A holistic framework to utilize natural ventilation to optimize energy performance of residential high-rise buildings

Abstract A novel holistic framework was established using Building Information Modelling (BIM) to estimate accurately the potential of natural ventilation of residential high-rise buildings. This framework integrates Computational Fluid Dynamics (CFD) simulation, multi-zone-air-flow modelling, and Building Energy Simulation (BES) to calculate ventilation rates under the mechanisms of wind-, buoyancy- and wind and buoyancy-driven ventilation. The framework was applied to a 40-storey residential building in Hong Kong for estimating the potential of natural ventilation in residential high-rise buildings. The results show that the building can save up to 25% of the electricity consumption if the building employs wind-driven natural ventilation instead of mechanical ventilation. The electricity consumption can be further reduced up to 45% by facilitating the buoyancy-driven natural ventilation. However, natural ventilation is found to be effective only if the temperature difference between indoor and outdoor is less than 2 °C. The study suggests to orienting residential high-rise buildings at an oblique angle with the prevalent wind direction than positioning perpendicular to the prevalent wind direction. Furthermore, the framework recommends promoting the wind-driven natural ventilation at top floors of residential high-rise buildings and to facilitate wind and buoyancy-driven natural ventilation at middle and lower floors of the buildings.

[1]  M G Apte,et al.  Indoor air quality, ventilation and health symptoms in schools: an analysis of existing information. , 2003, Indoor air.

[2]  Nuno R. Martins,et al.  Validation of numerical simulation tools for wind-driven natural ventilation design , 2016 .

[3]  Ursula Eicker,et al.  Controlled natural ventilation for energy efficient buildings , 2013 .

[4]  Alberto Hernandez Neto,et al.  Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption , 2008 .

[5]  Kelvin K. W. Yau,et al.  A study of domestic energy usage patterns in Hong Kong , 2003 .

[6]  John Burnett,et al.  Assessment of Envelope Energy Performance in HK-BEAM for Residential Buildings , 2000 .

[7]  Yoshihide Tominaga,et al.  Numerical simulation of dispersion around an isolated cubic building: Comparison of various types of k–ɛ models , 2009 .

[8]  Leon R. Glicksman,et al.  Application of integrating multi-zone model with CFD simulation to natural ventilation prediction , 2005 .

[9]  Fariborz Haghighat,et al.  A Comprehensive Validation of Two Airflow Models — COMIS and CONTAM , 1996 .

[10]  C.-F. Gao,et al.  Evaluating the influence of openings configuration on natural ventilation performance of residential , 2011 .

[11]  J. C. Lam.  A survey of electricity consumption and user behaviour in some government staff quarters , 1993 .

[12]  Hashem Akbari,et al.  Integrated and multi-hour optimization of office building energy consumption and expenditure , 2014 .

[13]  Chia-Hung Yeh,et al.  Analysis of building energy consumption parameters and energy savings measurement and verification by applying eQUEST software , 2013 .

[14]  Francis W.H. Yik,et al.  Energy Saving by Utilizing Natural Ventilation in Public Housing in Hong Kong , 2010 .

[15]  Jan Sundell,et al.  Associations between type of ventilation and air flow rates in office buildings and the risk of SBS-symptoms among occupants , 1994 .

[16]  Cheuk Ming Mak,et al.  Modeling of coupled urban wind flow and indoor air flow on a high-density near-wall mesh: Sensitivity analyses and case study for single-sided ventilation , 2014, Environ. Model. Softw..

[17]  S C Lee,et al.  Indoor and outdoor air quality investigation at schools in Hong Kong. , 2000, Chemosphere.

[18]  John Burnett BEng PhD CEng R.P.E. Fiee Fcibse,et al.  Framework of Building Environmental Assessment Methods , 2013 .

[19]  Steven J. Emmerich,et al.  Integration of Airflow and Energy Simulation Using CONTAM and TRNSYS | NIST , 2003 .

[20]  Arno Schlueter,et al.  Building information model based energy/exergy performance assessment in early design stages , 2009 .

[21]  K. Newcombe,et al.  Energy use in Hong Kong: Part II, sector end-use analysis , 1975 .

[22]  Nyuk Hien Wong,et al.  COMPARATIVE STUDY OF THE INDOOR AIR QUALITY OF NATURALLY VENTILATED AND AIR-CONDITIONED BEDROOMS OF RESIDENTIAL BUILDINGS IN SINGAPORE , 2004 .

[23]  S. Orszag,et al.  Renormalization group analysis of turbulence. I. Basic theory , 1986 .

[24]  James Mitchell,et al.  Intelligent Sustainable Design: Integration of Carbon Accounting and Building Information Modeling , 2011 .

[25]  Peng Ren,et al.  Analysis of energy efficiency retrofit scheme for hotel buildings using eQuest software: A case study from Tianjin, China , 2015 .

[26]  A. R. Escombe,et al.  Natural Ventilation for the Prevention of Airborne Contagion , 2007, PLoS medicine.

[27]  Shuncheng Lee,et al.  Investigation of indoor air quality at residential homes in Hong Kong - Case study , 2002 .

[28]  Matthias Haase,et al.  An investigation of the potential for natural ventilation and building orientation to achieve thermal comfort in warm and humid climates , 2009 .

[29]  Jane Matthews,et al.  Incorporating embodied energy in the BIM process , 2012 .

[30]  Joseph Andrew Clarke,et al.  Using results from field surveys to predict the effect of open windows on thermal comfort and energy use in buildings , 2007 .

[31]  C A Pickering,et al.  The sick building syndrome: prevalence studies. , 1984, British medical journal.

[32]  Brian J. Polidoro,et al.  CONTAM User Guide and Program Documentation Version 3.2 , 2015 .

[33]  J. Niu,et al.  Air infiltration induced inter-unit dispersion and infectious risk assessment in a high-rise residential building , 2017, Building Simulation.

[34]  Hema Sree Rallapalli.  A Comparison of Energy Plus and eQUEST Whole Building Energy Simulation Results for a Medium Sized Office Building , 2010 .

[35]  K.S.Y. Wan,et al.  Representative building design and internal load patterns for modelling energy use in residential buildings in Hong Kong , 2004 .

[36]  L. T. Wong,et al.  Electricity energy trends in Hong Kong residential housing environment , 2014 .

[37]  Qingyan Chen,et al.  Using CFD Capabilities of CONTAM 3.0 for Simulating Airflow and Contaminant Transport in and around Buildings , 2010 .

[38]  Francis W.H. Yik,et al.  Building design and energy end-use characteristics of high-rise residential buildings in Hong Kong , 2004 .

[39]  Joseph C. Lam.  An analysis of residential sector energy use in Hong Kong , 1996 .

[40]  Simi Hoque,et al.  Envelope retrofit analysis using eQUEST, IESVE Revit Plug-in and Green Building Studio: a university dormitory case study , 2015 .

[41]  Mani Golparvar-Fard,et al.  Monitoring and Visualization of Building Construction Embodied Carbon Footprint Using DnAR-N-Dimensional Augmented Reality Models , 2012 .

[42]  Peter Hills,et al.  Household energy transition in Hong Kong , 1994 .

[43]  Qingyan Chen,et al.  A new empirical model for predicting single-sided, wind-driven natural ventilation in buildings , 2012 .

[44]  Bje Bert Blocken,et al.  CFD simulation of cross-ventilation for a generic isolated building : impact of computational parameters , 2012 .

[45]  Mohamed B. Gadi,et al.  A comparison between CFD and Network models for predicting wind-driven ventilation in buildings , 2007 .

[46]  Kenny C. S Kwok,et al.  Evaluation of RANS turbulence models for simulating wind-induced mean pressures and dispersions around a complex-shaped high-rise building , 2013 .

[47]  Tetsuro Tamura,et al.  AIJ guide for numerical prediction of wind loads on buildings , 2006 .

[48]  Chun-Ho Liu,et al.  CFD simulations of natural ventilation behaviour in high-rise buildings in regular and staggered arr , 2011 .

[49]  Z T Ai,et al.  Numerical investigation of wind-induced airflow and interunit dispersion characteristics in multistory residential buildings. , 2013, Indoor air.

[50]  Elie Azar,et al.  A comprehensive analysis of the impact of occupancy parameters in energy simulation of office buildings , 2012 .

[51]  D. Prakash,et al.  Analysis of thermal comfort and indoor air flow characteristics for a residential building room under generalized window opening position at the adjacent walls , 2015 .

[52]  Jack C. P. Cheng,et al.  Holistic BIM framework for sustainable low carbon design of high-rise buildings , 2018, Journal of Cleaner Production.