Influence of context-sensitive urban and architectural design factors on the energy demand of buildings in Toulouse, France

Abstract This research aims to identify the statistical sensitivity of multi-scale urban design factors regarding buildings’ energy demand located in three districts in the city of Toulouse, France. The research method is composed of four main steps: (a) three typical urban blocks of Toulouse are parametrized, considering factors ranging from the urban form to the building material scales; (b) a fractional factorial sampling method is applied which allows elaborating statistically representative and non-redundant scenarios from all design variables and for each specific urban district; (c) the urban energy models generated are interactively assessed regarding the annual buildings’ heating and cooling loads for the temperate climate context of Toulouse, France; (d) through a global sensitivity analysis, results obtained are estimated through a statistic hypothesis test, which allows identifying the influence of the design variables on each energy response of interest. Results show that urban multi-scale design variables may have divergent influence on the same energy response when the urban form context changes. For traditional urban compact blocks, two less current urban form factors considered in this study (the courtyard aspect ratio and the standard-deviation of the built height) account for almost 50% of the overall impact on heating demand of buildings while building and envelope scale factors, such as glazing window properties, have more influence for pavilions and slabs urban blocks. The relevance of certain factors was strongly linked to their typologies or to their urban environment.

[1]  Klaus Hinkelmann,et al.  Design and Analysis of Experiment , 1975 .

[2]  Wei Tian,et al.  A review of sensitivity analysis methods in building energy analysis , 2013 .

[3]  K. Steemers.  Energy and the city: density, buildings and transport , 2003 .

[4]  Jan Carmeliet,et al.  Comparative assessment of various heat island mitigation measures , 2014 .

[5]  H. Mayer,et al.  Numerical study on the effects of aspect ratio and orientation of an urban street canyon on outdoor thermal comfort in hot and dry climate , 2006 .

[6]  Michele A. L. Martins,et al.  Sensitivity analysis of urban morphology factors regarding solar energy potential of buildings in a Brazilian tropical context , 2016 .

[7]  Enes Yasa,et al.  Evaluation of the effects of courtyard building shapes on solar heat gains and energy efficiency according to different climatic regions , 2014 .

[8]  Mohamed B. Gadi,et al.  Effect of courtyard proportions on solar heat gain and energy requirement in the temperate climate of Rome , 2006 .

[9]  M. Batty.  The Size, Scale, and Shape of Cities , 2008, Science.

[10]  Christian Anker Hviid,et al.  A simple tool to evaluate the effect of the urban canyon on daylight level and energy demand in the early stages of building design , 2014 .

[11]  Jan Hensen,et al.  Building Performance Simulation for Design and Operation , 2019 .

[12]  H. Takebayashi,et al.  Study to examine the potential for solar energy utilization based on the relationship between urban morphology and solar radiation gain on building rooftops and wall surfaces , 2015 .

[13]  Joseph C. Lam,et al.  Sensitivity analysis of energy performance of office buildings , 1996 .

[14]  Peter Andreas Sattrup,et al.  The urban canyon and building energy use: Urban density versus daylight and passive solar gains , 2011 .

[15]  A. Act,et al.  DOE sensitivity analysis of urban morphology factors regarding solar irradiation on buildings envelope in the Brazilian tropical context , 2014 .

[16]  Nedyomukti Imam Syafii,et al.  Evaluation of the impact of the surrounding urban morphology on building energy consumption , 2011 .

[17]  Aristotelis Vartholomaios,et al.  A parametric sensitivity analysis of the influence of urban form on domestic energy consumption for heating and cooling in a Mediterranean city , 2017 .

[18]  Kevin J. Lomas,et al.  Sensitivity analysis techniques for building thermal simulation programs , 1992 .

[19]  Darren Robinson.  Computer Modelling for Sustainable Urban Design , 2011 .

[20]  K. Steemers,et al.  Solar energy and urban morphology: Scenarios for increasing the renewable energy potential of neighbourhoods in London , 2015 .

[21]  Christoph F. Reinhart,et al.  Urban building energy modeling – A review of a nascent field , 2015 .

[22]  J. S. Hunter,et al.  Statistics for experimenters : an introduction to design, data analysis, and model building , 1979 .

[23]  Peter Droege,et al.  The Renewable City: A comprehensive guide to an urban revolution , 2007 .

[24]  T. Martins,et al.  From solar constraints to urban design opportunities: Optimization of built form typologies in a Brazilian tropical city , 2014 .

[25]  S. Ranji Ranjithan,et al.  Multivariate regression as an energy assessment tool in early building design , 2012 .

[26]  M. Grosso.  Urban form and renewable energy potential , 1998 .

[27]  Denton E. Morrison,et al.  The Significance Test Controversy , 1972 .

[28]  Jlm Jan Hensen,et al.  Uncertainty analysis in building performance simulation for design support , 2011 .

[29]  Y. Shimoda,et al.  Residential end-use energy simulation at city scale , 2004 .

[30]  Jérôme Henri Kämpf,et al.  A verification of CitySim results using the BESTEST and monitored consumption values , 2015 .

[31]  Koen Steemers,et al.  Building form and environmental performance: archetypes, analysis and an arid climate , 2003 .

[32]  Svend Svendsen,et al.  Method and simulation program informed decisions in the early stages of building design , 2010 .

[33]  Stefan Lechtenböhmer,et al.  The potential for large-scale savings from insulating residential buildings in the EU , 2011 .

[34]  B. Sajadi,et al.  Sensitivity analysis of building energy performance: A simulation-based approach using OFAT and variance-based sensitivity analysis methods , 2018 .

[35]  K. Steemers,et al.  Urban Form, Density and Solar Potential , 2006 .

[36]  A. Rasheed,et al.  From the neighbourhood to the city : resource flow modelling for urban sustainability , 2009 .

[37]  R. A. Fisher,et al.  Design of Experiments , 1936 .

[38]  R. Judkoff,et al.  International Energy Agency building energy simulation test (BESTEST) and diagnostic method , 1995 .

[39]  Sukumar Natarajan,et al.  Developing a database of energy use for historic dwellings in Bath, UK , 2012 .

[40]  Laura Bellia,et al.  Effects of solar shading devices on energy requirements of standalone office buildings for Italian climates , 2013 .

[41]  Stig-Inge Gustafsson,et al.  Sensitivity analysis of building energy retrofits , 1998 .

[42]  Fazia Ali-Toudert,et al.  Effects of asymmetry, galleries, overhanging façades and vegetation on thermal comfort in urban street canyons , 2007 .

[43]  Nicole M. Miller.  Urban form and building energy : quantifying relationships using a multi-scale approach , 2013 .

[44]  A. Saltelli,et al.  Sensitivity analysis: Could better methods be used? , 1999 .

[45]  Marjorie Musy,et al.  Microclimatic coupling as a solution to improve building energy simulation in an urban context , 2011 .

[46]  Marjorie Musy,et al.  Simulation tools to assess microclimate and building energy – A case study on the design of a new district , 2016 .

[47]  T. Oke.  Street design and urban canopy layer climate , 1988 .

[48]  Luc Adolphe,et al.  A Simplified Model of Urban Morphology: Application to an Analysis of the Environmental Performance of Cities , 2001 .

[49]  H. Taha.  Urban climates and heat islands: albedo, evapotranspiration, and anthropogenic heat , 1997 .

[50]  Steven K. Firth,et al.  INVESTIGATING CO 2 EMISSION REDUCTIONS IN EXISTING URBAN HOUSING USING A COMMUNITY DOMESTIC ENERGY MODEL , 2009 .

[51]  A. Holtslag,et al.  Seasonal dependence of the urban heat island on the street canyon aspect ratio , 2014 .

[52]  A. Saltelli,et al.  Update 1 of: Sensitivity analysis for chemical models. , 2012, Chemical reviews.

[53]  Marion Bonhomme,et al.  "MultipliCities": multi-scale energy modelling of urbain archetype buildings, case-study in Toulouse , 2017 .

[54]  Douglas H. Johnson.  The Insignificance of Statistical Significance Testing , 1999 .

[55]  Luc Adolphe.  SAGACités. Vers un Système d’Aide à la Gestion des Ambiances urbaines , 2006 .

[56]  Ferdinando Salata,et al.  How high albedo and traditional buildings’ materials and vegetation affect the quality of urban microclimate. A case study , 2015 .