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Calibration and uncertainty analysis for computer models – A meta-model based approach for integrated building energy simulation

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Cited by:

  1. Chaudhary, Gaurav & New, Joshua & Sanyal, Jibonananda & Im, Piljae & O’Neill, Zheng & Garg, Vishal, 2016. "Evaluation of “Autotune” calibration against manual calibration of building energy models," Applied Energy, Elsevier, vol. 182(C), pages 115-134.
  2. Brandão de Vasconcelos, Ana & Pinheiro, Manuel Duarte & Manso, Armando & Cabaço, António, 2015. "A Portuguese approach to define reference buildings for cost-optimal methodologies," Applied Energy, Elsevier, vol. 140(C), pages 316-328.
  3. Massimiliano Manfren & Maurizio Sibilla & Lamberto Tronchin, 2021. "Energy Modelling and Analytics in the Built Environment—A Review of Their Role for Energy Transitions in the Construction Sector," Energies, MDPI, vol. 14(3), pages 1-29, January.
  4. Enrico Fabrizio & Valentina Monetti, 2015. "Methodologies and Advancements in the Calibration of Building Energy Models," Energies, MDPI, vol. 8(4), pages 1-27, March.
  5. Sun, Kaiyu & Hong, Tianzhen & Taylor-Lange, Sarah C. & Piette, Mary Ann, 2016. "A pattern-based automated approach to building energy model calibration," Applied Energy, Elsevier, vol. 165(C), pages 214-224.
  6. Keshtkar, Azim & Arzanpour, Siamak, 2017. "An adaptive fuzzy logic system for residential energy management in smart grid environments," Applied Energy, Elsevier, vol. 186(P1), pages 68-81.
  7. Cheoljoon Jeong & Ziang Xu & Albert S. Berahas & Eunshin Byon & Kristen Cetin, 2023. "Multiblock Parameter Calibration in Computer Models," INFORMS Joural on Data Science, INFORMS, vol. 2(2), pages 116-137, October.
  8. Tian, Wei & Heo, Yeonsook & de Wilde, Pieter & Li, Zhanyong & Yan, Da & Park, Cheol Soo & Feng, Xiaohang & Augenbroe, Godfried, 2018. "A review of uncertainty analysis in building energy assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 285-301.
  9. Manfren, Massimiliano & Nastasi, Benedetto & Groppi, Daniele & Astiaso Garcia, Davide, 2020. "Open data and energy analytics - An analysis of essential information for energy system planning, design and operation," Energy, Elsevier, vol. 213(C).
  10. Carlos Fernández Bandera & Germán Ramos Ruiz, 2017. "Towards a New Generation of Building Envelope Calibration," Energies, MDPI, vol. 10(12), pages 1-19, December.
  11. Michael D. Murphy & Paul D. O’Sullivan & Guilherme Carrilho da Graça & Adam O’Donovan, 2021. "Development, Calibration and Validation of an Internal Air Temperature Model for a Naturally Ventilated Nearly Zero Energy Building: Comparison of Model Types and Calibration Methods," Energies, MDPI, vol. 14(4), pages 1-24, February.
  12. Edwards, Richard E. & New, Joshua & Parker, Lynne E. & Cui, Borui & Dong, Jin, 2017. "Constructing large scale surrogate models from big data and artificial intelligence," Applied Energy, Elsevier, vol. 202(C), pages 685-699.
  13. Yang, Zheng & Becerik-Gerber, Burcin, 2015. "A model calibration framework for simultaneous multi-level building energy simulation," Applied Energy, Elsevier, vol. 149(C), pages 415-431.
  14. Michel Noussan & Benedetto Nastasi, 2018. "Data Analysis of Heating Systems for Buildings—A Tool for Energy Planning, Policies and Systems Simulation," Energies, MDPI, vol. 11(1), pages 1-15, January.
  15. Sol Kim & Sungwon Jung & Seung-Man Baek, 2019. "A Model for Predicting Energy Usage Pattern Types with Energy Consumption Information According to the Behaviors of Single-Person Households in South Korea," Sustainability, MDPI, vol. 11(1), pages 1-24, January.
  16. Gholami, M. & Torreggiani, D. & Tassinari, P. & Barbaresi, A., 2021. "Narrowing uncertainties in forecasting urban building energy demand through an optimal archetyping method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
  17. João Delgado & Ana Mafalda Matos & Ana Sofia Guimarães, 2022. "Linking Indoor Thermal Comfort with Climate, Energy, Housing, and Living Conditions: Portuguese Case in European Context," Energies, MDPI, vol. 15(16), pages 1-22, August.
  18. Hu, Mengqi, 2015. "A data-driven feed-forward decision framework for building clusters operation under uncertainty," Applied Energy, Elsevier, vol. 141(C), pages 229-237.
  19. Manfren, Massimiliano & Nastasi, Benedetto & Tronchin, Lamberto & Groppi, Daniele & Garcia, Davide Astiaso, 2021. "Techno-economic analysis and energy modelling as a key enablers for smart energy services and technologies in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
  20. José Sánchez Ramos & MCarmen Guerrero Delgado & Servando Álvarez Domínguez & José Luis Molina Félix & Francisco José Sánchez de la Flor & José Antonio Tenorio Ríos, 2019. "Systematic Simplified Simulation Methodology for Deep Energy Retrofitting Towards Nze Targets Using Life Cycle Energy Assessment," Energies, MDPI, vol. 12(16), pages 1-27, August.
  21. Ramos Ruiz, Germán & Fernández Bandera, Carlos, 2017. "Analysis of uncertainty indices used for building envelope calibration," Applied Energy, Elsevier, vol. 185(P1), pages 82-94.
  22. Shamsi, Mohammad Haris & Ali, Usman & Mangina, Eleni & O’Donnell, James, 2020. "A framework for uncertainty quantification in building heat demand simulations using reduced-order grey-box energy models," Applied Energy, Elsevier, vol. 275(C).
  23. Tronchin, Lamberto & Manfren, Massimiliano & James, Patrick AB., 2018. "Linking design and operation performance analysis through model calibration: Parametric assessment on a Passive House building," Energy, Elsevier, vol. 165(PA), pages 26-40.
  24. Østergård, Torben & Jensen, Rasmus Lund & Maagaard, Steffen Enersen, 2018. "A comparison of six metamodeling techniques applied to building performance simulations," Applied Energy, Elsevier, vol. 211(C), pages 89-103.
  25. Marzouk, Mohamed & Seleem, Noreihan, 2018. "Assessment of existing buildings performance using system dynamics technique," Applied Energy, Elsevier, vol. 211(C), pages 1308-1323.
  26. Pang, Zhihong & O'Neill, Zheng, 2018. "Uncertainty quantification and sensitivity analysis of the domestic hot water usage in hotels," Applied Energy, Elsevier, vol. 232(C), pages 424-442.
  27. Saryazdi, Seyed mohammad Ebrahimi & Etemad, Alireza & Shafaat, Ali & Bahman, Ammar M., 2024. "A comprehensive review and sensitivity analysis of the factors affecting the performance of buildings equipped with Variable Refrigerant Flow system in Middle East climates," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
  28. Tronchin, Lamberto & Manfren, Massimiliano & Nastasi, Benedetto, 2018. "Energy efficiency, demand side management and energy storage technologies – A critical analysis of possible paths of integration in the built environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 341-353.
  29. Brunetti, Giuseppe & Porti, Michele & Piro, Patrizia, 2018. "Multi-level numerical and statistical analysis of the hygrothermal behavior of a non-vegetated green roof in a mediterranean climate," Applied Energy, Elsevier, vol. 221(C), pages 204-219.
  30. Jeong, Cheoljoon & Byon, Eunshin, 2024. "Calibration of building energy computer models via bias-corrected iteratively reweighted least squares method," Applied Energy, Elsevier, vol. 360(C).
  31. Aste, Niccolò & Leonforte, Fabrizio & Manfren, Massimiliano & Mazzon, Manlio, 2015. "Thermal inertia and energy efficiency – Parametric simulation assessment on a calibrated case study," Applied Energy, Elsevier, vol. 145(C), pages 111-123.
  32. Kapp, Sean & Choi, Jun-Ki & Hong, Taehoon, 2023. "Predicting industrial building energy consumption with statistical and machine-learning models informed by physical system parameters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 172(C).
  33. Massimiliano Manfren & Benedetto Nastasi, 2020. "Parametric Performance Analysis and Energy Model Calibration Workflow Integration—A Scalable Approach for Buildings," Energies, MDPI, vol. 13(3), pages 1-14, February.
  34. Calama-González, Carmen María & Symonds, Phil & Petrou, Giorgos & Suárez, Rafael & León-Rodríguez, Ángel Luis, 2021. "Bayesian calibration of building energy models for uncertainty analysis through test cells monitoring," Applied Energy, Elsevier, vol. 282(PA).
  35. Yang, Tao & Pan, Yiqun & Mao, Jiachen & Wang, Yonglong & Huang, Zhizhong, 2016. "An automated optimization method for calibrating building energy simulation models with measured data: Orientation and a case study," Applied Energy, Elsevier, vol. 179(C), pages 1220-1231.
  36. Muhammad Waseem Ahmad & Anthony Mouraud & Yacine Rezgui & Monjur Mourshed, 2018. "Deep Highway Networks and Tree-Based Ensemble for Predicting Short-Term Building Energy Consumption," Energies, MDPI, vol. 11(12), pages 1-21, December.
  37. Enríquez, R. & Jiménez, M.J. & Heras, M.R., 2017. "Towards non-intrusive thermal load Monitoring of buildings: BES calibration," Applied Energy, Elsevier, vol. 191(C), pages 44-54.
  38. Nutkiewicz, Alex & Yang, Zheng & Jain, Rishee K., 2018. "Data-driven Urban Energy Simulation (DUE-S): A framework for integrating engineering simulation and machine learning methods in a multi-scale urban energy modeling workflow," Applied Energy, Elsevier, vol. 225(C), pages 1176-1189.
  39. Ji, Ying & Xu, Peng, 2015. "A bottom-up and procedural calibration method for building energy simulation models based on hourly electricity submetering data," Energy, Elsevier, vol. 93(P2), pages 2337-2350.
  40. Hsu, David, 2015. "Identifying key variables and interactions in statistical models of building energy consumption using regularization," Energy, Elsevier, vol. 83(C), pages 144-155.
  41. Young Tae Chae & Young M. Lee & David Longinott, 2016. "Assessment of Retrofitting Measures for a Large Historic Research Facility Using a Building Energy Simulation Model," Energies, MDPI, vol. 9(6), pages 1-18, June.
  42. Ramos Ruiz, Germán & Fernández Bandera, Carlos & Gómez-Acebo Temes, Tomás & Sánchez-Ostiz Gutierrez, Ana, 2016. "Genetic algorithm for building envelope calibration," Applied Energy, Elsevier, vol. 168(C), pages 691-705.
  43. O' Donovan, Adam & O' Sullivan, Paul D. & Murphy, Michael D., 2019. "Predicting air temperatures in a naturally ventilated nearly zero energy building: Calibration, validation, analysis and approaches," Applied Energy, Elsevier, vol. 250(C), pages 991-1010.
  44. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
  45. Vicente Gutiérrez González & Lissette Álvarez Colmenares & Jesús Fernando López Fidalgo & Germán Ramos Ruiz & Carlos Fernández Bandera, 2019. "Uncertainy’s Indices Assessment for Calibrated Energy Models," Energies, MDPI, vol. 12(11), pages 1-18, May.
  46. Zhang, Yixiang & Wang, Zhaohua & Zhou, Guanghui, 2013. "Determinants and implications of employee electricity saving habit: An empirical study in China," Applied Energy, Elsevier, vol. 112(C), pages 1529-1535.
  47. Wate, P. & Iglesias, M. & Coors, V. & Robinson, D., 2020. "Framework for emulation and uncertainty quantification of a stochastic building performance simulator," Applied Energy, Elsevier, vol. 258(C).
  48. Lin, Boqiang & Zhang, Guoliang, 2013. "Estimates of electricity saving potential in Chinese nonferrous metals industry," Energy Policy, Elsevier, vol. 60(C), pages 558-568.
  49. Lim, Hyunwoo & Zhai, Zhiqiang (John), 2018. "Influences of energy data on Bayesian calibration of building energy model," Applied Energy, Elsevier, vol. 231(C), pages 686-698.
  50. Chen, Jianli & Gao, Xinghua & Hu, Yuqing & Zeng, Zhaoyun & Liu, Yanan, 2019. "A meta-model-based optimization approach for fast and reliable calibration of building energy models," Energy, Elsevier, vol. 188(C).
  51. Li, Nan & Yang, Zheng & Becerik-Gerber, Burcin & Tang, Chao & Chen, Nanlin, 2015. "Why is the reliability of building simulation limited as a tool for evaluating energy conservation measures?," Applied Energy, Elsevier, vol. 159(C), pages 196-205.
  52. Robertson, Joseph J. & Polly, Ben J. & Collis, Jon M., 2015. "Reduced-order modeling and simulated annealing optimization for efficient residential building utility bill calibration," Applied Energy, Elsevier, vol. 148(C), pages 169-177.
  53. Rackes, Adams & Melo, Ana Paula & Lamberts, Roberto, 2016. "Naturally comfortable and sustainable: Informed design guidance and performance labeling for passive commercial buildings in hot climates," Applied Energy, Elsevier, vol. 174(C), pages 256-274.
  54. Yuan, Jun & Nian, Victor & Su, Bin, 2019. "Evaluation of cost-effective building retrofit strategies through soft-linking a metamodel-based Bayesian method and a life cycle cost assessment method," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
  55. Lee, P. & Lam, P.T.I. & Lee, W.L. & Chan, E.H.W., 2016. "Analysis of an air-cooled chiller replacement project using a probabilistic approach for energy performance contracts," Applied Energy, Elsevier, vol. 171(C), pages 415-428.
  56. Østergård, Torben & Jensen, Rasmus L. & Maagaard, Steffen E., 2016. "Building simulations supporting decision making in early design – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 187-201.
  57. Li, Zhengwei & Han, Yanmin & Xu, Peng, 2014. "Methods for benchmarking building energy consumption against its past or intended performance: An overview," Applied Energy, Elsevier, vol. 124(C), pages 325-334.
  58. Aste, Niccolò & Manfren, Massimiliano & Marenzi, Giorgia, 2017. "Building Automation and Control Systems and performance optimization: A framework for analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 313-330.
  59. Yuan, Jun & Nian, Victor & Su, Bin & Meng, Qun, 2017. "A simultaneous calibration and parameter ranking method for building energy models," Applied Energy, Elsevier, vol. 206(C), pages 657-666.
  60. Gencel, Osman & Danish, Aamar & Yilmaz, Mukremin & Erdogmus, Ertugrul & Sutcu, Mucahit & Sadak, Ferhat & Ozbakkaloglu, Togay, 2024. "Performance evaluation of phosphor-based luminescent bricks using different coating methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
  61. Capozzoli, Alfonso & Piscitelli, Marco Savino & Neri, Francesco & Grassi, Daniele & Serale, Gianluca, 2016. "A novel methodology for energy performance benchmarking of buildings by means of Linear Mixed Effect Model: The case of space and DHW heating of out-patient Healthcare Centres," Applied Energy, Elsevier, vol. 171(C), pages 592-607.
  62. Hou, D. & Hassan, I.G. & Wang, L., 2021. "Review on building energy model calibration by Bayesian inference," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
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