The influence of urban form on the grid integration of renewable energy technologies and distributed energy systems.

Standard and newly designed building blocks for complex urban sites- also designated by urban archetypes - are used in this study to quantify the influence of urban forms on their energy demand and energy systems design. An energy hub, which consists on a multi-carrier energy system involving multiple energy conversion, storage and/or network technologies, is employed to quantify the impact of the urban morphology on the energy system requirements. This study reveals that urban archetypes have a notable influence on the heating and cooling energy demands of city districts that can be characterized using form factors and floor area ratio. However, the influence on demand profiles cannot be assessed based on the aforementioned indicators. The cost of energy systems can increase up to 50% due to the impact of urban forms that are well beyond the increase of peak and/or annual energy demands. In addition, renewable energy integration to the grid as well its utilization in districts is influenced by urban forms. This makes it essential to consider energy system design as a part of the urban planning process moving even beyond building simulation.

Multi-scale modelling to evaluate building energy consumption at the neighbourhood scale.

A new methodology is proposed to couple a meteorological model with a building energy use model. The aim of such a coupling is to improve the boundary conditions of both models with no significant increase in computational time. In the present case, the Canopy Interface Model (CIM) is coupled with CitySim. CitySim provides the geometrical characteristics to CIM, which then calculates a high resolution profile of the meteorological variables. These are in turn used by CitySim to calculate the energy flows in an urban district. We have conducted a series of experiments on the EPFL campus in Lausanne, Switzerland, to show the effectiveness of the coupling strategy. First, measured data from the campus for the year 2015 are used to force CIM and to evaluate its aptitude to reproduce high resolution vertical profiles. Second, we compare the use of local climatic data and data from a meteorological station located outside the urban area, in an evaluation of energy use. In both experiments, we demonstrate the importance of using in building energy software, meteorological variables that account for the urban microclimate. Furthermore, we also show that some building and urban forms are more sensitive to the local environment.