An Integrated Microclimate-Energy Demand Simulation Method for the Assessment of Urban Districts

Rapid urbanization and densification processes are changing microclimatic environments in cities around the world. Even though previous studies have demonstrated the impact of urban microclimate on space cooling and heating demand, modeling tools employed to support the design process largely overlook microclimatic conditions in assessing building energy performance, making use of data from weather stations often located in rural areas. This paper presents a computational approach for the quantitative analysis of building energy demand at the district scale, including interdependent factors such as local air temperature, relative humidity and wind speed, diversity in building geometry and materials. The method, which couples the microclimate model ENVI-met and the district-scale energy simulation tool City Energy Analyst, is applied to a case study in Zurich, Switzerland, in order to analyze the energy performance of the area on a hot summer day. The study contributes to advance a coupling approach between a microclimate simulation and an energy tool at the district scale. The results showed that the coupled assessment approach can deal with complex interactions between geometry, building materials and energy systems. The consideration of local microclimatic conditions led to a 5% increase in the space cooling demand on the selected day, while the simulated peak cooling load for each building was 8% higher on average. The variation in the space cooling demand was found to be mainly due to an increase in latent cooling demand. Moreover, the coupling method allowed a detailed analysis of energy demand variation at the building level showing that, when considering the local climate patterns, the space cooling demand of the individual buildings varied between −5% and +14% on the selected day. The proposed method represents a next step to reflect the mutual interactions between buildings and microclimate in urban districts and aims at supporting decision-making in the design process.