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A review on the basics of building energy estimation

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  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. Rohács, Dániel, 2023. "Analysis and optimization of potential energy sources for residential building application," Energy, Elsevier, vol. 275(C).
  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. 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).
  5. Tomasz Szul & Stanisław Kokoszka, 2020. "Application of Rough Set Theory (RST) to Forecast Energy Consumption in Buildings Undergoing Thermal Modernization," Energies, MDPI, vol. 13(6), pages 1-17, March.
  6. Gatt, Damien & Yousif, Charles & Cellura, Maurizio & Camilleri, Liberato & Guarino, Francesco, 2020. "Assessment of building energy modelling studies to meet the requirements of the new Energy Performance of Buildings Directive," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
  7. Li, Xiaoma & Zhou, Yuyu & Yu, Sha & Jia, Gensuo & Li, Huidong & Li, Wenliang, 2019. "Urban heat island impacts on building energy consumption: A review of approaches and findings," Energy, Elsevier, vol. 174(C), pages 407-419.
  8. Kyoungcheol Oh & Eui-Jong Kim & Chang-Young Park, 2022. "A Physical Model-Based Data-Driven Approach to Overcome Data Scarcity and Predict Building Energy Consumption," Sustainability, MDPI, vol. 14(15), pages 1-14, August.
  9. 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.
  10. Fu, Hongxiang & Baltazar, Juan-Carlos & Claridge, David E., 2021. "Review of developments in whole-building statistical energy consumption models for commercial buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
  11. Verbeke, Stijn & Audenaert, Amaryllis, 2018. "Thermal inertia in buildings: A review of impacts across climate and building use," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2300-2318.
  12. Ceballos-Fuentealba, Irlanda & Álvarez-Miranda, Eduardo & Torres-Fuchslocher, Carlos & del Campo-Hitschfeld, María Luisa & Díaz-Guerrero, John, 2019. "A simulation and optimisation methodology for choosing energy efficiency measures in non-residential buildings," Applied Energy, Elsevier, vol. 256(C).
  13. Solène Goy & François Maréchal & Donal Finn, 2020. "Data for Urban Scale Building Energy Modelling: Assessing Impacts and Overcoming Availability Challenges," Energies, MDPI, vol. 13(16), pages 1-23, August.
  14. Eleftheria Touloupaki & Theodoros Theodosiou, 2017. "Performance Simulation Integrated in Parametric 3D Modeling as a Method for Early Stage Design Optimization—A Review," Energies, MDPI, vol. 10(5), pages 1-18, May.
  15. 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.
  16. Zhengchao Xie & Xiao Wang & Lijun Zheng & Hao Chang & Fei Wang, 2022. "A Period-Based Neural Network Algorithm for Predicting Building Energy Consumption of District Heating," Energies, MDPI, vol. 15(17), pages 1-22, August.
  17. Langevin, J. & Reyna, J.L. & Ebrahimigharehbaghi, S. & Sandberg, N. & Fennell, P. & Nägeli, C. & Laverge, J. & Delghust, M. & Mata, É. & Van Hove, M. & Webster, J. & Federico, F. & Jakob, M. & Camaras, 2020. "Developing a common approach for classifying building stock energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
  18. Giovanni Barone & Annamaria Buonomano & Cesare Forzano & Adolfo Palombo, 2019. "Building Energy Performance Analysis: An Experimental Validation of an In-House Dynamic Simulation Tool through a Real Test Room," Energies, MDPI, vol. 12(21), pages 1-39, October.
  19. Deb, Chirag & Zhang, Fan & Yang, Junjing & Lee, Siew Eang & Shah, Kwok Wei, 2017. "A review on time series forecasting techniques for building energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 902-924.
  20. 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).
  21. Biswas, M.A. Rafe & Robinson, Melvin D. & Fumo, Nelson, 2016. "Prediction of residential building energy consumption: A neural network approach," Energy, Elsevier, vol. 117(P1), pages 84-92.
  22. Karakurt, Izzet, 2021. "Modelling and forecasting the oil consumptions of the BRICS-T countries," Energy, Elsevier, vol. 220(C).
  23. Orosz, Matthew & Altes-Buch, Queralt & Mueller, Amy & Lemort, Vincent, 2018. "Experimental validation of an electrical and thermal energy demand model for rapid assessment of rural health centers in sub-Saharan Africa," Applied Energy, Elsevier, vol. 218(C), pages 382-390.
  24. Hamid R. Khosravani & María Del Mar Castilla & Manuel Berenguel & Antonio E. Ruano & Pedro M. Ferreira, 2016. "A Comparison of Energy Consumption Prediction Models Based on Neural Networks of a Bioclimatic Building," Energies, MDPI, vol. 9(1), pages 1-24, January.
  25. Zhao, Deyin & Zhong, Ming & Zhang, Xu & Su, Xing, 2016. "Energy consumption predicting model of VRV (Variable refrigerant volume) system in office buildings based on data mining," Energy, Elsevier, vol. 102(C), pages 660-668.
  26. Berardi, Umberto & Jafarpur, Pouriya, 2020. "Assessing the impact of climate change on building heating and cooling energy demand in Canada," Renewable and Sustainable Energy Reviews, Elsevier, vol. 121(C).
  27. Wang, Chendong & Yuan, Jianjuan & Huang, Ke & Zhang, Ji & Zheng, Lihong & Zhou, Zhihua & Zhang, Yufeng, 2022. "Research on thermal load prediction of district heating station based on transfer learning," Energy, Elsevier, vol. 239(PE).
  28. Annamaria Buonomano, 2016. "Code-to-Code Validation and Application of a Dynamic Simulation Tool for the Building Energy Performance Analysis," Energies, MDPI, vol. 9(4), pages 1-29, April.
  29. 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.
  30. Tomasz Szul & Krzysztof Nęcka & Stanisław Lis, 2021. "Application of the Takagi-Sugeno Fuzzy Modeling to Forecast Energy Efficiency in Real Buildings Undergoing Thermal Improvement," Energies, MDPI, vol. 14(7), pages 1-16, March.
  31. Deepak Amaripadath & Mirjana Velickovic & Shady Attia, 2022. "Performance Evaluation of a Nearly Zero-Energy Office Building in Temperate Oceanic Climate Based on Field Measurements," Energies, MDPI, vol. 15(18), pages 1-16, September.
  32. Fumo, Nelson & Rafe Biswas, M.A., 2015. "Regression analysis for prediction of residential energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 332-343.
  33. Tiwari, Vipul Kumar & Kumar, Alok & Kumar, Arvind, 2019. "Enhancing ice slurry generation by using inclined cavity for subzero cold thermal energy storage: Simulation, experiment and performance analysis," Energy, Elsevier, vol. 183(C), pages 398-414.
  34. Ohlsson, K.E. Anders & Olofsson, Thomas, 2021. "Benchmarking the practice of validation and uncertainty analysis of building energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
  35. Amasyali, Kadir & El-Gohary, Nora M., 2018. "A review of data-driven building energy consumption prediction studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1192-1205.
  36. Rosenfelder, Markus & Wussow, Moritz & Gust, Gunther & Cremades, Roger & Neumann, Dirk, 2021. "Predicting residential electricity consumption using aerial and street view images," Applied Energy, Elsevier, vol. 301(C).
  37. 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.
  38. Muhammad Imran Khan & Dana I. Al Huneidi & Faisal Asfand & Sami G. Al-Ghamdi, 2023. "Climate Change Implications for Optimal Sizing of Residential Rooftop Solar Photovoltaic Systems in Qatar," Sustainability, MDPI, vol. 15(24), pages 1-17, December.
  39. Papineau, Maya & Yassin, Kareman & Newsham, Guy & Brice, Sarah, 2021. "Conditional demand analysis as a tool to evaluate energy policy options on the path to grid decarbonization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
  40. Deb, C. & Gelder, L.V. & Spiekman, M. & Pandraud, Guillaume & Jack, R. & Fitton, R., 2021. "Measuring the heat transfer coefficient (HTC) in buildings: A stakeholder's survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
  41. Mauricio Nath Lopes & Roberto Lamberts, 2018. "Development of a Metamodel to Predict Cooling Energy Consumption of HVAC Systems in Office Buildings in Different Climates," Sustainability, MDPI, vol. 10(12), pages 1-25, December.
  42. Shiyi Song & Hong Leng & Ran Guo, 2022. "Multi-Agent-Based Model for the Urban Macro-Level Impact Factors of Building Energy Consumption on Different Types of Land," Land, MDPI, vol. 11(11), pages 1-24, November.
  43. Chou, Jui-Sheng & Tran, Duc-Son, 2018. "Forecasting energy consumption time series using machine learning techniques based on usage patterns of residential householders," Energy, Elsevier, vol. 165(PB), pages 709-726.
  44. Venkatraj, V. & Dixit, M.K., 2022. "Challenges in implementing data-driven approaches for building life cycle energy assessment: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
  45. Tomasz Szul & Sylwester Tabor & Krzysztof Pancerz, 2021. "Application of the BORUTA Algorithm to Input Data Selection for a Model Based on Rough Set Theory (RST) to Prediction Energy Consumption for Building Heating," Energies, MDPI, vol. 14(10), pages 1-13, May.
  46. Luca Evangelisti & Claudia Guattari & Paola Gori, 2015. "Energy Retrofit Strategies for Residential Building Envelopes: An Italian Case Study of an Early-50s Building," Sustainability, MDPI, vol. 7(8), pages 1-16, August.
  47. Kwok Wai Mui & Ling Tim Wong & Manoj Kumar Satheesan & Anjana Balachandran, 2021. "A Hybrid Simulation Model to Predict the Cooling Energy Consumption for Residential Housing in Hong Kong," Energies, MDPI, vol. 14(16), pages 1-18, August.
  48. Shi, Xing & Tian, Zhichao & Chen, Wenqiang & Si, Binghui & Jin, Xing, 2016. "A review on building energy efficient design optimization rom the perspective of architects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 872-884.
  49. Niemierko, Rochus & Töppel, Jannick & Tränkler, Timm, 2019. "A D-vine copula quantile regression approach for the prediction of residential heating energy consumption based on historical data," Applied Energy, Elsevier, vol. 233, pages 691-708.
  50. Fan Yang & Qian Mao, 2023. "Auto-Evaluation Model for the Prediction of Building Energy Consumption That Combines Modified Kalman Filtering and Long Short-Term Memory," Sustainability, MDPI, vol. 15(22), pages 1-16, November.
  51. Mastrucci, Alessio & Marvuglia, Antonino & Leopold, Ulrich & Benetto, Enrico, 2017. "Life Cycle Assessment of building stocks from urban to transnational scales: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 316-332.
  52. Zhang, Liang & Wen, Jin & Li, Yanfei & Chen, Jianli & Ye, Yunyang & Fu, Yangyang & Livingood, William, 2021. "A review of machine learning in building load prediction," Applied Energy, Elsevier, vol. 285(C).
  53. Chenghao Wang & Jiyun Song & Dachuan Shi & Janet L. Reyna & Henry Horsey & Sarah Feron & Yuyu Zhou & Zutao Ouyang & Ying Li & Robert B. Jackson, 2023. "Impacts of climate change, population growth, and power sector decarbonization on urban building energy use," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
  54. Sehrish Malik & DoHyeun Kim, 2018. "Prediction-Learning Algorithm for Efficient Energy Consumption in Smart Buildings Based on Particle Regeneration and Velocity Boost in Particle Swarm Optimization Neural Networks," Energies, MDPI, vol. 11(5), pages 1-21, May.
  55. 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).
  56. Xiaoyu Lin & Hang Yu & Meng Wang & Chaoen Li & Zi Wang & Yin Tang, 2021. "Electricity Consumption Forecast of High-Rise Office Buildings Based on the Long Short-Term Memory Method," Energies, MDPI, vol. 14(16), pages 1-21, August.
  57. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
  58. Qi Dong & Kai Xing & Hongrui Zhang, 2017. "Artificial Neural Network for Assessment of Energy Consumption and Cost for Cross Laminated Timber Office Building in Severe Cold Regions," Sustainability, MDPI, vol. 10(1), pages 1-15, December.
  59. Sergio Ortega Alba & Mario Manana, 2017. "Characterization and Analysis of Energy Demand Patterns in Airports," Energies, MDPI, vol. 10(1), pages 1-35, January.
  60. Chalal, Moulay Larbi & Benachir, Medjdoub & White, Michael & Shrahily, Raid, 2016. "Energy planning and forecasting approaches for supporting physical improvement strategies in the building sector: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 761-776.
  61. Shakouri G., Hamed, 2019. "The share of cooling electricity in global warming: Estimation of the loop gain for the positive feedback," Energy, Elsevier, vol. 179(C), pages 747-761.
  62. Scarpa, Federico & Tagliafico, Luca A. & Bianco, Vincenzo, 2021. "Financial and energy performance analysis of efficiency measures in residential buildings. A probabilistic approach," Energy, Elsevier, vol. 236(C).
  63. Wang, Chendong & Yuan, Jianjuan & Zhang, Ji & Deng, Na & Zhou, Zhihua & Gao, Feng, 2020. "Multi-criteria comprehensive study on predictive algorithm of heating energy consumption of district heating station based on timeseries processing," Energy, Elsevier, vol. 202(C).
  64. Li, Guannan & Hu, Yunpeng & Chen, Huanxin & Li, Haorong & Hu, Min & Guo, Yabin & Liu, Jiangyan & Sun, Shaobo & Sun, Miao, 2017. "Data partitioning and association mining for identifying VRF energy consumption patterns under various part loads and refrigerant charge conditions," Applied Energy, Elsevier, vol. 185(P1), pages 846-861.
  65. Adam Kula & Albert Smalcerz & Maciej Sajkowski & Zygmunt Kamiński, 2021. "Analysis of Office Rooms Energy Consumption Data in Respect to Meteorological and Direct Sun Exposure Conditions," Energies, MDPI, vol. 14(22), pages 1-20, November.
  66. Joanna Piotrowska-Woroniak & Tomasz Szul, 2022. "Application of a Model Based on Rough Set Theory (RST) to Estimate the Energy Efficiency of Public Buildings," Energies, MDPI, vol. 15(23), pages 1-13, November.
  67. Verhaeghe, C. & Verbeke, S. & Audenaert, A., 2021. "A consistent taxonomic framework: towards common understanding of high energy performance building definitions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
  68. Bedi, Jatin & Toshniwal, Durga, 2019. "Deep learning framework to forecast electricity demand," Applied Energy, Elsevier, vol. 238(C), pages 1312-1326.
  69. Chou, Jui-Sheng & Ngo, Ngoc-Tri, 2016. "Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns," Applied Energy, Elsevier, vol. 177(C), pages 751-770.
  70. Xiao, Tong & Xu, Peng & He, Ruikai & Sha, Huajing, 2022. "Status quo and opportunities for building energy prediction in limited data Context—Overview from a competition," Applied Energy, Elsevier, vol. 305(C).
  71. Amin Nouri & Christoph van Treeck & Jérôme Frisch, 2024. "Sensitivity Assessment of Building Energy Performance Simulations Using MARS Meta-Modeling in Combination with Sobol’ Method," Energies, MDPI, vol. 17(3), pages 1-24, January.
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  73. Triebs, Merlin Sebastian & Tsatsaronis, George, 2022. "From heat demand to heat supply: How to obtain more accurate feed-in time series for district heating systems," Applied Energy, Elsevier, vol. 311(C).
  74. Faustino Patiño-Cambeiro & Guillermo Bastos & Julia Armesto & Faustino Patiño-Barbeito, 2017. "Multidisciplinary Energy Assessment of Tertiary Buildings: Automated Geomatic Inspection, Building Information Modeling Reconstruction and Building Performance Simulation," Energies, MDPI, vol. 10(7), pages 1-17, July.
  75. Waite, Michael & Cohen, Elliot & Torbey, Henri & Piccirilli, Michael & Tian, Yu & Modi, Vijay, 2017. "Global trends in urban electricity demands for cooling and heating," Energy, Elsevier, vol. 127(C), pages 786-802.
  76. van der Meer, D.W. & Widén, J. & Munkhammar, J., 2018. "Review on probabilistic forecasting of photovoltaic power production and electricity consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1484-1512.
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