Energy planning and forecasting approaches for supporting physical improvement strategies in the building sector: A review
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DOI: 10.1016/j.rser.2016.06.040
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- 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.
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- 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).
- Oraiopoulos, A. & Howard, B., 2022. "On the accuracy of Urban Building Energy Modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
- 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).
- Spiliotis, Evangelos & Petropoulos, Fotios & Kourentzes, Nikolaos & Assimakopoulos, Vassilios, 2018. "Cross-temporal aggregation: Improving the forecast accuracy of hierarchical electricity consumption," MPRA Paper 91762, University Library of Munich, Germany.
- Rafiee, A. & Dias, E. & Koomen, E., 2019. "Analysing the impact of spatial context on the heat consumption of individual households," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 461-470.
- Chen, Yibo & Wu, Jianzhong, 2018. "Distribution patterns of energy consumed in classified public buildings through the data mining process," Applied Energy, Elsevier, vol. 226(C), pages 240-251.
- 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.
- 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.
- Chalal, M.L. & Medjdoub, B. & Bezai, N. & Bull, R. & Zune, M., 2022. "Visualisation in energy eco-feedback systems: A systematic review of good practice," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
- Munan Li, 2019. "Visualizing the studies on smart cities in the past two decades: a two-dimensional perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 683-705, August.
- Philipp Rode & Alexandra Gomes & Muhammad Adeel & Fizzah Sajjad & Andreas Koch & Syed Monjur Murshed, 2020. "Between Abundance and Constraints: The Natural Resource Equation of Asia’s Diverging, Higher-Income City Models," Land, MDPI, vol. 9(11), pages 1-33, October.
- Felix Biessmann & Bhaskar Kamble & Rita Streblow, 2023. "An Automated Machine Learning Approach towards Energy Saving Estimates in Public Buildings," Energies, MDPI, vol. 16(19), pages 1-12, September.
- Spiliotis, Evangelos & Petropoulos, Fotios & Kourentzes, Nikolaos & Assimakopoulos, Vassilios, 2020. "Cross-temporal aggregation: Improving the forecast accuracy of hierarchical electricity consumption," Applied Energy, Elsevier, vol. 261(C).
- 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.
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Keywords
Urban energy planning; Smart cities; Future cities; Energy forecasting; Building sector;All these keywords.
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