Urban scale is now considered as one of the most relevant scales to face energy and climate challenges. Specific needs for knowledge, decision making tools and evaluation are identified at urban scale. Modelling energy demand from residential buildings is one key aspect, priorto energy retrofitting of existing building asset or to valorisation of local energy sources. Diversity of local contexts, stake holder goals and data availability lead to search flexible models, with ability to produce information for different applications, from alternative input data sets, combining different types of basic models (namely both physical and statistical ones), according to user needs. The present work is exploring the potential of bottom-up approaches, based on engineering models, developed originally for isolated buildings. These models are extrapolated for the complete set of buildings in a city or neighbourhood, based on building archetypes. Two key questions tackled are the selection of suitable archetypes and the reconstitution of relevant input data, statistically representative for the area of interest Sensitivity analysis techniques have been applied to a thermal simulation programme (ESP-r), particularly the Morris elementary effects method. A non-linear response of the model has been emphasized, caused by scattering of input parameters and interaction effects. The most influencing and interacting parameters have been identified. They concern the buildings themselves, their environment and the inhabitants. Data collection or statistical reconstitution must be concentrated in priority to these main parameters. A model of the heat demand at a neighbourhood scale has been developed and tested on the sector St-Félix in Nantes. It is called MEDUS (Modelling Energy Demand at Urban Scale). Application is based on three building archetypes. Census data (INSEE) available at the sector scale are the main input data. Results are analyzed both to check archetype relevancy and to study a possible application for evaluating actions at sector scale, such as energy retrofitting.
