domestic hot-water heating energy-consumption in the residential sector using neural networks
    • Aydinalp M., Ugursal V.I., Fung A.S. Modeling of the space and domestic hot-water heating energy-consumption in the residential sector using neural networks. Appl Energy 2004, 79:159-178.
    • (2004) Appl Energy , vol.79 , pp. 159-178
    • Aydinalp, M.1    Ugursal, V.I.2    Fung, A.S.3
  • 35
    • 33646870136 scopus 로고    scopus 로고
    • Modeling and predicting building's energy use with artificial neural networks: methods and results
    • Karatasou S., Santamouris M., Geros V. Modeling and predicting building's energy use with artificial neural networks: methods and results. Energy Build 2006, 38:949-958.
    • (2006) Energy Build , vol.38 , pp. 949-958
    • Karatasou, S.1    Santamouris, M.2    Geros, V.3
  • 36
    • 84875818053 scopus 로고    scopus 로고
    • Development of an RDP neural network for building energy consumption fault detection and diagnosis
    • Magoules F., Zhao H., Elizondo D. Development of an RDP neural network for building energy consumption fault detection and diagnosis. Energy Build 2013, 62:133-138.
    • (2013) Energy Build , vol.62 , pp. 133-138
    • Magoules, F.1    Zhao, H.2    Elizondo, D.3
  • 37
    • 34250170125 scopus 로고    scopus 로고
    • Predicting electricity energy consumption: a comparison of regression analysis, decision tree and neural network
    • Tso G.K.F., Yau K.K.W. Predicting electricity energy consumption: a comparison of regression analysis, decision tree and neural network. Energy 2007, 32:1761-1768.
    • (2007) Energy , vol.32 , pp. 1761-1768
    • Tso, G.K.F.1    Yau, K.K.W.2
  • 38
    • 77955585423 scopus 로고    scopus 로고
    • A decision tree method for building energy demand modelling
    • Yu Z., Haghighat F., Fung B.C.M., et al. A decision tree method for building energy demand modelling. Energy Build 2010, 42:1637-1646.
    • (2010) Energy Build , vol.42 , pp. 1637-1646
    • Yu, Z.1    Haghighat, F.2    Fung, B.C.M.3
  • 39
    • 84870164656 scopus 로고    scopus 로고
    • Automatically calibrating a probabilistic graphical model of building energy consumption.
    • 11th IBPSA Conference, Glasgow, Scotland, July 27-30
    • Tarlow D, Peterman A, Schwegler BR, et al. Automatically calibrating a probabilistic graphical model of building energy consumption. In: 11th IBPSA Conference, Glasgow, Scotland, July 27-30, 2009.
    • (2009)
    • Tarlow, D.1    Peterman, A.2    Schwegler, B.R.3
  • 40
    • 31444445721 scopus 로고    scopus 로고
    • Simplified building model for transient thermal performances estimation using GA-based parameter identification
    • Wang S., Xu X. Simplified building model for transient thermal performances estimation using GA-based parameter identification. Int J Therm Sci 2006, 45:419-432.
    • (2006) Int J Therm Sci , vol.45 , pp. 419-432
    • Wang, S.1    Xu, X.2
  • 41
    • 0036163187 scopus 로고    scopus 로고
    • An inverse gray-box model for transient building load prediction
    • Braun J.E., Chaturvedi N. An inverse gray-box model for transient building load prediction. HVAC&R Res 2002, 8:73-99.
    • (2002) HVAC&R Res , vol.8 , pp. 73-99
    • Braun, J.E.1    Chaturvedi, N.2
  • 42
    • 46149086385 scopus 로고    scopus 로고
    • Development of methods for determining demand-limiting setpoint trajectories in buildings using short-term measurements
    • Lee K., Braun J.E. Development of methods for determining demand-limiting setpoint trajectories in buildings using short-term measurements. Build Environ 2008, 43:1755-1768.
    • (2008) Build Environ , vol.43 , pp. 1755-1768
    • Lee, K.1    Braun, J.E.2
  • 43
    • 84870218972 scopus 로고    scopus 로고
    • The use of normative energy calculation beyond building performance rating systems.
    • 12th IBPSA Conference, Sydney, Australia, November 14-16, 2011.
    • Lee SH, Zhao F, Augenbroe G. The use of normative energy calculation beyond building performance rating systems. In: 12th IBPSA Conference, Sydney, Australia, November 14-16, 2011.
    • Lee, S.H.1    Zhao, F.2    Augenbroe, G.3
  • 44
    • 84897496502 scopus 로고    scopus 로고
    • ISO 13789:2007, Thermal performance of buildings - Transmission and ventilation heat transfer coefficients - calculation method; 2007.
    • ISO, ISO 13789:2007, Thermal performance of buildings - Transmission and ventilation heat transfer coefficients - calculation method; 2007.
    • ISO
  • 45
    • 84897489373 scopus 로고    scopus 로고
    • EN 15241:2007, Ventilation for buildings. Calculation methods for energy losses due to ventilation and infiltration in buildings; 2007.
    • CEN, EN 15241:2007, Ventilation for buildings. Calculation methods for energy losses due to ventilation and infiltration in buildings; 2007.
    • CEN
  • 46
    • 84885933555 scopus 로고    scopus 로고
    • A novel dynamic modelling approach for predicting building energy performance
    • Lv X., Lu T., Kibert C.J. A novel dynamic modelling approach for predicting building energy performance. Appl Energy 2014, 114:91-103.
    • (2014) Appl Energy , vol.114 , pp. 91-103
    • Lv, X.1    Lu, T.2    Kibert, C.J.3
  • 47
    • 77953741930 scopus 로고    scopus 로고
    • The development and testing of an automated building commissioning analysis tool (ABCAT)
    • Master thesis, Texas A&M University, College Station, U.S.; 2007.
    • Curtin JM. The development and testing of an automated building commissioning analysis tool (ABCAT), Master thesis, Texas A&M University, College Station, U.S.; 2007.
    • Curtin, J.M.1
  • 48
    • 84870577507 scopus 로고    scopus 로고
    • Development and testing of an Automated Building Commissioning Analysis Tool (ABCAT)
    • Bynum J.D., Claridge D.E., Curtin J.M. Development and testing of an Automated Building Commissioning Analysis Tool (ABCAT). Energy Build 2012, 55:607-617.
    • (2012) Energy Build , vol.55 , pp. 607-617
    • Bynum, J.D.1    Claridge, D.E.2    Curtin, J.M.3
  • 49
    • 84870176717 scopus 로고    scopus 로고
    • Real time model-based energy diagnostics in buildings.
    • 12th IBPSA Conference, Sydney, Australia, November 14-16
    • O'Neill Z, Shashanka M, Pang X et al. Real time model-based energy diagnostics in buildings. In: 12th IBPSA Conference, Sydney, Australia, November 14-16, 2011.
    • (2011)
    • O'Neill, Z.1    Shashanka, M.2    Pang, X.3
  • 50
    • 79952460910 scopus 로고    scopus 로고
    • Multi-criteria optimisation using past, real time and predictive performance benchmarks
    • Torrens J.I., Keane M., Costa A., et al. Multi-criteria optimisation using past, real time and predictive performance benchmarks. Simul Model Pract Theory 2011, 19:1258-1265.
    • (2011) Simul Model Pract Theory , vol.19 , pp. 1258-1265
    • Torrens, J.I.1    Keane, M.2    Costa, A.3
  • 51
    • 78651436409 scopus 로고    scopus 로고
    • A screening methodology for implementing cost effective energy retrofit measures in Canadian office buildings
    • Chidiac S.E., Catania E.J.C., Morofsky E., et al. A screening methodology for implementing cost effective energy retrofit measures in Canadian office buildings. Energy Build 2011, 43:614-620.
    • (2011) Energy Build , vol.43 , pp. 614-620
    • Chidiac, S.E.1    Catania, E.J.C.2    Morofsky, E.3
  • 52
    • 77957711740 scopus 로고    scopus 로고
    • Methodology to estimate building energy consumption using EnergyPlus benchmark models
    • Fumo N., Mago P., Luck R. Methodology to estimate building energy consumption using EnergyPlus benchmark models. Energy Build 2010, 42:2331-2337.
    • (2010) Energy Build , vol.42 , pp. 2331-2337
    • Fumo, N.1    Mago, P.2    Luck, R.3
  • 53
    • 84878822289 scopus 로고    scopus 로고
    • On variations of space-heating energy use in office buildings
    • Lin H., Hong T. On variations of space-heating energy use in office buildings. Appl Energy 2013, 111:515-528.
    • (2013) Appl Energy , vol.111 , pp. 515-528
    • Lin, H.1    Hong, T.2
  • 54
    • 84870730207 scopus 로고    scopus 로고
    • Monitoring-based HVAC commissioning of an existing office building for energy efficiency
    • Wang L., Greenberg S., Flegel J., et al. Monitoring-based HVAC commissioning of an existing office building for energy efficiency. Appl Energy 2013, 102:1382-1390.
    • (2013) Appl Energy , vol.102 , pp. 1382-1390
    • Wang, L.1    Greenberg, S.2    Flegel, J.3
  • 56
    • 34247520494 scopus 로고    scopus 로고
    • Calibrating detailed building energy simulation programs with measured data - part I: general methodology (RP-1051)
    • Reddy T.A., Maor I., Panjapornpon C. Calibrating detailed building energy simulation programs with measured data - part I: general methodology (RP-1051). HVAC&R Res 2007, 13:221-241.
    • (2007) HVAC&R Res , vol.13 , pp. 221-241
    • Reddy, T.A.1    Maor, I.2    Panjapornpon, C.3
  • 57
    • 79960744120 scopus 로고    scopus 로고
    • Calibrating whole building energy models: an evidence-based methodology
    • Raftery P., Keane M., O'Nonnell J. Calibrating whole building energy models: an evidence-based methodology. Energy Build 2011, 43:2356-2364.
    • (2011) Energy Build , vol.43 , pp. 2356-2364
    • Raftery, P.1    Keane, M.2    O'Nonnell, J.3
  • 58
    • 0041752417 scopus 로고    scopus 로고
    • ASHRAE, ASHRAE Guideline 14: measurement of energy and demand savings
    • American Society of Heating, Refrigerating, and Air-conditioning Engineers Inc., Atlanta, GA, 2002.
    • ASHRAE, ASHRAE Guideline 14: measurement of energy and demand savings, American Society of Heating, Refrigerating, and Air-conditioning Engineers Inc., Atlanta, GA, 2002.


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