Dynamic occupant density models of commercial buildings for urban energy simulation

Damassa, 2014 European Commission, 2017 China’s State Council, 2014 Cerezo Davila, 2016, Modeling Boston: a workflow for the efficient generation and maintenance of urban building energy models from existing geospatial datasets, Energy, 117, 237, 10.1016/j.energy.2016.10.057 Reinhart, 2016, Urban building energy modeling–A review of a nascent field, Build. Environ., 97, 196, 10.1016/j.buildenv.2015.12.001 Cerezo, 2017, Comparison of four building archetype characterization methods in urban building energy modeling (UBEM): a residential case study in Kuwait City, Energy Build., 154, 321, 10.1016/j.enbuild.2017.08.029 Nouvel, 2017, The influence of data quality on urban heating demand modeling using 3D city models, Comput. Environ. Urban Syst., 64, 68, 10.1016/j.compenvurbsys.2016.12.005 Feng, 2015, Simulation of occupancy in buildings, Energy Build., 87, 348, 10.1016/j.enbuild.2014.11.067 D'Oca, 2014, A data-mining approach to discover patterns of window opening and closing behavior in offices, Build. Environ., 82, 726, 10.1016/j.buildenv.2014.10.021 Monteiro, 2018, An urban building database (UBD) supporting a smart city information system, Energy Build., 158, 244, 10.1016/j.enbuild.2017.10.009 Menezes, 2012, Predicted vs. actual energy performance of non-domestic buildings: using post-occupancy evaluation data to reduce the performance gap, Appl. Energy, 97, 355, 10.1016/j.apenergy.2011.11.075 Kwok, 2011, A study of the importance of occupancy to building cooling load in prediction by intelligent approach, Energy Convers. Manag., 52, 2555, 10.1016/j.enconman.2011.02.002 Page, 2008, A generalised stochastic model for the simulation of occupant presence, Energy Build., 40, 83, 10.1016/j.enbuild.2007.01.018 Wang, 2016, Meta-modeling of occupancy variables and analysis of their impact on energy outcomes of office buildings, Appl. Energy, 174, 166, 10.1016/j.apenergy.2016.04.062 Hong, 2016, Advances in research and applications of energy-related occupant behavior in buildings, Energy Build., 116, 694, 10.1016/j.enbuild.2015.11.052 Haldi, 2017, Modelling diversity in building occupant behaviour: a novel statistical approach, J. Build. Perform. Simul., 10, 527, 10.1080/19401493.2016.1269245 Haldi, 2011, The impact of occupants' behaviour on building energy demand, J. Build. Perform. Simul., 4, 323, 10.1080/19401493.2011.558213 Tahmasebi, 2018, On the utility of occupants' behavioural diversity information for building performance simulation: an exploratory case study, Energy Build., 176, 380, 10.1016/j.enbuild.2018.07.042 Yun, 2010, Night-time ventilated offices: statistical simulations of window-use patterns from field monitoring, Sol. Energy, 84, 1216, 10.1016/j.solener.2010.03.029 Zhang, 2012, Factors influencing the occupants' window opening behaviour in a naturally ventilated office building, Build. Environ., 50, 125, 10.1016/j.buildenv.2011.10.018 O'Brien, 2017, A preliminary study of representing the inter-occupant diversity in occupant modelling, J. Build. Perform. Simul., 10, 509, 10.1080/19401493.2016.1261943 Dong, 2018, Modelling occupancy and behavior for better building design and operation---A critical review, Build. Simul., 11, 899, 10.1007/s12273-018-0452-x Gunay, 2013, A critical review of observation studies, modeling, and simulation of adaptive occupant behaviors in offices, Build. Environ., 70, 31, 10.1016/j.buildenv.2013.07.020 Haldi, 2010, Adaptive actions on shading devices in response to local visual stimuli, J. Build. Perform. Simul., 3, 135, 10.1080/19401490903580759 Yang, 2014, Coupling occupancy information with HVAC energy simulation: a systematic review of simulation programs Wang, 2011, A novel approach for building occupancy simulation, Build. Simul., 4, 149, 10.1007/s12273-011-0044-5 Ai, 2014, Occupancy estimation for smart buildings by an auto-regressive hidden markov model Erickson, 2009, Energy efficient building environment control strategies using real-time occupancy measurements Gilani, 2018, A preliminary study of occupants' use of manual lighting controls in private offices: a case study, Energy Build., 159, 572, 10.1016/j.enbuild.2017.11.055 2014 Kimura, 2017, Urban scale energy demand modelling of commercial building stock considering the variety of HVAC system configuration Li, 2018, Developing a landscape of urban building energy use with improved spatiotemporal representations in a cool-humid climate, Build. Environ., 136, 107, 10.1016/j.buildenv.2018.03.036 Feng, 2014, Statistical analysis and modeling for occupant density in commercial buildings, Fire Saf. Sci., 18, 130 Li, 2018, Live-Work-Play centers of Chinese cities: identification and temporal evolution with emerging data, Comput. Environ. Urban Syst., 71, 58, 10.1016/j.compenvurbsys.2018.04.002 Zhong, 2017, Revealing the changing spatial structure of cities from human activity patterns, Urban Stud., 54, 437, 10.1177/0042098015601599 Sun, 2015, Identifying the city center using human travel flows generated from location-based social networking data, Environ. Plan. Plan. Des., 43, 480, 10.1177/0265813515617642 Niu, 2017, Integting multi-source big data to infer building functions, Geogr. Inf. Sci., 31, 1871 Pan, 2013, Land-use classification using taxi GPS traces, IEEE Trans. Intell. Transp. Syst., 14, 113, 10.1109/TITS.2012.2209201 Nanjing Statistic Bureau, 2017 2016 Fan, 2014, Quality assessment for building footprints data on OpenStreetMap, Geogr. Inf. Sci., 28, 700, 10.1080/13658816.2013.867495 Holmes, 2017, Optimizing a parametric energy model for use in citywide residential overheating analysis Song, 2018, Mapping urban functional zones by integrating very high spatial resolution remote sensing imagery and Points of Interest: a case study of Xiamen, China, Remote Sens., 10, 1737, 10.3390/rs10111737 Caputo, 2013, A supporting method for defining energy strategies in the building sector at urban scale, Energy Policy, 55, 261, 10.1016/j.enpol.2012.12.006 Alhamwi, 2017, OpenStreetMap data in modelling the urban energy infrastructure: a first assessment and analysis Gao, 2019, Travel behavior analysis using 2016 Qingdao's household traffic surveys and Baidu electric map API data, Adv. Transp., 2019, 1 Liu, 2018, Design and implementation of emergency and evacuation system based on Baidu map API ISO 14825-2004, 2004 Zou, 2018, Device-free occupancy detection and crowd counting in smart buildings with WiFi-enabled IoT, Energy Build., 174, 309, 10.1016/j.enbuild.2018.06.040 MOHURD, 2012 Dogan, 2017, An algorithm for abstracted rapid multi-zone urban building energy model generation and simulation, Energy Build., 140, 140, 10.1016/j.enbuild.2017.01.030