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Volumn 144, Issue , 2015, Pages 261-275

Modeling and forecasting energy consumption for heterogeneous buildings using a physical-statistical approach

Author keywords

Energy consumption; Heterogeneous buildings; Modeling method; Physical statistical approach

Indexed keywords

BUILDINGS; ELECTRIC LOAD FORECASTING; ENERGY UTILIZATION; FORECASTING; GAS EMISSIONS; GREENHOUSE GASES; STOCHASTIC MODELS; STOCHASTIC SYSTEMS; UNCERTAINTY ANALYSIS;

EID: 84925541167     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2014.12.019     Document Type: Article
Times cited : (163)

References (46)
  • 1
    • 84883770107 scopus 로고    scopus 로고
    • Energy refurbishment of existing buildings through the use of phase change materials: energy savings and indoor comfort in the cooling season
    • Ascione F., Bianco N., De Masi R.F., de Rossi F., Vanoli G.P. Energy refurbishment of existing buildings through the use of phase change materials: energy savings and indoor comfort in the cooling season. Appl Energy 2014, 113:990-1007.
    • (2014) Appl Energy , vol.113 , pp. 990-1007
    • Ascione, F.1    Bianco, N.2    De Masi, R.F.3    de Rossi, F.4    Vanoli, G.P.5
  • 2
    • 84861793096 scopus 로고    scopus 로고
    • Accurate quantitative estimation of energy performance of residential buildings using statistical machine learning tools
    • Tsanas A., Xifara A. Accurate quantitative estimation of energy performance of residential buildings using statistical machine learning tools. Energy Build 2012, 49:560-567.
    • (2012) Energy Build , vol.49 , pp. 560-567
    • Tsanas, A.1    Xifara, A.2
  • 3
    • 84896085639 scopus 로고    scopus 로고
    • Forecasting energy consumption of multi-family residential buildings using support vector regression: investigating the impact of temporal and spatial monitoring granularity on performance accuracy
    • Jain R.K., Smith K.M., Culligan P.J., Taylor J.E. Forecasting energy consumption of multi-family residential buildings using support vector regression: investigating the impact of temporal and spatial monitoring granularity on performance accuracy. Appl Energy 2014, 123:168-178.
    • (2014) Appl Energy , vol.123 , pp. 168-178
    • Jain, R.K.1    Smith, K.M.2    Culligan, P.J.3    Taylor, J.E.4
  • 4
    • 84900826776 scopus 로고    scopus 로고
    • Modeling an aggressive energy-efficiency scenario in long-range load forecasting for electric power transmission planning
    • Sanstad A.H., McMenamin S., Sukenik A., Barbose G.L., Goldman C.A. Modeling an aggressive energy-efficiency scenario in long-range load forecasting for electric power transmission planning. Appl Energy 2014, 128:265-276.
    • (2014) Appl Energy , vol.128 , pp. 265-276
    • Sanstad, A.H.1    McMenamin, S.2    Sukenik, A.3    Barbose, G.L.4    Goldman, C.A.5
  • 5
    • 52349093047 scopus 로고    scopus 로고
    • Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption
    • Neto A.H., Fiorelli F.A.S. Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption. Energy Build 2008, 40(12):2169-2176.
    • (2008) Energy Build , vol.40 , Issue.12 , pp. 2169-2176
    • Neto, A.H.1    Fiorelli, F.A.S.2
  • 6
    • 85067710714 scopus 로고    scopus 로고
    • DOE EnergyPlus engineering reference - the reference to EnergyPlus calculations. US Department of Energy, Washington, DC, 868
    • DOE EnergyPlus engineering reference - the reference to EnergyPlus calculations. US Department of Energy, Washington, DC, 868; 2007.
    • (2007)
  • 7
    • 84870611237 scopus 로고    scopus 로고
    • The impact of place-based affiliation networks on energy conservation: an holistic model that integrates the influence of buildings, residents and the neighborhood context
    • Xu X., Taylor J.E., Pisello A.L., Culligan P.J. The impact of place-based affiliation networks on energy conservation: an holistic model that integrates the influence of buildings, residents and the neighborhood context. Energy Build 2012, 55:637-646.
    • (2012) Energy Build , vol.55 , pp. 637-646
    • Xu, X.1    Taylor, J.E.2    Pisello, A.L.3    Culligan, P.J.4
  • 8
    • 84862821419 scopus 로고    scopus 로고
    • Forecasting nonlinear time series of energy consumption using a hybrid dynamic model
    • Lee Y.-S., Tong L.-I. Forecasting nonlinear time series of energy consumption using a hybrid dynamic model. Appl Energy 2012, 94:251-256.
    • (2012) Appl Energy , vol.94 , pp. 251-256
    • Lee, Y.-S.1    Tong, L.-I.2
  • 9
    • 80055052873 scopus 로고    scopus 로고
    • Future energy demand for public buildings in the context of climate change for Burkina Faso
    • Ouedraogo B.I., Levermore G.J., Parkinson J.B. Future energy demand for public buildings in the context of climate change for Burkina Faso. Build Environ 2012, 49:270-282.
    • (2012) Build Environ , vol.49 , pp. 270-282
    • Ouedraogo, B.I.1    Levermore, G.J.2    Parkinson, J.B.3
  • 10
    • 84868573652 scopus 로고    scopus 로고
    • Projections of energy services demand for residential buildings: insights from a bottom-up methodology
    • Gouveia J.P., Fortes P., Seixas J. Projections of energy services demand for residential buildings: insights from a bottom-up methodology. Energy 2012, 47(1):430-442.
    • (2012) Energy , vol.47 , Issue.1 , pp. 430-442
    • Gouveia, J.P.1    Fortes, P.2    Seixas, J.3
  • 11
    • 84871789129 scopus 로고    scopus 로고
    • Feasibility study on a novel methodology for short-term real-time energy demand prediction using weather forecasting data
    • Kwak Y., Seo D., Jang C., Huh J.-H. Feasibility study on a novel methodology for short-term real-time energy demand prediction using weather forecasting data. Energy Build 2013, 57:250-260.
    • (2013) Energy Build , vol.57 , pp. 250-260
    • Kwak, Y.1    Seo, D.2    Jang, C.3    Huh, J.-H.4
  • 12
    • 84873888789 scopus 로고    scopus 로고
    • Upgrade of an artificial neural network prediction method for electrical consumption forecasting using an hourly temperature curve model
    • Roldan-Blay C., Escriva-Escriva G., Alvarez-Bel C., Roldan-Porta C., Rodriguez-Garcia J. Upgrade of an artificial neural network prediction method for electrical consumption forecasting using an hourly temperature curve model. Energy Build 2013, 60:38-46.
    • (2013) Energy Build , vol.60 , pp. 38-46
    • Roldan-Blay, C.1    Escriva-Escriva, G.2    Alvarez-Bel, C.3    Roldan-Porta, C.4    Rodriguez-Garcia, J.5
  • 13
    • 84871874052 scopus 로고    scopus 로고
    • Development of polynomial regression models for composite dynamic envelopes' thermal performance forecasting
    • Mavromatidis L.E., Bykalyuk A., Lequay H. Development of polynomial regression models for composite dynamic envelopes' thermal performance forecasting. Appl Energy 2013, 104:379-391.
    • (2013) Appl Energy , vol.104 , pp. 379-391
    • Mavromatidis, L.E.1    Bykalyuk, A.2    Lequay, H.3
  • 14
    • 48949090769 scopus 로고    scopus 로고
    • Electricity consumption and efficiency trends in the enlarged European Union - Status Report 2006
    • European Commission: DG Joint Research Centre;
    • Bertoldi P, Atanasiu B. Electricity consumption and efficiency trends in the enlarged European Union - Status Report 2006. European Commission: DG Joint Research Centre; 2007.
    • (2007)
    • Bertoldi, P.1    Atanasiu, B.2
  • 15
    • 84859799055 scopus 로고    scopus 로고
    • The Impact of Control Technology
    • IEEE Control Systems Society, 2011. Available at.
    • Samad T, Annaswamy AM (Eds.), The Impact of Control Technology, IEEE Control Systems Society, 2011. Available at. http://www.ieeecss.org.
    • Samad, T.1    Annaswamy, A.M.2
  • 16
    • 69249216516 scopus 로고    scopus 로고
    • The effect of occupancy and building characteristics on energy use for space and water heating in Dutch residential stock
    • Santin O.G., Itard L., Visscher H. The effect of occupancy and building characteristics on energy use for space and water heating in Dutch residential stock. Energy Build 2009, 41(11):1223-1232.
    • (2009) Energy Build , vol.41 , Issue.11 , pp. 1223-1232
    • Santin, O.G.1    Itard, L.2    Visscher, H.3
  • 17
    • 84885933555 scopus 로고    scopus 로고
    • A novel dynamic modeling approach for predicting building energy performance
    • Lü X., Lu T., Kibert C., Viljanen M. A novel dynamic modeling approach for predicting building energy performance. Appl Energy 2014, 114:91-103.
    • (2014) Appl Energy , vol.114 , pp. 91-103
    • Lü, X.1    Lu, T.2    Kibert, C.3    Viljanen, M.4
  • 18
    • 0040294424 scopus 로고
    • Direct solar radiation available on clear days
    • Threlkeld J.L., Jordan R.C. Direct solar radiation available on clear days. ASHRAE Trans 1958, 64:45-48.
    • (1958) ASHRAE Trans , vol.64 , pp. 45-48
    • Threlkeld, J.L.1    Jordan, R.C.2
  • 19
    • 85067730813 scopus 로고    scopus 로고
    • Handbook: HVAC Systems and Equipment 2012, SI edition, American society of heating
    • Refrigeration and Air-Conditioning Engineers, Atlanta, GA, 2012.
    • ASHRAE 2012. Handbook: HVAC Systems and Equipment 2012, SI edition, American society of heating. Refrigeration and Air-Conditioning Engineers, Atlanta, GA, 2012.
    • (2012)
  • 20
    • 33745084855 scopus 로고    scopus 로고
    • A new analytical method to simulate heat transfer process in buildings
    • Lü X., Lu T., Viljanen M. A new analytical method to simulate heat transfer process in buildings. Appl Ther Eng 2006, 26:1901-1909.
    • (2006) Appl Ther Eng , vol.26 , pp. 1901-1909
    • Lü, X.1    Lu, T.2    Viljanen, M.3
  • 21
    • 0042817453 scopus 로고
    • On the likelihood of a time series model
    • Akaike H. On the likelihood of a time series model. The Statistician 1978, 27:217-235.
    • (1978) The Statistician , vol.27 , pp. 217-235
    • Akaike, H.1
  • 22
    • 85033517914 scopus 로고
    • A Bayesian extension of the minimum AIC procedure of autoregressive model fitting
    • Akaike H. A Bayesian extension of the minimum AIC procedure of autoregressive model fitting. Biometrika 1979, 66:237-242.
    • (1979) Biometrika , vol.66 , pp. 237-242
    • Akaike, H.1
  • 25
    • 0001922398 scopus 로고
    • (1978) Generalized reduced gradient software for linearly and nonlinearly constrained problems
    • Sijthoff and Noordhoff, Holland, H.J. Greenberg (Ed.)
    • Lasdon L.S., Waren A.D. (1978) Generalized reduced gradient software for linearly and nonlinearly constrained problems. Design and implementation of optimization software 1978, 335-362. Sijthoff and Noordhoff, Holland. H.J. Greenberg (Ed.).
    • (1978) Design and implementation of optimization software , pp. 335-362
    • Lasdon, L.S.1    Waren, A.D.2
  • 26
    • 84875152479 scopus 로고    scopus 로고
    • Multiscale Markov models with random transitions for energy demand management
    • Meidani H., Ghanem R. Multiscale Markov models with random transitions for energy demand management. Energy Build 2013, 61:267-274.
    • (2013) Energy Build , vol.61 , pp. 267-274
    • Meidani, H.1    Ghanem, R.2
  • 27
    • 84870755239 scopus 로고    scopus 로고
    • Predicting the diversity of internal temperatures from the English residential sector using panel methods
    • Kelly S., Shipworth M., Shipworth D., Gentry M., Wright A., Pollitt M., et al. Predicting the diversity of internal temperatures from the English residential sector using panel methods. Appl Energy 2013, 102:601-621.
    • (2013) Appl Energy , vol.102 , pp. 601-621
    • Kelly, S.1    Shipworth, M.2    Shipworth, D.3    Gentry, M.4    Wright, A.5    Pollitt, M.6
  • 28
    • 85067730926 scopus 로고    scopus 로고
    • Applied & computational mathematics challenges for the design and control of dynamic energy systems, Lawrence Livermore National Laboratory
    • Available at.
    • Brown DL, Burns JA, Collis S, Grosh J, Jacobson CA, Johansen H, Mezic I, Narayanan S, Wetter M. Applied & computational mathematics challenges for the design and control of dynamic energy systems, Lawrence Livermore National Laboratory, 2011. Available at. https://e-reports-ext.llnl.gov/pdf/473349.pdf.
    • (2011)
    • Brown, D.L.1    Burns, J.A.2    Collis, S.3    Grosh, J.4    Jacobson, C.A.5    Johansen, H.6    Mezic, I.7    Narayanan, S.8    Wetter, M.9
  • 29
    • 67650761091 scopus 로고    scopus 로고
    • Modeling of end-use energy consumption in the residential sector: a review of modeling techniques
    • Swan L.G., Ugursal V.I. Modeling of end-use energy consumption in the residential sector: a review of modeling techniques. Renew Sust Energy Rev 2009, 13:1819-1835.
    • (2009) Renew Sust Energy Rev , vol.13 , pp. 1819-1835
    • Swan, L.G.1    Ugursal, V.I.2
  • 32
    • 84885907163 scopus 로고    scopus 로고
    • Energy demand characteristics and the potential for energy efficiency in sports statium and arenas
    • Duke University;
    • Dietrich A, Melville C. Energy demand characteristics and the potential for energy efficiency in sports statium and arenas. Duke University; 2011.
    • (2011)
    • Dietrich, A.1    Melville, C.2
  • 36
    • 0000028873 scopus 로고    scopus 로고
    • A reality check for data snooping
    • White H. A reality check for data snooping. Econometrica 2000, 68:1097-1126.
    • (2000) Econometrica , vol.68 , pp. 1097-1126
    • White, H.1
  • 39
    • 85067719167 scopus 로고    scopus 로고
    • Natick, Massachusetts, United States: The MathWorks, Inc.;
    • MATLAB and Statistics Toolbox Release. Natick, Massachusetts, United States: The MathWorks, Inc.; 2012b.
    • (2012)
  • 41
    • 84920195266 scopus 로고    scopus 로고
    • Short-term load forecasting using a kernel-based support vector regression combination model
    • Che J.X., Wang J.Z. Short-term load forecasting using a kernel-based support vector regression combination model. Appl Energy 2014, 132:602-609.
    • (2014) Appl Energy , vol.132 , pp. 602-609
    • Che, J.X.1    Wang, J.Z.2
  • 42
    • 84893302125 scopus 로고    scopus 로고
    • Continuous hyperparameter optimization for large-scale recommender systems
    • In: IEEE international conference on big data. Silicon Valley, CA (USA);
    • Chan S, Treleaven P, Capra L. Continuous hyperparameter optimization for large-scale recommender systems. In: IEEE international conference on big data. Silicon Valley, CA (USA); 2013. p 350-8.
    • (2013) , pp. 350-358
    • Chan, S.1    Treleaven, P.2    Capra, L.3
  • 43
    • 84859918822 scopus 로고    scopus 로고
    • Prediction of CO concentrations based on a hybrid partial least square and support vector machine model
    • Yeganeh B., Motlagh M.S.P., Rashidi Y., Kamalan H. Prediction of CO concentrations based on a hybrid partial least square and support vector machine model. Atmos Environ 2012, 55:357-365.
    • (2012) Atmos Environ , vol.55 , pp. 357-365
    • Yeganeh, B.1    Motlagh, M.S.P.2    Rashidi, Y.3    Kamalan, H.4
  • 44
    • 77956907243 scopus 로고    scopus 로고
    • On over-fitting in model selection and subsequent selection bias in performance evaluation
    • Cawley G.C., Talbot N.L.C. On over-fitting in model selection and subsequent selection bias in performance evaluation. J Mach Learn Res 2010, 11:2079-2107.
    • (2010) J Mach Learn Res , vol.11 , pp. 2079-2107
    • Cawley, G.C.1    Talbot, N.L.C.2
  • 45
    • 0008202233 scopus 로고    scopus 로고
    • Duality and geometry in SVM classifiers
    • In: Proceedings of the Seventeenth International conference on machine learning (ICML'00);
    • Bennett KP, Bredensteiner EJ. Duality and geometry in SVM classifiers. In: Proceedings of the Seventeenth International conference on machine learning (ICML'00); 2000. p. 57-64.
    • (2000) , pp. 57-64
    • Bennett, K.P.1    Bredensteiner, E.J.2
  • 46
    • 33646516358 scopus 로고    scopus 로고
    • A geometric approach to support vector machine (SVM) classification
    • IEEE Transactions on
    • Mavroforakis ME, Theodoridis S. A geometric approach to support vector machine (SVM) classification. Neural Networks. IEEE Transactions on 17; 2006. p. 671-82.
    • (2006) Neural Networks , vol.17 , pp. 671-682
    • Mavroforakis, M.E.1    Theodoridis, S.2


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