IDEAS home Printed from https://ideas.repec.org/r/eee/energy/v89y2015icp1087-1100.html
   My bibliography  Save this item

Energy retrofit analysis toolkits for commercial buildings: A review

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Thrampoulidis, Emmanouil & Mavromatidis, Georgios & Lucchi, Aurelien & Orehounig, Kristina, 2021. "A machine learning-based surrogate model to approximate optimal building retrofit solutions," Applied Energy, Elsevier, vol. 281(C).
  2. Rachael Sherman & Hariharan Naganathan & Kristen Parrish, 2021. "Energy Savings Results from Small Commercial Building Retrofits in the US," Energies, MDPI, vol. 14(19), pages 1-16, September.
  3. 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.
  4. Garg, Amit & Maheshwari, Jyoti & Shukla, P.R. & Rawal, Rajan, 2017. "Energy appliance transformation in commercial buildings in India under alternate policy scenarios," Energy, Elsevier, vol. 140(P1), pages 952-965.
  5. Kotarela, Faidra & Kyritsis, Anastasios & Agathokleous, Rafaela & Papanikolaou, Nick, 2023. "On the exploitation of dynamic simulations for the design of buildings energy systems," Energy, Elsevier, vol. 271(C).
  6. Gil-Baez, Maite & Padura, Ángela Barrios & Huelva, Marta Molina, 2019. "Passive actions in the building envelope to enhance sustainability of schools in a Mediterranean climate," Energy, Elsevier, vol. 167(C), pages 144-158.
  7. Christina Diakaki & Evangelos Grigoroudis, 2021. "Improving Energy Efficiency in Buildings Using an Interactive Mathematical Programming Approach," Sustainability, MDPI, vol. 13(8), pages 1-25, April.
  8. Jin, Xiaoyu & Xiao, Fu & Zhang, Chong & Chen, Zhijie, 2022. "Semi-supervised learning based framework for urban level building electricity consumption prediction," Applied Energy, Elsevier, vol. 328(C).
  9. Ascione, Fabrizio & Bianco, Nicola & De Stasio, Claudio & Mauro, Gerardo Maria & Vanoli, Giuseppe Peter, 2017. "Artificial neural networks to predict energy performance and retrofit scenarios for any member of a building category: A novel approach," Energy, Elsevier, vol. 118(C), pages 999-1017.
  10. Chen, Yixing & Deng, Zhang & Hong, Tianzhen, 2020. "Automatic and rapid calibration of urban building energy models by learning from energy performance database," Applied Energy, Elsevier, vol. 277(C).
  11. Lizana, Jesus & Serrano-Jimenez, Antonio & Ortiz, Carlos & Becerra, Jose A. & Chacartegui, Ricardo, 2018. "Energy assessment method towards low-carbon energy schools," Energy, Elsevier, vol. 159(C), pages 310-326.
  12. 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).
  13. Abdulrahman Alanezi & Kevin P. Hallinan & Kefan Huang, 2021. "Automated Residential Energy Audits Using a Smart WiFi Thermostat-Enabled Data Mining Approach," Energies, MDPI, vol. 14(9), pages 1-23, April.
  14. Henrik Engelbrecht Foldager & Rasmus Camillus Jeppesen & Muhyiddine Jradi, 2019. "DanRETRO: A Decision-Making Tool for Energy Retrofit Design and Assessment of Danish Buildings," Sustainability, MDPI, vol. 11(14), pages 1-19, July.
  15. Gireesh Nair & Leo Verde & Thomas Olofsson, 2022. "A Review on Technical Challenges and Possibilities on Energy Efficient Retrofit Measures in Heritage Buildings," Energies, MDPI, vol. 15(20), pages 1-20, October.
  16. Nora Munguia & Javier Esquer & Hector Guzman & Janim Herrera & Jesus Gutierrez-Ruelas & Luis Velazquez, 2020. "Energy Efficiency in Public Buildings: A Step toward the UN 2030 Agenda for Sustainable Development," Sustainability, MDPI, vol. 12(3), pages 1-18, February.
  17. Ferahtia, Seydali & Rezk, Hegazy & Olabi, A.G. & Alhumade, Hesham & Bamufleh, Hisham S. & Doranehgard, Mohammad Hossein & Abdelkareem, Mohammad Ali, 2022. "Optimal techno-economic multi-level energy management of renewable-based DC microgrid for commercial buildings applications," Applied Energy, Elsevier, vol. 327(C).
  18. Yujie Xu & Vivian Loftness & Edson Severnini, 2021. "Using Machine Learning to Predict Retrofit Effects for a Commercial Building Portfolio," Energies, MDPI, vol. 14(14), pages 1-24, July.
  19. Lešnik, Maja & Premrov, Miroslav & Žegarac Leskovar, Vesna, 2018. "Design parameters of the timber-glass upgrade module and the existing building: Impact on the energy-efficient refurbishment process," Energy, Elsevier, vol. 162(C), pages 1125-1138.
  20. Deb, C. & Schlueter, A., 2021. "Review of data-driven energy modelling techniques for building retrofit," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
  21. Miller, Clayton & Nagy, Zoltán & Schlueter, Arno, 2018. "A review of unsupervised statistical learning and visual analytics techniques applied to performance analysis of non-residential buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1365-1377.
  22. 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.
  23. Zheng, Donglin & Yu, Lijun & Wang, Lizhen, 2019. "A techno-economic-risk decision-making methodology for large-scale building energy efficiency retrofit using Monte Carlo simulation," Energy, Elsevier, vol. 189(C).
  24. Mahmud, Khizir & Amin, Uzma & Hossain, M.J. & Ravishankar, Jayashri, 2018. "Computational tools for design, analysis, and management of residential energy systems," Applied Energy, Elsevier, vol. 221(C), pages 535-556.
  25. Yung Yau & Huiying (Cynthia) Hou & Ka Chi Yip & Queena Kun Qian, 2021. "Transaction Cost and Agency Perspectives on Eco-Certification of Existing Buildings: A Study of Hong Kong," Energies, MDPI, vol. 14(19), pages 1-20, October.
  26. Galatioto, A. & Ciulla, G. & Ricciu, R., 2017. "An overview of energy retrofit actions feasibility on Italian historical buildings," Energy, Elsevier, vol. 137(C), pages 991-1000.
  27. Hou, Jing & Liu, Yisheng & Wu, Yong & Zhou, Nan & Feng, Wei, 2016. "Comparative study of commercial building energy-efficiency retrofit policies in four pilot cities in China," Energy Policy, Elsevier, vol. 88(C), pages 204-215.
  28. Kyung Hwa Cho & Sun Sook Kim, 2019. "Energy Performance Assessment According to Data Acquisition Levels of Existing Buildings," Energies, MDPI, vol. 12(6), pages 1-17, March.
  29. Alessia Buda & Ernst Jan de Place Hansen & Alexander Rieser & Emanuela Giancola & Valeria Natalina Pracchi & Sara Mauri & Valentina Marincioni & Virginia Gori & Kalliopi Fouseki & Cristina S. Polo Lóp, 2021. "Conservation-Compatible Retrofit Solutions in Historic Buildings: An Integrated Approach," Sustainability, MDPI, vol. 13(5), pages 1-19, March.
  30. Qiong He & S. Thomas Ng & Md. Uzzal Hossain & Godfried L. Augenbroe, 2020. "A Data-driven Approach for Sustainable Building Retrofit—A Case Study of Different Climate Zones in China," Sustainability, MDPI, vol. 12(11), pages 1-29, June.
  31. Thrampoulidis, Emmanouil & Hug, Gabriela & Orehounig, Kristina, 2023. "Approximating optimal building retrofit solutions for large-scale retrofit analysis," Applied Energy, Elsevier, vol. 333(C).
  32. Hong, Tianzhen & Piette, Mary Ann & Chen, Yixing & Lee, Sang Hoon & Taylor-Lange, Sarah C. & Zhang, Rongpeng & Sun, Kaiyu & Price, Phillip, 2015. "Commercial Building Energy Saver: An energy retrofit analysis toolkit," Applied Energy, Elsevier, vol. 159(C), pages 298-309.
  33. García Kerdan, Iván & Raslan, Rokia & Ruyssevelt, Paul, 2016. "An exergy-based multi-objective optimisation model for energy retrofit strategies in non-domestic buildings," Energy, Elsevier, vol. 117(P2), pages 506-522.
  34. Marco Castagna & Olga Somova & Cristian Pozza & Giuseppe De Michele & Federico Garzia & Daniele Antonucci & Roberta Pernetti, 2024. "Optimizing Energy Renovation in Building Portfolios: Approach and Decision-Making Platform," Energies, MDPI, vol. 17(22), pages 1-17, November.
  35. Mohammed Seddiki & Amar Bennadji & Richard Laing & David Gray & Jamal M. Alabid, 2021. "Review of Existing Energy Retrofit Decision Tools for Homeowners," Sustainability, MDPI, vol. 13(18), pages 1-23, September.
  36. 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.
  37. Kalevi Piira & Julia Kantorovitch & Lotta Kannari & Jouko Piippo & Nam Vu Hoang, 2022. "Decision Support Tool to Enable Real-Time Data-Driven Building Energy Retrofitting Design," Energies, MDPI, vol. 15(15), pages 1-17, July.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.