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A review of data-driven building energy consumption prediction studies

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Cited by:

  1. Rohács, Dániel, 2023. "Analysis and optimization of potential energy sources for residential building application," Energy, Elsevier, vol. 275(C).
  2. Cao, Wenqiang & Yu, Junqi & Chao, Mengyao & Wang, Jingqi & Yang, Siyuan & Zhou, Meng & Wang, Meng, 2023. "Short-term energy consumption prediction method for educational buildings based on model integration," Energy, Elsevier, vol. 283(C).
  3. 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).
  4. Jinrong Wu & Su Nguyen & Damminda Alahakoon & Daswin De Silva & Nishan Mills & Prabod Rathnayaka & Harsha Moraliyage & Andrew Jennings, 2024. "A Comparative Analysis of Machine Learning-Based Energy Baseline Models across Multiple Building Types," Energies, MDPI, vol. 17(6), pages 1-18, March.
  5. Huang, Yaohui & Zhao, Yuan & Wang, Zhijin & Liu, Xiufeng & Liu, Hanjing & Fu, Yonggang, 2023. "Explainable district heat load forecasting with active deep learning," Applied Energy, Elsevier, vol. 350(C).
  6. Mohammad Mahdi Forootan & Iman Larki & Rahim Zahedi & Abolfazl Ahmadi, 2022. "Machine Learning and Deep Learning in Energy Systems: A Review," Sustainability, MDPI, vol. 14(8), pages 1-49, April.
  7. Wang, Zhe & Hong, Tianzhen & Piette, Mary Ann, 2020. "Building thermal load prediction through shallow machine learning and deep learning," Applied Energy, Elsevier, vol. 263(C).
  8. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A novel improved model for building energy consumption prediction based on model integration," Applied Energy, Elsevier, vol. 262(C).
  9. Muideen Adegoke & Alaka Hafiz & Saheed Ajayi & Razak Olu-Ajayi, 2022. "Application of Multilayer Extreme Learning Machine for Efficient Building Energy Prediction," Energies, MDPI, vol. 15(24), pages 1-21, December.
  10. Guo, Jing & Lin, Penghui & Zhang, Limao & Pan, Yue & Xiao, Zhonghua, 2023. "Dynamic adaptive encoder-decoder deep learning networks for multivariate time series forecasting of building energy consumption," Applied Energy, Elsevier, vol. 350(C).
  11. Gökhan Demirdöğen & Zeynep Işık & Yusuf Arayici, 2020. "Lean Management Framework for Healthcare Facilities Integrating BIM, BEPS and Big Data Analytics," Sustainability, MDPI, vol. 12(17), pages 1-33, August.
  12. Vangelis Marinakis, 2020. "Big Data for Energy Management and Energy-Efficient Buildings," Energies, MDPI, vol. 13(7), pages 1-18, March.
  13. Zhang, Yan & Teoh, Bak Koon & Wu, Maozhi & Chen, Jiayu & Zhang, Limao, 2023. "Data-driven estimation of building energy consumption and GHG emissions using explainable artificial intelligence," Energy, Elsevier, vol. 262(PA).
  14. Tang, Lingfeng & Xie, Haipeng & Wang, Xiaoyang & Bie, Zhaohong, 2023. "Privacy-preserving knowledge sharing for few-shot building energy prediction: A federated learning approach," Applied Energy, Elsevier, vol. 337(C).
  15. 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.
  16. Gao, Zhikun & Yang, Siyuan & Yu, Junqi & Zhao, Anjun, 2024. "Hybrid forecasting model of building cooling load based on combined neural network," Energy, Elsevier, vol. 297(C).
  17. Satre-Meloy, Aven, 2019. "Investigating structural and occupant drivers of annual residential electricity consumption using regularization in regression models," Energy, Elsevier, vol. 174(C), pages 148-168.
  18. Lu, Chujie & Li, Sihui & Reddy Penaka, Santhan & Olofsson, Thomas, 2023. "Automated machine learning-based framework of heating and cooling load prediction for quick residential building design," Energy, Elsevier, vol. 274(C).
  19. Ding, Zhikun & Chen, Weilin & Hu, Ting & Xu, Xiaoxiao, 2021. "Evolutionary double attention-based long short-term memory model for building energy prediction: Case study of a green building," Applied Energy, Elsevier, vol. 288(C).
  20. Sarabia Escriva, Emilio José & Hart, Matthew & Acha, Salvador & Soto Francés, Víctor & Shah, Nilay & Markides, Christos N., 2022. "Techno-economic evaluation of integrated energy systems for heat recovery applications in food retail buildings," Applied Energy, Elsevier, vol. 305(C).
  21. Yan, Biao & Yang, Wansheng & He, Fuquan & Zeng, Wenhao, 2023. "Occupant behavior impact in buildings and the artificial intelligence-based techniques and data-driven approach solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
  22. Chun-Wei Chen, 2023. "A Feasibility Discussion: Is ML Suitable for Predicting Sustainable Patterns in Consumer Product Preferences?," Sustainability, MDPI, vol. 15(5), pages 1-21, February.
  23. Maatouk Khoukhi & Abeer Fuad Darsaleh & Sara Ali, 2020. "Retrofitting an Existing Office Building in the UAE Towards Achieving Low-Energy Building," Sustainability, MDPI, vol. 12(6), pages 1-16, March.
  24. James Ogundiran & Ehsan Asadi & Manuel Gameiro da Silva, 2024. "A Systematic Review on the Use of AI for Energy Efficiency and Indoor Environmental Quality in Buildings," Sustainability, MDPI, vol. 16(9), pages 1-30, April.
  25. Ganapathy Ramesh & Jaganathan Logeshwaran & Thangavel Kiruthiga & Jaime Lloret, 2023. "Prediction of Energy Production Level in Large PV Plants through AUTO-Encoder Based Neural-Network (AUTO-NN) with Restricted Boltzmann Feature Extraction," Future Internet, MDPI, vol. 15(2), pages 1-20, January.
  26. Seyed Morteza Moghimi & Thomas Aaron Gulliver & Ilamparithi Thirumai Chelvan, 2024. "Energy Management in Modern Buildings Based on Demand Prediction and Machine Learning—A Review," Energies, MDPI, vol. 17(3), pages 1-20, January.
  27. Mohsen Sharifi & Amin Kouti & Evi Lambie & Yixiao Ma & Maria Fernandez Boneta & Mohammad Haris Shamsi, 2023. "A Comprehensive Framework for Data-Driven Building End-Use Assessment Utilizing Monitored Operational Parameters," Energies, MDPI, vol. 16(20), pages 1-23, October.
  28. Yue, Naihua & Caini, Mauro & Li, Lingling & Zhao, Yang & Li, Yu, 2023. "A comparison of six metamodeling techniques applied to multi building performance vectors prediction on gymnasiums under multiple climate conditions," Applied Energy, Elsevier, vol. 332(C).
  29. Tuukka Salmi & Jussi Kiljander & Daniel Pakkala, 2020. "Stacked Boosters Network Architecture for Short-Term Load Forecasting in Buildings," Energies, MDPI, vol. 13(9), pages 1-15, May.
  30. Koschwitz, D. & Frisch, J. & van Treeck, C., 2018. "Data-driven heating and cooling load predictions for non-residential buildings based on support vector machine regression and NARX Recurrent Neural Network: A comparative study on district scale," Energy, Elsevier, vol. 165(PA), pages 134-142.
  31. Liang, Xinbin & Liu, Zhuoxuan & Wang, Jie & Jin, Xinqiao & Du, Zhimin, 2023. "Uncertainty quantification-based robust deep learning for building energy systems considering distribution shift problem," Applied Energy, Elsevier, vol. 337(C).
  32. Kang, Hyuna & An, Jongbaek & Kim, Hakpyeong & Ji, Changyoon & Hong, Taehoon & Lee, Seunghye, 2021. "Changes in energy consumption according to building use type under COVID-19 pandemic in South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
  33. Zhang, Chengyu & Ma, Liangdong & Luo, Zhiwen & Han, Xing & Zhao, Tianyi, 2024. "Forecasting building plug load electricity consumption employing occupant-building interaction input features and bidirectional LSTM with improved swarm intelligent algorithms," Energy, Elsevier, vol. 288(C).
  34. Ihab Taleb & Guillaume Guerard & Frédéric Fauberteau & Nga Nguyen, 2022. "A Flexible Deep Learning Method for Energy Forecasting," Energies, MDPI, vol. 15(11), pages 1-16, May.
  35. Altieri, Domenico & Patel, Martin K. & Lazarus, Joël & Branca, Giovanni, 2023. "Numerical analysis of low-cost optimization measures for improving energy efficiency in residential buildings," Energy, Elsevier, vol. 273(C).
  36. Fan, Cheng & Sun, Yongjun & Zhao, Yang & Song, Mengjie & Wang, Jiayuan, 2019. "Deep learning-based feature engineering methods for improved building energy prediction," Applied Energy, Elsevier, vol. 240(C), pages 35-45.
  37. 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).
  38. Zhang, Chengyu & Luo, Zhiwen & Rezgui, Yacine & Zhao, Tianyi, 2024. "Enhancing building energy consumption prediction introducing novel occupant behavior models with sparrow search optimization and attention mechanisms: A case study for forty-five buildings in a univer," Energy, Elsevier, vol. 294(C).
  39. Kazimierz Kawa & Rafał Mularczyk & Waldemar Bauer & Katarzyna Grobler-Dębska & Edyta Kucharska, 2024. "Prediction of Energy Consumption on Example of Heterogenic Commercial Buildings," Energies, MDPI, vol. 17(13), pages 1-16, June.
  40. García Kerdan, Iván & Morillón Gálvez, David, 2020. "Artificial neural network structure optimisation for accurately prediction of exergy, comfort and life cycle cost performance of a low energy building," Applied Energy, Elsevier, vol. 280(C).
  41. Gao, Zhikun & Yu, Junqi & Zhao, Anjun & Hu, Qun & Yang, Siyuan, 2022. "A hybrid method of cooling load forecasting for large commercial building based on extreme learning machine," Energy, Elsevier, vol. 238(PC).
  42. Amasyali, Kadir & El-Gohary, Nora M., 2021. "Real data-driven occupant-behavior optimization for reduced energy consumption and improved comfort," Applied Energy, Elsevier, vol. 302(C).
  43. Cui, Borui & Fan, Cheng & Munk, Jeffrey & Mao, Ning & Xiao, Fu & Dong, Jin & Kuruganti, Teja, 2019. "A hybrid building thermal modeling approach for predicting temperatures in typical, detached, two-story houses," Applied Energy, Elsevier, vol. 236(C), pages 101-116.
  44. Zhaocheng Li & Yu Song, 2022. "Energy Consumption Linkages of the Chinese Construction Sector," Energies, MDPI, vol. 15(5), pages 1-13, February.
  45. Abhinandana Boodi & Karim Beddiar & Malek Benamour & Yassine Amirat & Mohamed Benbouzid, 2018. "Intelligent Systems for Building Energy and Occupant Comfort Optimization: A State of the Art Review and Recommendations," Energies, MDPI, vol. 11(10), pages 1-26, September.
  46. Qin, Meng & Hu, Wei & Qi, Xinzhou & Chang, Tsangyao, 2024. "Do the benefits outweigh the disadvantages? Exploring the role of artificial intelligence in renewable energy," Energy Economics, Elsevier, vol. 131(C).
  47. Sunil Kumar Mohapatra & Sushruta Mishra & Hrudaya Kumar Tripathy & Akash Kumar Bhoi & Paolo Barsocchi, 2021. "A Pragmatic Investigation of Energy Consumption and Utilization Models in the Urban Sector Using Predictive Intelligence Approaches," Energies, MDPI, vol. 14(13), pages 1-28, June.
  48. Cao, Jingyu & Zheng, Ling & Peng, Jinqing & Wang, Wenjie & Leung, Michael K.H. & Zheng, Zhanying & Hu, Mingke & Wang, Qiliang & Cai, Jingyong & Pei, Gang & Ji, Jie, 2023. "Advances in coupled use of renewable energy sources for performance enhancement of vapour compression heat pump: A systematic review of applications to buildings," Applied Energy, Elsevier, vol. 332(C).
  49. Fredrik Skaug Fadnes & Reyhaneh Banihabib & Mohsen Assadi, 2023. "Using Artificial Neural Networks to Gather Intelligence on a Fully Operational Heat Pump System in an Existing Building Cluster," Energies, MDPI, vol. 16(9), pages 1-33, May.
  50. Muhammad Aslam Jarwar & Sajjad Ali & Ilyoung Chong, 2019. "Microservices Model to Enhance the Availability of Data for Buildings Energy Efficiency Management Services," Energies, MDPI, vol. 12(3), pages 1-27, January.
  51. 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.
  52. Akhtari, Mohammad Reza & Shayegh, Iman & Karimi, Nader, 2020. "Techno-economic assessment and optimization of a hybrid renewable earth - air heat exchanger coupled with electric boiler, hydrogen, wind and PV configurations," Renewable Energy, Elsevier, vol. 148(C), pages 839-851.
  53. Zhong, Hai & Wang, Jiajun & Jia, Hongjie & Mu, Yunfei & Lv, Shilei, 2019. "Vector field-based support vector regression for building energy consumption prediction," Applied Energy, Elsevier, vol. 242(C), pages 403-414.
  54. Jason Runge & Radu Zmeureanu, 2021. "A Review of Deep Learning Techniques for Forecasting Energy Use in Buildings," Energies, MDPI, vol. 14(3), pages 1-26, January.
  55. Ahmad, Tanveer & Chen, Huanxin, 2018. "Potential of three variant machine-learning models for forecasting district level medium-term and long-term energy demand in smart grid environment," Energy, Elsevier, vol. 160(C), pages 1008-1020.
  56. Sun, Ying & Haghighat, Fariborz & Fung, Benjamin C.M., 2022. "Trade-off between accuracy and fairness of data-driven building and indoor environment models: A comparative study of pre-processing methods," Energy, Elsevier, vol. 239(PD).
  57. Zhang, Xiang & Rasmussen, Christoffer & Saelens, Dirk & Roels, Staf, 2022. "Time-dependent solar aperture estimation of a building: Comparing grey-box and white-box approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
  58. Sahraei, Mohammad Ali & Duman, Hakan & Çodur, Muhammed Yasin & Eyduran, Ecevit, 2021. "Prediction of transportation energy demand: Multivariate Adaptive Regression Splines," Energy, Elsevier, vol. 224(C).
  59. 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).
  60. 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).
  61. 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.
  62. Ahmed Abdelaziz & Vitor Santos & Miguel Sales Dias, 2021. "Machine Learning Techniques in the Energy Consumption of Buildings: A Systematic Literature Review Using Text Mining and Bibliometric Analysis," Energies, MDPI, vol. 14(22), pages 1-31, November.
  63. Weinand, Jann Michael & Scheller, Fabian & McKenna, Russell, 2020. "Reviewing energy system modelling of decentralized energy autonomy," Energy, Elsevier, vol. 203(C).
  64. Aiman Mohammed & Muhammad Atiq Ur Rehman Tariq & Anne Wai Man Ng & Zeeshan Zaheer & Safwan Sadeq & Mahmood Mohammed & Hooman Mehdizadeh-Rad, 2022. "Reducing the Cooling Loads of Buildings Using Shading Devices: A Case Study in Darwin," Sustainability, MDPI, vol. 14(7), pages 1-20, March.
  65. 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.
  66. Grillone, Benedetto & Danov, Stoyan & Sumper, Andreas & Cipriano, Jordi & Mor, Gerard, 2020. "A review of deterministic and data-driven methods to quantify energy efficiency savings and to predict retrofitting scenarios in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
  67. Kamel, Ehsan & Sheikh, Shaya & Huang, Xueqing, 2020. "Data-driven predictive models for residential building energy use based on the segregation of heating and cooling days," Energy, Elsevier, vol. 206(C).
  68. Gautham Krishnadas & Aristides Kiprakis, 2020. "A Machine Learning Pipeline for Demand Response Capacity Scheduling," Energies, MDPI, vol. 13(7), pages 1-25, April.
  69. Wang, Zeyu & Liu, Jian & Zhang, Yuanxin & Yuan, Hongping & Zhang, Ruixue & Srinivasan, Ravi S., 2021. "Practical issues in implementing machine-learning models for building energy efficiency: Moving beyond obstacles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
  70. Mohammad Navid Fekri & Ananda Mohon Ghosh & Katarina Grolinger, 2019. "Generating Energy Data for Machine Learning with Recurrent Generative Adversarial Networks," Energies, MDPI, vol. 13(1), pages 1-23, December.
  71. Joanna Henzel & Łukasz Wróbel & Marcin Fice & Marek Sikora, 2022. "Energy Consumption Forecasting for the Digital-Twin Model of the Building," Energies, MDPI, vol. 15(12), pages 1-21, June.
  72. Hai Tao & Isa Ebtehaj & Hossein Bonakdari & Salim Heddam & Cyril Voyant & Nadhir Al-Ansari & Ravinesh Deo & Zaher Mundher Yaseen, 2019. "Designing a New Data Intelligence Model for Global Solar Radiation Prediction: Application of Multivariate Modeling Scheme," Energies, MDPI, vol. 12(7), pages 1-24, April.
  73. Wang, Xiaolu & Tan, Yumin & Zhou, Guanhua & Jing, Guifei & John Francis, Emolu, 2024. "A framework for analyzing energy consumption in urban built-up areas based on single photonic radar and spatial big data," Energy, Elsevier, vol. 290(C).
  74. Simon Wenninger & Christian Wiethe, 2021. "Benchmarking Energy Quantification Methods to Predict Heating Energy Performance of Residential Buildings in Germany," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(3), pages 223-242, June.
  75. Abdulrahman Alanezi & Kevin P. Hallinan & Rodwan Elhashmi, 2021. "Using Smart-WiFi Thermostat Data to Improve Prediction of Residential Energy Consumption and Estimation of Savings," Energies, MDPI, vol. 14(1), pages 1-16, January.
  76. Chen, Yibo & Zhang, Fengyi & Berardi, Umberto, 2020. "Day-ahead prediction of hourly subentry energy consumption in the building sector using pattern recognition algorithms," Energy, Elsevier, vol. 211(C).
  77. Lukas Lundström & Jan Akander & Jesús Zambrano, 2019. "Development of a Space Heating Model Suitable for the Automated Model Generation of Existing Multifamily Buildings—A Case Study in Nordic Climate," Energies, MDPI, vol. 12(3), pages 1-27, February.
  78. Nikolaos Kampelis & Georgios I. Papayiannis & Dionysia Kolokotsa & Georgios N. Galanis & Daniela Isidori & Cristina Cristalli & Athanasios N. Yannacopoulos, 2020. "An Integrated Energy Simulation Model for Buildings," Energies, MDPI, vol. 13(5), pages 1-23, March.
  79. Li, Xinyi & Yao, Runming, 2020. "A machine-learning-based approach to predict residential annual space heating and cooling loads considering occupant behaviour," Energy, Elsevier, vol. 212(C).
  80. Yang, Tianrun & Liu, Wen & Kramer, Gert Jan & Sun, Qie, 2021. "Seasonal thermal energy storage: A techno-economic literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
  81. Yan, Xiuying & Ji, Xingxing & Meng, Qinglong & Sun, Hang & Lei, Yu, 2024. "A hybrid prediction model of improved bidirectional long short-term memory network for cooling load based on PCANet and attention mechanism," Energy, Elsevier, vol. 292(C).
  82. Chen, Xia & Geyer, Philipp, 2022. "Machine assistance in energy-efficient building design: A predictive framework toward dynamic interaction with human decision-making under uncertainty," Applied Energy, Elsevier, vol. 307(C).
  83. Jacob Hale & Suzanna Long, 2020. "A Time Series Sustainability Assessment of a Partial Energy Portfolio Transition," Energies, MDPI, vol. 14(1), pages 1-14, December.
  84. Lara Ramadan & Isam Shahrour & Hussein Mroueh & Fadi Hage Chehade, 2021. "Use of Machine Learning Methods for Indoor Temperature Forecasting," Future Internet, MDPI, vol. 13(10), pages 1-18, September.
  85. Hang Thi Thanh Vu & Jeonghan Ko, 2024. "Effective Modeling of CO 2 Emissions for Light-Duty Vehicles: Linear and Non-Linear Models with Feature Selection," Energies, MDPI, vol. 17(7), pages 1-23, March.
  86. Lotta Kannari & Jussi Kiljander & Kalevi Piira & Jouko Piippo & Pekka Koponen, 2021. "Building Heat Demand Forecasting by Training a Common Machine Learning Model with Physics-Based Simulator," Forecasting, MDPI, vol. 3(2), pages 1-13, April.
  87. Nouri, Narjes & Balali, Farhad & Nasiri, Adel & Seifoddini, Hamid & Otieno, Wilkistar, 2019. "Water withdrawal and consumption reduction for electrical energy generation systems," Applied Energy, Elsevier, vol. 248(C), pages 196-206.
  88. Joaquín Garrido-Zafra & Antonio Moreno-Munoz & Aurora Gil-de-Castro & Emilio J. Palacios-Garcia & Carlos D. Moreno-Moreno & Tomás Morales-Leal, 2019. "A Novel Direct Load Control Testbed for Smart Appliances," Energies, MDPI, vol. 12(17), pages 1-16, August.
  89. Jiang, Ben & Li, Yu & Rezgui, Yacine & Zhang, Chengyu & Wang, Peng & Zhao, Tianyi, 2024. "Multi-source domain generalization deep neural network model for predicting energy consumption in multiple office buildings," Energy, Elsevier, vol. 299(C).
  90. 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.
  91. Amna Shibeika & Maatouk Khoukhi & Omar Al Khatib & Nouf Alzahmi & Shamma Tahnoon & Maryam Al Dhahri & Nouf Alshamsi, 2021. "Integrated Design Process for High-Performance Buildings; a Case Study from Dubai," Sustainability, MDPI, vol. 13(15), pages 1-18, July.
  92. Behrad Bezyan & Radu Zmeureanu, 2020. "Machine Learning for Benchmarking Models of Heating Energy Demand of Houses in Northern Canada," Energies, MDPI, vol. 13(5), pages 1-20, March.
  93. Michel Noussan & Roberta Roberto & Benedetto Nastasi, 2018. "Performance Indicators of Electricity Generation at Country Level—The Case of Italy," Energies, MDPI, vol. 11(3), pages 1-14, March.
  94. Sesil Koutra & Christos S. Ioakimidis, 2022. "Unveiling the Potential of Machine Learning Applications in Urban Planning Challenges," Land, MDPI, vol. 12(1), pages 1-19, December.
  95. Md Mijanur Rahman & Mohammad Shakeri & Sieh Kiong Tiong & Fatema Khatun & Nowshad Amin & Jagadeesh Pasupuleti & Mohammad Kamrul Hasan, 2021. "Prospective Methodologies in Hybrid Renewable Energy Systems for Energy Prediction Using Artificial Neural Networks," Sustainability, MDPI, vol. 13(4), pages 1-28, February.
  96. 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.
  97. Ahlrichs, Jakob & Rockstuhl, Sebastian & Tränkler, Timm & Wenninger, Simon, 2020. "The impact of political instruments on building energy retrofits: A risk-integrated thermal Energy Hub approach," Energy Policy, Elsevier, vol. 147(C).
  98. Chen, Siliang & Ge, Wei & Liang, Xinbin & Jin, Xinqiao & Du, Zhimin, 2024. "Lifelong learning with deep conditional generative replay for dynamic and adaptive modeling towards net zero emissions target in building energy system," Applied Energy, Elsevier, vol. 353(PB).
  99. 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).
  100. Fan, Cheng & Xiao, Fu & Song, Mengjie & Wang, Jiayuan, 2019. "A graph mining-based methodology for discovering and visualizing high-level knowledge for building energy management," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
  101. Sang-Woo Ha & Seung-Hoon Park & Jae-Yong Eom & Min-Suk Oh & Ga-Young Cho & Eui-Jong Kim, 2020. "Parameter Calibration for a TRNSYS BIPV Model Using In Situ Test Data," Energies, MDPI, vol. 13(18), pages 1-15, September.
  102. Serik Tokbolat & Farnush Nazipov & Jong R. Kim & Ferhat Karaca, 2019. "Evaluation of the Environmental Performance of Residential Building Envelope Components," Energies, MDPI, vol. 13(1), pages 1-10, December.
  103. Salvatore Favuzza & Mariano Giuseppe Ippolito & Fabio Massaro & Rossano Musca & Eleonora Riva Sanseverino & Giuseppe Schillaci & Gaetano Zizzo, 2018. "Building Automation and Control Systems and Electrical Distribution Grids: A Study on the Effects of Loads Control Logics on Power Losses and Peaks," Energies, MDPI, vol. 11(3), pages 1-15, March.
  104. Fu, Chun & Miller, Clayton, 2022. "Using Google Trends as a proxy for occupant behavior to predict building energy consumption," Applied Energy, Elsevier, vol. 310(C).
  105. Hazar, Hanbey & Tekdogan, Remziye & Sevinc, Huseyin, 2021. "Determination of the effects of oxygen-enriched air with the help of zeolites on the exhaust emission and performance of a diesel engine," Energy, Elsevier, vol. 236(C).
  106. Somu, Nivethitha & M R, Gauthama Raman & Ramamritham, Krithi, 2020. "A hybrid model for building energy consumption forecasting using long short term memory networks," Applied Energy, Elsevier, vol. 261(C).
  107. Deb, Chirag & Dai, Zhonghao & Schlueter, Arno, 2021. "A machine learning-based framework for cost-optimal building retrofit," Applied Energy, Elsevier, vol. 294(C).
  108. Ali, Usman & Shamsi, Mohammad Haris & Bohacek, Mark & Hoare, Cathal & Purcell, Karl & Mangina, Eleni & O’Donnell, James, 2020. "A data-driven approach to optimize urban scale energy retrofit decisions for residential buildings," Applied Energy, Elsevier, vol. 267(C).
  109. Pan, Yue & Zhang, Limao, 2020. "Data-driven estimation of building energy consumption with multi-source heterogeneous data," Applied Energy, Elsevier, vol. 268(C).
  110. Tien, Paige Wenbin & Wei, Shuangyu & Calautit, John Kaiser & Darkwa, Jo & Wood, Christopher, 2022. "Real-time monitoring of occupancy activities and window opening within buildings using an integrated deep learning-based approach for reducing energy demand," Applied Energy, Elsevier, vol. 308(C).
  111. Maltais, Louis-Gabriel & Gosselin, Louis, 2022. "Forecasting of short-term lighting and plug load electricity consumption in single residential units: Development and assessment of data-driven models for different horizons," Applied Energy, Elsevier, vol. 307(C).
  112. Guanjing Lin & Hannah Kramer & Valerie Nibler & Eliot Crowe & Jessica Granderson, 2022. "Building Analytics Tool Deployment at Scale: Benefits, Costs, and Deployment Practices," Energies, MDPI, vol. 15(13), pages 1-17, July.
  113. Xing, Zhuoqun & Pan, Yiqun & Yang, Yiting & Yuan, Xiaolei & Liang, Yumin & Huang, Zhizhong, 2024. "Transfer learning integrating similarity analysis for short-term and long-term building energy consumption prediction," Applied Energy, Elsevier, vol. 365(C).
  114. Amasyali, Kadir & El-Gohary, Nora, 2021. "Machine learning for occupant-behavior-sensitive cooling energy consumption prediction in office buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
  115. Angelina D. Bintoudi & Lampros Zyglakis & Apostolos C. Tsolakis & Paschalis A. Gkaidatzis & Athanasios Tryferidis & Dimosthenis Ioannidis & Dimitrios Tzovaras, 2021. "OptiMEMS: An Adaptive Lightweight Optimal Microgrid Energy Management System Based on the Novel Virtual Distributed Energy Resources in Real-Life Demonstration," Energies, MDPI, vol. 14(10), pages 1-19, May.
  116. Zhang, Yan & Teoh, Bak Koon & Zhang, Limao, 2023. "Exploring driving force factors of building energy use and GHG emission using a spatio-temporal regression method," Energy, Elsevier, vol. 269(C).
  117. Ekmekci, Ece & Ozturk, Z. Fatih & Sisman, Altug, 2023. "Collective behavior of boreholes and its optimization to maximize BTES performance," Applied Energy, Elsevier, vol. 343(C).
  118. Toroghi, Shahaboddin H. & Oliver, Matthew E., 2019. "Framework for estimation of the direct rebound effect for residential photovoltaic systems," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
  119. Fan, Cheng & Xiao, Fu & Yan, Chengchu & Liu, Chengliang & Li, Zhengdao & Wang, Jiayuan, 2019. "A novel methodology to explain and evaluate data-driven building energy performance models based on interpretable machine learning," Applied Energy, Elsevier, vol. 235(C), pages 1551-1560.
  120. Lei Jiang & Weiqing Liu & Haiping Liao & Jiabao Li, 2020. "Investigation of the Geometric Shape Effect on the Solar Energy Potential of Gymnasium Buildings," Energies, MDPI, vol. 13(23), pages 1-21, December.
  121. Wang, Wei & Hong, Tianzhen & Xu, Xiaodong & Chen, Jiayu & Liu, Ziang & Xu, Ning, 2019. "Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm," Applied Energy, Elsevier, vol. 248(C), pages 217-230.
  122. Sihan Zhou & Lijie Zhu & Runan Wan & Tao Zhang & Yongzheng Zhang & Yi Zhan & Fang Wang & Linfeng Zhang & Tian You, 2023. "An Overview of Sandbox Experiment on Ground Heat Exchangers," Sustainability, MDPI, vol. 15(14), pages 1-39, July.
  123. Lei, Lei & Shao, Suola & Liang, Lixia, 2024. "An evolutionary deep learning model based on EWKM, random forest algorithm, SSA and BiLSTM for building energy consumption prediction," Energy, Elsevier, vol. 288(C).
  124. Song, Zhaofang & Shi, Jing & Li, Shujian & Chen, Zexu & Jiao, Fengshun & Yang, Wangwang & Zhang, Zitong, 2022. "Data-driven and physical model-based evaluation method for the achievable demand response potential of residential consumers' air conditioning loads," Applied Energy, Elsevier, vol. 307(C).
  125. Zhou, Xinlei & Lin, Wenye & Kumar, Ritunesh & Cui, Ping & Ma, Zhenjun, 2022. "A data-driven strategy using long short term memory models and reinforcement learning to predict building electricity consumption," Applied Energy, Elsevier, vol. 306(PB).
  126. Hasim Altan & Bertug Ozarisoy, 2022. "An Analysis of the Development of Modular Building Design Elements to Improve Thermal Performance of a Representative High Rise Residential Estate in the Coastline City of Famagusta, Cyprus," Sustainability, MDPI, vol. 14(7), pages 1-50, March.
  127. Qian, Yu & Ji, Jie & Xie, Hao & Jia, Hengmin & Tang, Yayun & Mu, Yan, 2024. "Performance prediction of a novel disinfection-enhanced type Trombe wall with transverse fins," Energy, Elsevier, vol. 302(C).
  128. Mark Kipngetich Kiptoo & Oludamilare Bode Adewuyi & Mohammed Elsayed Lotfy & Theophilus Amara & Keifa Vamba Konneh & Tomonobu Senjyu, 2019. "Assessing the Techno-Economic Benefits of Flexible Demand Resources Scheduling for Renewable Energy–Based Smart Microgrid Planning," Future Internet, MDPI, vol. 11(10), pages 1-16, October.
  129. Gleydson de Oliveira Cavalcanti & Handson Claudio Dias Pimenta, 2023. "Electric Energy Management in Buildings Based on the Internet of Things: A Systematic Review," Energies, MDPI, vol. 16(15), pages 1-29, August.
  130. Tian, Shen & Shao, Shuangquan & Liu, Bin, 2019. "Investigation on transient energy consumption of cold storages: Modeling and a case study," Energy, Elsevier, vol. 180(C), pages 1-9.
  131. Yuwen You & Zhonghua Wang & Zhihao Liu & Chunmei Guo & Bin Yang, 2024. "Load Prediction of Regional Heat Exchange Station Based on Fuzzy Clustering Based on Fourier Distance and Convolutional Neural Network–Bidirectional Long Short-Term Memory Network," Energies, MDPI, vol. 17(16), pages 1-19, August.
  132. dos Santos Ferreira, Greicili & Martins dos Santos, Deilson & Luciano Avila, Sérgio & Viana Luiz Albani, Vinicius & Cardoso Orsi, Gustavo & Cesar Cordeiro Vieira, Pedro & Nilson Rodrigues, Rafael, 2023. "Short- and long-term forecasting for building energy consumption considering IPMVP recommendations, WEO and COP27 scenarios," Applied Energy, Elsevier, vol. 339(C).
  133. Luo, Na & Langevin, Jared & Chandra-Putra, Handi & Lee, Sang Hoon, 2022. "Quantifying the effect of multiple load flexibility strategies on commercial building electricity demand and services via surrogate modeling," Applied Energy, Elsevier, vol. 309(C).
  134. Andrzej Pacana & Karolina Czerwińska & Grzegorz Ostasz, 2023. "Analysis of the Level of Efficiency of Control Methods in the Context of Energy Intensity," Energies, MDPI, vol. 16(8), pages 1-26, April.
  135. Yun-Yi Zhang & Kai Kang & Jia-Rui Lin & Jian-Ping Zhang & Yi Zhang, 2020. "Building information modeling–based cyber-physical platform for building performance monitoring," International Journal of Distributed Sensor Networks, , vol. 16(2), pages 15501477209, February.
  136. Abokersh, Mohamed Hany & Spiekman, Marleen & Vijlbrief, Olav & van Goch, T.A.J. & Vallès, Manel & Boer, Dieter, 2021. "A real-time diagnostic tool for evaluating the thermal performance of nearly zero energy buildings," Applied Energy, Elsevier, vol. 281(C).
  137. Fath U Min Ullah & Noman Khan & Tanveer Hussain & Mi Young Lee & Sung Wook Baik, 2021. "Diving Deep into Short-Term Electricity Load Forecasting: Comparative Analysis and a Novel Framework," Mathematics, MDPI, vol. 9(6), pages 1-22, March.
  138. Haiyan Meng & Yakai Lu & Zhe Tian & Xiangbei Jiang & Zhongqing Han & Jide Niu, 2023. "Performance Evaluation Method of Day-Ahead Load Prediction Models in a District Heating and Cooling System: A Case Study," Energies, MDPI, vol. 16(14), pages 1-19, July.
  139. Pallonetto, Fabiano & De Rosa, Mattia & D’Ettorre, Francesco & Finn, Donal P., 2020. "On the assessment and control optimisation of demand response programs in residential buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
  140. Shamim Akhtar & Muhamad Zahim Bin Sujod & Syed Sajjad Hussain Rizvi, 2022. "An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms," Energies, MDPI, vol. 15(15), pages 1-19, August.
  141. Malte Stienecker & Anne Hagemeier, 2023. "Developing Feedforward Neural Networks as Benchmark for Load Forecasting: Methodology Presentation and Application to Hospital Heat Load Forecasting," Energies, MDPI, vol. 16(4), pages 1-22, February.
  142. 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).
  143. Razak Olu-Ajayi & Hafiz Alaka & Hakeem Owolabi & Lukman Akanbi & Sikiru Ganiyu, 2023. "Data-Driven Tools for Building Energy Consumption Prediction: A Review," Energies, MDPI, vol. 16(6), pages 1-20, March.
  144. Wei, Jin & Ni, Yang & Zhang, Yue-Jun, 2020. "The mitigation strategies for bottom environment of service-oriented public building from a micro-scale perspective: A case study in China," Energy, Elsevier, vol. 205(C).
  145. Thomas Wu & Bo Wang & Dongdong Zhang & Ziwei Zhao & Hongyu Zhu, 2023. "Benchmarking Evaluation of Building Energy Consumption Based on Data Mining," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
  146. Li, Guannan & Wu, Yubei & Yoon, Sungmin & Fang, Xi, 2024. "Comprehensive transferability assessment of short-term cross-building-energy prediction using deep adversarial network transfer learning," Energy, Elsevier, vol. 299(C).
  147. 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).
  148. 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).
  149. Jin, Xin & Wu, Fengping & Xu, Tao & Huang, Gongsheng & Wu, Huijun & Zhou, Xiaoqing & Wang, Dengjia & Liu, Yanfeng & Lai, Alvin CK., 2021. "Experimental investigation of the novel melting point modified Phase–Change material for heat pump latent heat thermal energy storage application," Energy, Elsevier, vol. 216(C).
  150. Severinsen, A. & Myrland, Ø., 2022. "Statistical learning to estimate energy savings from retrofitting in the Norwegian food retail market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
  151. Israr Ullah & Rashid Ahmad & DoHyeun Kim, 2018. "A Prediction Mechanism of Energy Consumption in Residential Buildings Using Hidden Markov Model," Energies, MDPI, vol. 11(2), pages 1-20, February.
  152. Khan, Zulfiqar Ahmad & Khan, Shabbir Ahmad & Hussain, Tanveer & Baik, Sung Wook, 2024. "DSPM: Dual sequence prediction model for efficient energy management in micro-grid," Applied Energy, Elsevier, vol. 356(C).
  153. Ijaz Ul Haq & Amin Ullah & Samee Ullah Khan & Noman Khan & Mi Young Lee & Seungmin Rho & Sung Wook Baik, 2021. "Sequential Learning-Based Energy Consumption Prediction Model for Residential and Commercial Sectors," Mathematics, MDPI, vol. 9(6), pages 1-17, March.
  154. Abhinandana Boodi & Karim Beddiar & Yassine Amirat & Mohamed Benbouzid, 2022. "Building Thermal-Network Models: A Comparative Analysis, Recommendations, and Perspectives," Energies, MDPI, vol. 15(4), pages 1-27, February.
  155. Tran, Duc-Hoc & Luong, Duc-Long & Chou, Jui-Sheng, 2020. "Nature-inspired metaheuristic ensemble model for forecasting energy consumption in residential buildings," Energy, Elsevier, vol. 191(C).
  156. Li, Sihui & Peng, Jinqing & Wang, Meng & Wang, Kai & Li, Houpei & Lu, Chujie, 2024. "Approaching nearly zero energy of PV direct air conditioners by integrating building design, load flexibility and PCM," Renewable Energy, Elsevier, vol. 221(C).
  157. Guillaume Guerard & Hugo Pousseur & Ihab Taleb, 2021. "Isolated Areas Consumption Short-Term Forecasting Method," Energies, MDPI, vol. 14(23), pages 1-23, November.
  158. Pedone, Livio & Molaioni, Filippo & Vallati, Andrea & Pampanin, Stefano, 2023. "Energy refurbishment planning of Italian school buildings using data-driven predictive models," Applied Energy, Elsevier, vol. 350(C).
  159. Ramya Kuppusamy & Srete Nikolovski & Yuvaraja Teekaraman, 2023. "Review of Machine Learning Techniques for Power Quality Performance Evaluation in Grid-Connected Systems," Sustainability, MDPI, vol. 15(20), pages 1-29, October.
  160. Chang Zhao & Jianhui Zhao & Mei Wang, 2024. "Performance Analysis and Optimization of Solar-Coupled Mine Water-Source Heat Pump Combined Heating and Cooling System," Sustainability, MDPI, vol. 16(11), pages 1-20, June.
  161. Maher Selim & Ryan Zhou & Wenying Feng & Peter Quinsey, 2021. "Estimating Energy Forecasting Uncertainty for Reliable AI Autonomous Smart Grid Design," Energies, MDPI, vol. 14(1), pages 1-15, January.
  162. Abbasabadi, Narjes & Ashayeri, Mehdi & Azari, Rahman & Stephens, Brent & Heidarinejad, Mohammad, 2019. "An integrated data-driven framework for urban energy use modeling (UEUM)," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
  163. Marta Laska & Katarzyna Reclik, 2024. "Analysis of Internal Conditions and Energy Consumption during Winter in an Apartment Located in a Tenement Building in Poland," Sustainability, MDPI, vol. 16(10), pages 1-21, May.
  164. Xu, Yuanjin & Li, Fei & Asgari, Armin, 2022. "Prediction and optimization of heating and cooling loads in a residential building based on multi-layer perceptron neural network and different optimization algorithms," Energy, Elsevier, vol. 240(C).
  165. Li, Han & Johra, Hicham & de Andrade Pereira, Flavia & Hong, Tianzhen & Le Dréau, Jérôme & Maturo, Anthony & Wei, Mingjun & Liu, Yapan & Saberi-Derakhtenjani, Ali & Nagy, Zoltan & Marszal-Pomianowska,, 2023. "Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives," Applied Energy, Elsevier, vol. 343(C).
  166. Xuan Liu & Qiancheng Wang & Hsi-Hsien Wei & Hung-Lin Chi & Yaotian Ma & Izzy Yi Jian, 2020. "Psychological and Demographic Factors Affecting Household Energy-Saving Intentions: A TPB-Based Study in Northwest China," Sustainability, MDPI, vol. 12(3), pages 1-20, January.
  167. Aslam, Sheraz & Herodotou, Herodotos & Mohsin, Syed Muhammad & Javaid, Nadeem & Ashraf, Nouman & Aslam, Shahzad, 2021. "A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
  168. Vavouris, Apostolos & Guasselli, Fernanda & Stankovic, Lina & Stankovic, Vladimir & Gram-Hanssen, Kirsten & Didierjean, Sébastien, 2024. "A complex mixed-methods data-driven energy-centric evaluation of net-positive households," Applied Energy, Elsevier, vol. 367(C).
  169. Zhang, Chengyu & Ma, Liangdong & Han, Xing & Zhao, Tianyi, 2024. "Reconstituted data-driven air conditioning energy consumption prediction system employing occupant-orientated probability model as input and swarm intelligence optimization algorithms," Energy, Elsevier, vol. 288(C).
  170. Chen, Xiaoyi & Dong, Zhenbiao & Zhu, Liujuan & Ling, Xiang, 2023. "Mass transfer performance inside Ca-based thermochemical energy storage materials under different operating conditions," Renewable Energy, Elsevier, vol. 205(C), pages 340-348.
  171. Capozzoli, Alfonso & Piscitelli, Marco Savino & Brandi, Silvio & Grassi, Daniele & Chicco, Gianfranco, 2018. "Automated load pattern learning and anomaly detection for enhancing energy management in smart buildings," Energy, Elsevier, vol. 157(C), pages 336-352.
  172. Cai, Yang & Wang, Lei & Ding, Wen-Tao & Liu, Di & Zhao, Fu-Yun, 2019. "Thermal performance of an active thermoelectric ventilation system applied for built space cooling: Network model and finite time thermodynamic optimization," Energy, Elsevier, vol. 170(C), pages 915-930.
  173. Xie, Hao & Yu, Bendong & Wang, Jun & Ji, Jie, 2021. "A novel disinfected Trombe wall for space heating and virus inactivation: Concept and performance investigation," Applied Energy, Elsevier, vol. 291(C).
  174. Wakui, Tetsuya & Sawada, Kento & Yokoyama, Ryohei & Aki, Hirohisa, 2019. "Predictive management for energy supply networks using photovoltaics, heat pumps, and battery by two-stage stochastic programming and rule-based control," Energy, Elsevier, vol. 179(C), pages 1302-1319.
  175. Kasım Zor & Özgür Çelik & Oğuzhan Timur & Ahmet Teke, 2020. "Short-Term Building Electrical Energy Consumption Forecasting by Employing Gene Expression Programming and GMDH Networks," Energies, MDPI, vol. 13(5), pages 1-24, March.
  176. Gao, Lei & Liu, Tianyuan & Cao, Tao & Hwang, Yunho & Radermacher, Reinhard, 2021. "Comparing deep learning models for multi energy vectors prediction on multiple types of building," Applied Energy, Elsevier, vol. 301(C).
  177. Luo, X.J. & Oyedele, Lukumon O. & Ajayi, Anuoluwapo O. & Akinade, Olugbenga O. & Owolabi, Hakeem A. & Ahmed, Ashraf, 2020. "Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
  178. Senocak, Ahmet Alp & Guner Goren, Hacer, 2023. "Three-phase artificial intelligence-geographic information systems-based biomass network design approach: A case study in Denizli," Applied Energy, Elsevier, vol. 343(C).
  179. Laura Canale & Anna Rita Di Fazio & Mario Russo & Andrea Frattolillo & Marco Dell’Isola, 2021. "An Overview on Functional Integration of Hybrid Renewable Energy Systems in Multi-Energy Buildings," Energies, MDPI, vol. 14(4), pages 1-33, February.
  180. Marcin Relich & Arkadiusz Gola & Małgorzata Jasiulewicz-Kaczmarek, 2022. "Identifying Improvement Opportunities in Product Design for Reducing Energy Consumption," Energies, MDPI, vol. 15(24), pages 1-19, December.
  181. Wang, Lan & Lee, Eric W.M. & Hussian, Syed Asad & Yuen, Anthony Chun Yin & Feng, Wei, 2021. "Quantitative impact analysis of driving factors on annual residential building energy end-use combining machine learning and stochastic methods," Applied Energy, Elsevier, vol. 299(C).
  182. Moudgil, Vipul & Hewage, Kasun & Hussain, Syed Asad & Sadiq, Rehan, 2023. "Integration of IoT in building energy infrastructure: A critical review on challenges and solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 174(C).
  183. Marco Pritoni & Drew Paine & Gabriel Fierro & Cory Mosiman & Michael Poplawski & Avijit Saha & Joel Bender & Jessica Granderson, 2021. "Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis," Energies, MDPI, vol. 14(7), pages 1-37, April.
  184. 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).
  185. 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.
  186. Ravita D. Prasad, 2024. "School Electricity Consumption in a Small Island Country: The Case of Fiji," Energies, MDPI, vol. 17(7), pages 1-25, April.
  187. Hu, Zehuan & Gao, Yuan & Sun, Luning & Mae, Masayuki & Imaizumi, Taiji, 2024. "Self-learning dynamic graph neural network with self-attention based on historical data and future data for multi-task multivariate residential air conditioning forecasting," Applied Energy, Elsevier, vol. 364(C).
  188. Paul Anton Verwiebe & Stephan Seim & Simon Burges & Lennart Schulz & Joachim Müller-Kirchenbauer, 2021. "Modeling Energy Demand—A Systematic Literature Review," Energies, MDPI, vol. 14(23), pages 1-58, November.
  189. Bampoulas, Adamantios & Pallonetto, Fabiano & Mangina, Eleni & Finn, Donal P., 2022. "An ensemble learning-based framework for assessing the energy flexibility of residential buildings with multicomponent energy systems," Applied Energy, Elsevier, vol. 315(C).
  190. 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).
  191. Finck, Christian & Li, Rongling & Zeiler, Wim, 2020. "Optimal control of demand flexibility under real-time pricing for heating systems in buildings: A real-life demonstration," Applied Energy, Elsevier, vol. 263(C).
  192. Achini Shanika Weerasinghe & Eziaku Onyeizu Rasheed & James Olabode Bamidele Rotimi, 2023. "Occupants’ Decision-Making of Their Energy Behaviours in Office Environments: A Case of New Zealand," Sustainability, MDPI, vol. 15(3), pages 1-27, January.
  193. Shaoxiong Li & Le Liu & Changhai Peng, 2020. "A Review of Performance-Oriented Architectural Design and Optimization in the Context of Sustainability: Dividends and Challenges," Sustainability, MDPI, vol. 12(4), pages 1-36, February.
  194. Zhang, Guiqing & Tian, Chenlu & Li, Chengdong & Zhang, Jun Jason & Zuo, Wangda, 2020. "Accurate forecasting of building energy consumption via a novel ensembled deep learning method considering the cyclic feature," Energy, Elsevier, vol. 201(C).
  195. Wenninger, Simon & Kaymakci, Can & Wiethe, Christian, 2022. "Explainable long-term building energy consumption prediction using QLattice," Applied Energy, Elsevier, vol. 308(C).
  196. Bampoulas, Adamantios & Pallonetto, Fabiano & Mangina, Eleni & Finn, Donal P., 2023. "A Bayesian deep-learning framework for assessing the energy flexibility of residential buildings with multicomponent energy systems," Applied Energy, Elsevier, vol. 348(C).
  197. Zou, Rongwei & Yang, Qiliang & Xing, Jianchun & Zhou, Qizhen & Xie, Liqiang & Chen, Wenjie, 2024. "Predicting the electric power consumption of office buildings based on dynamic and static hybrid data analysis," Energy, Elsevier, vol. 290(C).
  198. Guo, Yabin & Wang, Jiangyu & Chen, Huanxin & Li, Guannan & Liu, Jiangyan & Xu, Chengliang & Huang, Ronggeng & Huang, Yao, 2018. "Machine learning-based thermal response time ahead energy demand prediction for building heating systems," Applied Energy, Elsevier, vol. 221(C), pages 16-27.
  199. Fan, Cheng & Chen, Ruikun & Mo, Jinhan & Liao, Longhui, 2024. "Personalized federated learning for cross-building energy knowledge sharing: Cost-effective strategies and model architectures," Applied Energy, Elsevier, vol. 362(C).
  200. Zhan, Sicheng & Chong, Adrian, 2021. "Data requirements and performance evaluation of model predictive control in buildings: A modeling perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
  201. Salah Bouktif & Ali Ouni & Sanja Lazarova-Molnar, 2022. "Towards a Rigorous Consideration of Occupant Behaviours of Residential Households for Effective Electrical Energy Savings: An Overview," Energies, MDPI, vol. 15(5), pages 1-30, February.
  202. Ibrahim Ali Kachalla & Christian Ghiaus, 2024. "Electric Water Boiler Energy Prediction: State-of-the-Art Review of Influencing Factors, Techniques, and Future Directions," Energies, MDPI, vol. 17(2), pages 1-32, January.
  203. Choi, Jongwoo & Lee, Il-Woo & Cha, Suk-Won, 2022. "Analysis of data errors in the solar photovoltaic monitoring system database: An overview of nationwide power plants in Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
  204. Olman Araya Mejías & Cristina Montalvo & Agustín García-Berrocal & María Cubillo & Daniel Gordaliza, 2021. "Energy Savings after Comprehensive Renovations of the Building: A Case Study in the United Kingdom and Italy," Energies, MDPI, vol. 14(20), pages 1-18, October.
  205. Meng Wang & Junqi Yu & Meng Zhou & Wei Quan & Renyin Cheng, 2023. "Joint Forecasting Model for the Hourly Cooling Load and Fluctuation Range of a Large Public Building Based on GA-SVM and IG-SVM," Sustainability, MDPI, vol. 15(24), pages 1-23, December.
  206. Athila Santos & Na Liu & Muhyiddine Jradi, 2021. "AUSTRET: An Automated Step Response Testing Tool for Building Automation and Control Systems," Energies, MDPI, vol. 14(13), pages 1-20, July.
  207. Prince, & Hati, Ananda Shankar & Kumar, Prashant, 2023. "An adaptive neural fuzzy interface structure optimisation for prediction of energy consumption and airflow of a ventilation system," Applied Energy, Elsevier, vol. 337(C).
  208. Somu, Nivethitha & Raman M R, Gauthama & Ramamritham, Krithi, 2021. "A deep learning framework for building energy consumption forecast," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
  209. Xiao Han & Chu Wei, 2021. "Household energy consumption: state of the art, research gaps, and future prospects," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 12479-12504, August.
  210. Miriam Benedetti & Francesca Bonfà & Vito Introna & Annalisa Santolamazza & Stefano Ubertini, 2019. "Real Time Energy Performance Control for Industrial Compressed Air Systems: Methodology and Applications," Energies, MDPI, vol. 12(20), pages 1-28, October.
  211. Saidjon Shiralievich Tavarov & Pavel Matrenin & Murodbek Safaraliev & Mihail Senyuk & Svetlana Beryozkina & Inga Zicmane, 2023. "Forecasting of Electricity Consumption by Household Consumers Using Fuzzy Logic Based on the Development Plan of the Power System of the Republic of Tajikistan," Sustainability, MDPI, vol. 15(4), pages 1-14, February.
  212. Anand Krishnan Prakash & Susu Xu & Ram Rajagopal & Hae Young Noh, 2018. "Robust Building Energy Load Forecasting Using Physically-Based Kernel Models," Energies, MDPI, vol. 11(4), pages 1-21, April.
  213. Ke Wang & Yafei Zhao & Rajan Kumar Gangadhari & Zhixing Li, 2021. "Analyzing the Adoption Challenges of the Internet of Things (IoT) and Artificial Intelligence (AI) for Smart Cities in China," Sustainability, MDPI, vol. 13(19), pages 1-35, October.
  214. Gebrail Bekdaş & Yaren Aydın & Ümit Isıkdağ & Aidin Nobahar Sadeghifam & Sanghun Kim & Zong Woo Geem, 2023. "Prediction of Cooling Load of Tropical Buildings with Machine Learning," Sustainability, MDPI, vol. 15(11), pages 1-17, June.
  215. Nweye, Kingsley & Nagy, Zoltan, 2022. "MARTINI: Smart meter driven estimation of HVAC schedules and energy savings based on Wi-Fi sensing and clustering," Applied Energy, Elsevier, vol. 316(C).
  216. Xiong, Suqin & Li, Yang & Li, Qiuyang & Ye, Zhishan & Pouramini, Somayeh, 2024. "Energy consumption prediction by modified fish migration optimization algorithm: City single-family homes," Applied Energy, Elsevier, vol. 353(PA).
  217. Kathirgamanathan, Anjukan & De Rosa, Mattia & Mangina, Eleni & Finn, Donal P., 2021. "Data-driven predictive control for unlocking building energy flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
  218. Fateme Dinmohammadi & Yuxuan Han & Mahmood Shafiee, 2023. "Predicting Energy Consumption in Residential Buildings Using Advanced Machine Learning Algorithms," Energies, MDPI, vol. 16(9), pages 1-23, April.
  219. Attila Kostyák & Csaba Béres & Szabolcs Szekeres & Imre Csáky, 2022. "Buffer Tank Discharge Strategies in the Case of a Centrifugal Water Chiller," Energies, MDPI, vol. 16(1), pages 1-15, December.
  220. Zhang, Xiaohai & Ramírez-Mendiola, José Luis & Li, Mingtao & Guo, Liejin, 2022. "Electricity consumption pattern analysis beyond traditional clustering methods: A novel self-adapting semi-supervised clustering method and application case study," Applied Energy, Elsevier, vol. 308(C).
  221. Haosen Qin & Zhen Yu & Tailu Li & Xueliang Liu & Li Li, 2022. "Heating Control Strategy Based on Dynamic Programming for Building Energy Saving and Emission Reduction," IJERPH, MDPI, vol. 19(21), pages 1-27, October.
  222. Hany Habbak & Mohamed Mahmoud & Khaled Metwally & Mostafa M. Fouda & Mohamed I. Ibrahem, 2023. "Load Forecasting Techniques and Their Applications in Smart Grids," Energies, MDPI, vol. 16(3), pages 1-33, February.
  223. Satre-Meloy, Aven & Diakonova, Marina & Grünewald, Philipp, 2020. "Cluster analysis and prediction of residential peak demand profiles using occupant activity data," Applied Energy, Elsevier, vol. 260(C).
  224. Jason Runge & Radu Zmeureanu, 2019. "Forecasting Energy Use in Buildings Using Artificial Neural Networks: A Review," Energies, MDPI, vol. 12(17), pages 1-27, August.
  225. Amir Mosavi & Mohsen Salimi & Sina Faizollahzadeh Ardabili & Timon Rabczuk & Shahaboddin Shamshirband & Annamaria R. Varkonyi-Koczy, 2019. "State of the Art of Machine Learning Models in Energy Systems, a Systematic Review," Energies, MDPI, vol. 12(7), pages 1-42, April.
  226. Fan, Cheng & Sun, Yongjun & Xiao, Fu & Ma, Jie & Lee, Dasheng & Wang, Jiayuan & Tseng, Yen Chieh, 2020. "Statistical investigations of transfer learning-based methodology for short-term building energy predictions," Applied Energy, Elsevier, vol. 262(C).
  227. Li, Lechen & Meinrenken, Christoph J. & Modi, Vijay & Culligan, Patricia J., 2021. "Short-term apartment-level load forecasting using a modified neural network with selected auto-regressive features," Applied Energy, Elsevier, vol. 287(C).
  228. Ion-Costinel Mareș & Tiberiu Catalina & Marian-Andrei Istrate & Alexandra Cucoș & Tiberius Dicu & Betty Denissa Burghele & Kinga Hening & Lelia Letitia Popescu & Razvan Stefan Popescu, 2021. "Research on Best Solution for Improving Indoor Air Quality and Reducing Energy Consumption in a High-Risk Radon Dwelling from Romania," IJERPH, MDPI, vol. 18(23), pages 1-18, November.
  229. Chendong Wang & Lihong Zheng & Jianjuan Yuan & Ke Huang & Zhihua Zhou, 2022. "Building Heat Demand Prediction Based on Reinforcement Learning for Thermal Comfort Management," Energies, MDPI, vol. 15(21), pages 1-20, October.
  230. Liang, Xinbin & Chen, Siliang & Zhu, Xu & Jin, Xinqiao & Du, Zhimin, 2023. "Domain knowledge decomposition of building energy consumption and a hybrid data-driven model for 24-h ahead predictions," Applied Energy, Elsevier, vol. 344(C).
  231. Huakun Huang & Dingrong Dai & Longtao Guo & Sihui Xue & Huijun Wu, 2023. "AI and Big Data-Empowered Low-Carbon Buildings: Challenges and Prospects," Sustainability, MDPI, vol. 15(16), pages 1-21, August.
  232. Liu, Jiangyan & Zhang, Qing & Dong, Zhenxiang & Li, Xin & Li, Guannan & Xie, Yi & Li, Kuining, 2021. "Quantitative evaluation of the building energy performance based on short-term energy predictions," Energy, Elsevier, vol. 223(C).
  233. Ali, Usman & Shamsi, Mohammad Haris & Bohacek, Mark & Purcell, Karl & Hoare, Cathal & Mangina, Eleni & O’Donnell, James, 2020. "A data-driven approach for multi-scale GIS-based building energy modeling for analysis, planning and support decision making," Applied Energy, Elsevier, vol. 279(C).
  234. Wiethe, Christian & Wenninger, Simon, 2023. "The influence of building energy performance prediction accuracy on retrofit rates," Energy Policy, Elsevier, vol. 177(C).
  235. Khan, Rana Asad Javid & Thaheem, Muhammad Jamaluddin & Ali, Tauha Hussain, 2020. "Are Pakistani homebuyers ready to adopt sustainable housing? An insight into their willingness to pay," Energy Policy, Elsevier, vol. 143(C).
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