Urban-Scale Energy Models: the relationship between cooling energy demand and urban form

Abstract

To enhance the quality of life in cities, it is necessary to improve the energy performance of buildings together with a sustainable urban planning especially in high-density contexts. Previous works investigated the building shape, the urban morphology, and the local climate conditions to optimize the energy performance for space heating of buildings. The aim of this study is to validate a GIS-based engineering model to simulate the hourly energy demand for space cooling in residential buildings at neighborhood scale and to assess the relationship between the urban form and the energy performance in terms of cooling energy demand. A place- based methodology was applied to six neighborhoods in the city of Turin (Italy), identified as homogeneous zones with different building characteristics and urban contexts. The hourly cooling demand of residential buildings was studied starting from the energy balance at building scale, and then was applied at block of buildings scale with the support of GIS. This model was validated with a comparison of the results using CitySim tool and ISO 52016 assessment. In order to investigate the relationship between cooling energy demand and urban form, the GIS- based engineering model was applied to five typical blocks of buildings with different construction periods. The results show how cooling energy demand varies according to building characteristics and urban morphology in a continental-temperate climate. By this analysis, it is possible to identify the optimal block of building shape in Turin ensuring lower energy consumptions during the cooling season with different types of buildings.

GIS for the Potential Application of Renewable Energy in Buildings towards Net Zero: A Perspective

“…Meanwhile, the potential of renewable energy applications, building envelope retrofitting, and urban energy balance is assessed to provide key information for energy design and planning [40]. Energy simulation at the city level has been developed many years ago, and some up-scaling Urban Building Energy Models (UBEM) already exist, such as the City Building Energy Saver (CtiyBES) developed by the Lawrence Berkeley National Laboratory, the Urban Modeling Interface (UMI) developed by the MIT Sustainable Design Lab, CitySim, Simstadt, City Fast Fluid Dynamics (City FFD), and city-related 3D geospatial data in an XML-based format (CityGML) [43,44]. Generally, there are two types of UBEM, including aggregated archetype and data-driven/physical-based models.…”

Exploiting geographic open data to improve urban building energy simulations: The Padova city center case study

“…For instance, a study [8] evaluated urbanscale building energy-use models using CityGML models, which employ standardized geometrical formats and geographical information systems (GIS). An urban energy atlas for the Turin building stock has been created using a GIS, enhancing the energy-use model for urban areas of different dimensions [9]. Sun highlighted the need for multilevel semantic modelling of urban building space based on geometric characteristics in 3D environments to meet the increasing demands of precise urban form recognition and space management [10].…”

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“…Another important aspect of this work is the importance of the renewable energy communities; the energy sharing permit to reach the energy independence [21], reduce emissions [22] and improve the equity of energy systems [23]. Families and small commercial activities can install photovoltaic or other renewable systems not only for own consumption, but with an idea of sharing the energy with the collectivity; with this approach the installed power on a single roof or, in general, of a single small renewable power plant is like a part of a large collective plant, participating and increasing in the distributed energy generation network.…”