GIS-based urban energy modelling and energy efficiency scenarios using the energy performance certificate database

Abstract

The EU building stock is 97% not energy efficient and the promotion of energy retrofitting strategies is a key way of reducing energy consumptions and greenhouse gas emission. In order to improve the energy performance of buildings, the European Union released the Energy Performance of Buildings and the Energy Efficiency Directives. The certification of the energy performance of a building is a central element of these Directives to monitor and promote energy performance improvements in buildings, with the aim of increasing their energy efficiency level, thereby reducing greenhouse gas emissions. This work evaluates the energy performance of existing residential buildings using the energy performance certificate database and identifies the more effective retrofitting interventions by applying an urban-scale energy model. The novelty of this study is that a new retrofitting database is created to improve the results of a building energy model at urban scale taking into account the real characteristics of the built environment. The here presented GIS-based monthly engineering model is flexible and easily applicable to different contexts, and was used to investigate energy efficiency scenarios by evaluating their effects of city scale. An urban energy atlas was designed for an Italian city, Turin, as a decision-making platform for policy makers and citizens. This energy platform can give information on energy consumption, production and productivity potential, but also on energy retrofitting scenarios. The results of this work show that it is possible to obtain energy savings for space heating of 79,064 MWh/year for the residential buildings connected to the district heating network in the city of Turin; these interventions refer mainly to thermal insulation of buildings envelope with windows replacement and allow a reduction in greenhouse gas emissions of 12,097 tonCO2eq/year.

Impact of the COVID-19 pandemic on the energy performance of residential neighborhoods and their occupancy behavior

“…It is also not feasible to update the input data as thermal capacities and thermal transmittances of the materials. This limitation could reduce the accuracy of the model ( Mutani and Todeschi, 2021 ). To overcome this limitation, a machine learning model was developed to improve the accuracy of the GIS-based engineering model.…”

An Innovative Tool for Optimised Development Envelope Control (Dec) Analysis and Scenario Building in Digital Twin

“…The literature on the solar analysis used the buildings and development envelope to measure the solar irradiation (de Luca, 2017; Lindberg et al, 2015;Zhu et al, 2022Zhu et al, , 2020, solar rights, and solar harvesting (de Luca and Dogan, 2019;de Luca, 2017;Shach-Pinsly and Capeluto, 2020;Stasinopoulos, 2018). Furthermore, the literature suggests that building energy modelling should be analysed in different scales such as urban and neighbourhood levels (Bozonnet et al, 2015;Cheng et al, 2018;Keller et al, 2018;Martín-Consuegra et al, 2018;Mutani et al, 2019;Mutani and Todeschi, 2021;Tooke et al, 2014). One of the critical applications of 3D building/city models is lifcycle assessment (building design, development, implementation, performance, retrofit, and demolish) (de Trocóniz y Revuelta et al, 2013;Elbeltagi et al, 2017;Mastrucci and Rao, 2017;Saroglou et al, 2017;Soust-Verdaguer et al, 2018;Yi, 2015).…”

Modelling & Spatial Mapping of Residential-Sector Emissions for Sub-National & Urban Areas

“…Previous research on residential sector emissions has focused mainly on analyzing building efficiency [ [33] , [34] , [35] ] as opposed to residential sector BEIs. In an Irish context, for the purpose of emissions reporting, residential sector emissions only include the combustion of fuel for domestic space and water heating, while electricity is accounted for upstream at the power plant under ‘energy industries’ [ 36 ].…”