Mapping demand for residential building thermal energy services using airborne LiDAR
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DOI: 10.1016/j.apenergy.2014.03.035
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- Martínez-Rubio, A. & Sanz-Adan, F. & Santamaría-Peña, J. & Martínez, Araceli, 2016. "Evaluating solar irradiance over facades in high building cities, based on LiDAR technology," Applied Energy, Elsevier, vol. 183(C), pages 133-147.
- Wang, Endong, 2017. "Decomposing core energy factor structure of U.S. residential buildings through principal component analysis with variable clustering on high-dimensional mixed data," Applied Energy, Elsevier, vol. 203(C), pages 858-873.
- 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).
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- Bertrand, Alexandre & Mastrucci, Alessio & Schüler, Nils & Aggoune, Riad & Maréchal, François, 2017. "Characterisation of domestic hot water end-uses for integrated urban thermal energy assessment and optimisation," Applied Energy, Elsevier, vol. 186(P2), pages 152-166.
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Keywords
Building energy; Services; Map; Modelling; Simulation; LiDAR;All these keywords.
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