CESAR: A bottom-up building stock modelling tool for Switzerland to address sustainable energy transformation strategies

[1]  Stefanie Hellweg,et al.  Assessing Space Heating Demand on a Regional Level: Evaluation of a Bottom�?Up Model in the Scope of a Case Study , 2017 .

[2]  Jan Carmeliet,et al.  Multiobjective optimisation of energy systems and building envelope retrofit in a residential community , 2017 .

[3]  François Maréchal,et al.  City Energy Analyst (CEA): Integrated framework for analysis and optimization of building energy systems in neighborhoods and city districts , 2016 .

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

[5]  Mohammad Heidarinejad,et al.  Effect of urban neighborhoods on the performance of building cooling systems , 2015 .

[6]  Shengwei Wang,et al.  Impacts of cooling load calculation uncertainties on the design optimization of building cooling systems , 2015 .

[7]  Arno Schlueter,et al.  Integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts , 2015 .

[8]  Niklaus Kohler,et al.  Building age as an indicator for energy consumption , 2015 .

[9]  Filip Johnsson,et al.  Building-stock aggregation through archetype buildings: France, Germany, Spain and the UK , 2014 .

[10]  Jan Carmeliet,et al.  Predicting energy consumption of a neighbourhood using building performance simulations , 2014 .

[11]  Jan Carmeliet,et al.  MULTI-OBJECTIVE OPTIMISATION TO SIMULTANEOUSLY ADDRESS ENERGY HUB SIZING AND SCHEDULING USING A LINEAR FORMULATION , 2014 .

[12]  S. Hellweg,et al.  Housing and mobility demands of individual households and their life cycle assessment. , 2013, Environmental science & technology.

[13]  Niko Heeren,et al.  A component based bottom-up building stock model for comprehensive environmental impact assessment and target control , 2013 .

[14]  Volker Coors,et al.  Citygml-based 3d City Model For Energy Diagnostics And Urban Energy Policy Support , 2013, Building Simulation Conference Proceedings.

[15]  Christoph F. Reinhart,et al.  Umi-an Urban Simulation Environment for Building 1 Energy Use , Daylighting and Walkability 2 3 , 2013 .

[16]  Giuliano Dall'O',et al.  A methodology for the energy performance classification of residential building stock on an urban scale , 2012 .

[17]  Niko Heeren,et al.  Energiekonzept 2050 für die Stadt Zürich - Auf dem Weg zur 2000 Watt tauglichen Wärme-Versorgung mit einem räumlich differenzierten Gebäudeparkmodell , 2012 .

[18]  J. Hensen,et al.  Uncertainty analysis in building performance simulation for design support , 2011 .

[19]  Gian Vincenzo Fracastoro,et al.  A methodology for assessing the energy performance of large scale building stocks and possible appli , 2011 .

[20]  Diane Hubbard,et al.  Ventilation, Infiltration and Air Permeability of Traditional UK Dwellings , 2011 .

[21]  Darren Robinson,et al.  CITYSIM simulation: the case study of Alt-Wiedikon, a neighbourhood of Zürich City , 2011 .

[22]  Dejan Mumovic,et al.  A review of bottom-up building stock models for energy consumption in the residential sector , 2010 .

[23]  V. Ismet Ugursal,et al.  Modeling of end-use energy consumption in the residential sector: A review of modeling techniques , 2009 .

[24]  T. Celik,et al.  Increased lung uptake of radioactive tracers for the prediction of left main coronary artery disease: how reliable? , 2009, Journal of cardiology.

[25]  Maria Kolokotroni,et al.  A GIS-based bottom-up space heating demand model of the London domestic stock , 2009 .

[26]  F. Giorgi,et al.  Addressing climate information needs at the regional level: the CORDEX framework , 2009 .

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

[28]  A. Rasheed,et al.  CITYSIM: Comprehensive Micro-Simulation of Resource Flows for Sustainable Urban Planning , 2009 .

[29]  Shem Heiple,et al.  Using building energy simulation and geospatial modeling techniques to determine high resolution building sector energy consumption profiles , 2008 .

[30]  Jn Hacker,et al.  Constructing design weather data for future climates , 2005 .