Data for Urban Scale Building Energy Modelling: Assessing Impacts and Overcoming Availability Challenges
作者： Solène Goy , François Maréchal , Donal Finn
DOI: 10.3390/EN13164244
关键词:
摘要: Data are essential to urban building energy models and yet, obtaining sufficient accurate data at a large-scale is challenging. Previous studies have highlighted that the impact on case has not been sufficiently discussed. This paper addresses this gap by providing an analysis of input modelling scale. The proposes joint review accessibility identify areas where future survey efforts should be concentrated. Moreover, Morris sensitivity carried out residential study, rank parameters space heating demand. shows accessible whole process, from approach selection model replicability. setpoint thermal characteristics were most impactful for study considered. Solutions proposed overcome availability issues include organising annual workshops between users owners, or developing online databases could populated volunteer-basis owners. Overall, overcoming challenges transition towards smarter cities, will require improved communication all city stakeholders.
mdpi.com
sci-hub.st 参考文章(66)
Jonas Allegrini, Kristina Orehounig, Georgios Mavromatidis, Florian Ruesch, Viktor Dorer, Ralph Evins, A review of modelling approaches and tools for the simulation of district-scale energy systems Renewable & Sustainable Energy Reviews. ,vol. 52, pp. 1391- 1404 ,(2015) , 10.1016/J.RSER.2015.07.123
Robert Hecht, Gotthard Meinel, Manfred Buchroithner, Automatic identification of building types based on topographic databases – a comparison of different data sources International Journal of Cartography. ,vol. 1, pp. 18- 31 ,(2015) , 10.1080/23729333.2015.1055644
A.T. Booth, R. Choudhary, D.J. Spiegelhalter, Handling uncertainty in housing stock models Building and Environment. ,vol. 48, pp. 35- 47 ,(2012) , 10.1016/J.BUILDENV.2011.08.016
Shengwei Wang, Xinhua Xu, Simplified building model for transient thermal performance estimation using GA-based parameter identification International Journal of Thermal Sciences. ,vol. 45, pp. 419- 432 ,(2006) , 10.1016/J.IJTHERMALSCI.2005.06.009
Moritz Lauster, Jens Teichmann, Marcus Fuchs, Rita Streblow, Dirk Mueller, Low order thermal network models for dynamic simulations of buildings on city district scale Building and Environment. ,vol. 73, pp. 223- 231 ,(2014) , 10.1016/J.BUILDENV.2013.12.016
R. Mena, F. Rodríguez, M. Castilla, M.R. Arahal, A prediction model based on neural networks for the energy consumption of a bioclimatic building Energy and Buildings. ,vol. 82, pp. 142- 155 ,(2014) , 10.1016/J.ENBUILD.2014.06.052
Ilaria Ballarini, Stefano Paolo Corgnati, Vincenzo Corrado, Use of reference buildings to assess the energy saving potentials of the residential building stock: the experience of TABULA Project Energy Policy. ,vol. 68, pp. 273- 284 ,(2014) , 10.1016/J.ENPOL.2014.01.027
M. Kavgic, A. Mavrogianni, D. Mumovic, A. Summerfield, Z. Stevanovic, M. Djurovic-Petrovic, A review of bottom-up building stock models for energy consumption in the residential sector Building and Environment. ,vol. 45, pp. 1683- 1697 ,(2010) , 10.1016/J.BUILDENV.2010.01.021
Aurélie Foucquier, Sylvain Robert, Frédéric Suard, Louis Stéphan, Arnaud Jay, State of the art in building modelling and energy performances prediction: A review Renewable & Sustainable Energy Reviews. ,vol. 23, pp. 272- 288 ,(2013) , 10.1016/J.RSER.2013.03.004
Enrico Fabrizio, Valentina Monetti, Methodologies and Advancements in the Calibration of Building Energy Models Energies. ,vol. 8, pp. 2548- 2574 ,(2015) , 10.3390/EN8042548