Energy resilience can be reached with a secure, sustainable, competitive, and affordable system. In order to achieve energy resilience in the urban environment, urban-scale energy models play a key role in supporting the promotion and identification of effective energy-efficient and low-carbon policies pertaining to buildings. In this work, a dynamic urban-scale energy model, based on an energy balance, has been designed to take into account the local climate conditions and morphological urban-scale parameters. The aim is to present an engineering methodology, applied to clusters of buildings, using the available urban databases. This methodology has been calibrated and optimized through an iterative procedure on 102 residential buildings in a district of the city of Turin (Italy). The results of this work show how a place-based dynamic energy balance methodology can also be sufficiently accurate at an urban scale with an average seasonal relative error of 14%. In particular, to achieve this accuracy, the model has been optimized by correcting the typological and geometrical characteristics of the buildings and the typologies of ventilation and heating system; in addition, the indoor temperatures of the buildings—that were initially estimated as constant—have been correlated to the climatic variables. The proposed model can be applied to other cities utilizing the existing databases or, being an engineering model, can be used to assess the impact of climate change or other scenarios.
The energy community is defined as a "cooperative/partnership/non-profit organization of final customers (municipalities, public and private entities, citizens) aimed at achieving energy independence in order to guarantee energy security, low environment impact and affordable energy costs". This work defines a place-based methodology for the dimensioning of energy communities, according to the requirements of the first Italian law on energy communities issued by the Piedmont Region. The aim is to evaluate the correct size and optimal aggregation of municipalities for future energy communities, considering the energy consumptions and the renewable energy sources available in a territory. In particular, with a place-based methodology, the electricity potentially produced by forest and agricultural biomass, waste, wind, solar and hydraulic sources was evaluated, in accordance with regulations and constrains. Thus, a renewable energy sources atlas was implemented to provide a tool for the estimation of energy, environmental and socio-economic performance indexes of the municipalities of the Piedmont Region. In conclusion, considering the energy production, productivity and consumption of each municipality and the requirements of energy communities, a tool to optimally aggregate municipalities for creating energetic communities is described.
Nowadays, energy consumption in buildings is one of the fundamental drivers to control greenhouse gas emissions and environmental impact. In fact, the air quality of urban environments can cause two main phenomena in metropolitan areas: urban heat island and climate changes. The aim of this work is to showcase how different building variables can impact the residential building’s space heating and cooling energy consumption. Buildings energy-related variables can be fundamental viewpoints to improve the energy performance of neighborhoods, especially in future urban planning. This work examines four neighborhoods in the city of Turin (IT): Arquata, Crocetta, Sacchi, and Olympic Village characterized by different morphologies and building typologies. In each neighborhood, residential building was grouped according to orientations and construction periods. A sensitivity analysis was applied by analysing six building variables: infiltration rate, window-to-wall ratio, and windows, walls, roofs, and floor thermal transmittances. The energy consumption for space heating and cooling of residential buildings and local climate conditions were investigated using CitySim Pro tool and ENVI-met. The challenge of this work is to identify the building variables that most influence energy consumption and to understand how to promote high-energy efficiency neighborhoods: the goal is to identify the “ideal” urban form with low consumption and good comfort conditions in outdoor urban environments. The results of this work show a significant connection between the energy consumption and the six analyzed building variables; however, this relationship also depends on the shape and orientation of the neighborhood.
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