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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.

Reviewed assessment methods for the urban environment • Critically analysed papers working on urban climate and energy demand, outdoor thermal comfort and the urban energy systems. • Demonstrated the links between the processes • An integrated workflow is proposed for assessment of the urban environment. AbstractThe current climate change is calling for a drastic reduction of energy demand as well as of greenhouse gases. Besides this, cities also need to adapt to face the challenges related to climate change. Cities, with their complex urban texture and fabric, can be represented as a diverse ecosystem that does not have a clear and defined boundary. Multiple software tools that have been developed, in recent years, for assessment of urban climate, building energy demand, the outdoor thermal comfort and the energy systems. In this review, we, however, noted that these tools often address only one or two of these urban planning aspects. There is nonetheless an intricate link between them. For instance, the outdoor comfort assessment has shown that there is a strong link between biometeorology and architecture and urban climate. Additionally, to address the challenges of the energy transition, there will be a convergence of the energy needs in the future with an energy nexus regrouping the energy demand of urban areas. It is also highlighted that the uncertainty related to future climatic data makes urban adaptation and mitigation strategies complex to implement and to design given the lack of a comprehensive framework. We thus conclude by suggesting the need for a holistic interface to take into account this multi-dimensional problem. With the help of such a platform, a positive loop in urban design can be initiated leading to the development of low carbon cities and/or with the use of blue and green infrastructure to have a positive impact on the mitigation and adaptation strategies.

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Rapid growth of cities, concerns on global warming and depletion of fossil fuel resources call for sustainable energy solutions for cities. Distributed energy systems such as energy hubs offer promising solutions in this context. Evaluating the energy demand at urban scale is vital to support the design of energy hubs. However, most of the recent studies are based on bottom-up models and do not consider the energy demand in detail. More specifically, the influence of the urban climate on urban energy demand has not been considered so far in the energy system design process. In order to address this research gap, a novel computational platform is developed in the first part of this study, combining an urban climate model with a building simulation tool and an energy system optimization model. The second part of the manuscript is devoted to quantifying the impact of urban climate on energy system design and assessing the consequences of neglecting this specific aspect on energy system performance. Three case studies are conducted considering three building densities for the city of Nablus (building density at the periphery, center and future center of the city) in Palestine. Three scenarios representing 1) standalone buildings (present practice) 2) shadowing and longwave reflection (radiation heat transfer from the walls and the roofs of the buildings to the urban climate and to the sky) of neighboring buildings and 3) urban climate are considered for each case study when computing the energy demand. Subsequently, the energy system is optimized considering Net Present Value (NPV) and system autonomy level as the objective functions (Pareto optimization). The results of the study reveal that the urban climate has a notable impact on the energy demand and energy system design. More importantly, it is shown that the influence of urban climate results in higher fluctuations in the energy demand, which in turn results in a notable increase in the NPV (by up to 40%). This further magnifies the increase in annual or peak demand. The study reveals that neglecting the influence of urban climate in the energy system design process can result in a performance gap in NPV, grid integration level, and greenhouse gas emissions and can impose reliability issues. The design tool introduced in this study can be used for urban planning to mitigate the aforementioned adverse effects.