1,720,987 research outputs found
Urban Building Energy Modeling: an hourly energy balance model of residential buildings at a district scale
Full text linkThe energy consumption of buildings is related to several factors, such as the construction and geometric characteristics, occupancy, climate and microclimate conditions, solar exposure, and urban morphology. However, the interaction between buildings and the surrounding urban context should also be taken into consideration in energy consumption models. The aim of this work has been to create a bottom-up model in order to evaluate the energy balance of residential buildings at an urban scale, starting from the hourly energy consumption data. This modeling approach considers the building characteristics together with urban variables to describe the energy balance of the built environment; it can therefore be used to manage heterogeneous types of data at different scales and it can offer accurate spatial-temporal information on the energy performance of buildings. Detailed heat balance methods can be used at a building scale to estimate heating loads, but this urban-scale simplified model can also be used as a decision tool to support urban design explorations and for policy purposes.
This urban energy consumption model was verified for a case study of a district in Turin, Italy, with the support of a GIS tool, considering hourly energy consumption data of about 50 residential users for two or three consecutive heating seasons. The results show that a simplified model, based on low quality and quantity data, which are typical of an urban scale, can be a powerful tool for the evaluation and spatial representation of the energy needs of buildings at an urban scale
Evaluation to Adapt COMIS to Smoke Movements in Buildings Analysis
No full textPubblicazione interna Dipartimento di Energetica Politecnico di Torino, PT DE FT 33
Urban-Scale Energy Models: the relationship between cooling energy demand and urban form
Full text linkTo 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
Statistical GIS-based analysis of energy consumption for residential buildings in Turin (IT)
Full text linkGreenhouse gas emission is an important issue and the largest source of it is from human activities and from building sectors. Therefore, the building stocks play a key role in the reduction of GHG emissions through the analysis of the energy performance of buildings, in order to understand their behavior and to identify effective models that will allow expanding investigations in vast areas as districts or cities.
This work analyses space heating energy performance of buildings with a multi-scale approach using the main energy related variables at building, block of buildings and district scale. The purpose of this study is to identify a simple regression model in order to evaluate the space heating energy consumption of a large part of residential buildings in Turin (IT). A cluster analysis was applied in order to find groups of buildings with similar energy consumptions and to identify the main energy-related characteristics of each group. The analysis was developed with the support of a GIS tool to evaluate the buildings characteristics and a statistical software to identify a stable model at urban scale. The identified models evidenced that the space heating energy consumption not only depends on the characteristics of the building itself, but also on the urban characteristics. At urban scale, the most influential variables were: the heating degree days, positively correlated with the space heating consumption, and the albedo that was negatively correlated. Also, socio-economic variables were utilized: the percentage of working people with a positive correlation and the percentage of young inhabitants with a negative correlation. The statistical GIS-based methodology proposed in this study is simple and then replicable to other urban contexts. This kind of analysis can be useful for policy makers in defining specific energy efficiency measures for each group of buildings to identify new more effective energy performance variables and benchmarks for the different groups of buildings and then to improve the energy performance of a city reducing energy consumptions and the relative GHG emissions
Preliminary investigation on thermal behavior of vehicles in different climate conditions
Full text linkThe objective of this paper is to provide an initial estimate, albeit rough, about the possible energy savings that can be achieved by reducing the use of the air condition system in cars. A simplified numerical model of the car has been created to predict the cabin temperature in different climatic conditions.
In order to reduce the thermal load and so the temperature inside the cabin several different types of glazing have been considered, characterized by different absorbance coefficients and solar factors. Furthermore, two types of coatings with different absorbance coefficients were examined for the envelope. The paper describe
Self-Sufficiency Building Energy Modelling from Urban to Block-Scale with PV Technology
No full textDecarbonisation policies are often implemented in cities through the promotion of rooftop solar resources. However, urban solar assessments need to identify favourable locations and appropriate sizing to effectively support these strategies. This research aims to estimate the potential for photovoltaic (PV) systems in a dense urban context, as a basis for future policy support. The downtown district of Toronto, Ontario (Canada) is examined as a case study using the 2030 online platform. This work adopts a multi-scalar methodology to model the potential of roof-mounted PV systems for the main residential archetypes. An urban-scale GIS-LiDAR assessment, informed by environmental criteria, is followed by a block-level optimization using URBANopt, which considers energy and economic parameters. The rooftop GIS-based analysis estimates that up to 20% of electricity consumption for detached houses could be satisfied, primarily in the summer, and 5% for apartment buildings. Optimization with URBANopt shows that solar collective configurations can provide significant benefits to users, primarily in terms of economics. When optimization is performed by clusters for each block, the benefits over single-building analysis are evident, particularly in reducing lifecycle costs. In the selected case study, polycrystalline panels with net metering can achieve self-sufficiency levels ranging from 18% to 41% for residential blocks. This study confirms that solar PV systems can increase local production, reduce grid energy dependency, and support energy communities
Data-driven urban building energy models for the platform of Toronto
No full textIncreasing building efficiency is a key topic in territorial policies at different scales, for which new pathways and actions are progressively introduced. However, the evaluation of building consumptions according to energy features and urban and socio-economic variables is crucial to better assess building efficiency measures. This study presents a place-based statistical model for the evaluation of energy demand at the building scale, starting from disaggregating consumption values at the block level. The case study is the central district of Toronto (Ontario, Canada), part of the 2030 Toronto Platform. The existing interactive tool shows energy data only at the block scale, limiting specific evaluations and benchmarking. Therefore, the analysis presents a set of statistical models for assessing residential building consumption by archetypes. The aim of this study is to extend the application and visualisation of the energy demand of the whole city by GIS software. The statistical models underline more reliable results for electricity use, distinguished by appliances and space cooling. Low-rise apartments are the most challenging category to be assessed for appliance use. The variability of natural gas consumption does not allow to build only one model and values for apartment buildings are more variable for different construction ages
Toward Improved Urban Building Energy Modeling Using a Place-Based Approach
No full textUrban building energy models present a valuable tool for promoting energy efficiency in building design and control, as well as for managing urban energy systems. However, the current models often overlook the importance of site-specific characteristics, as well as the spatial attributes and variations within a specific area of a city. This methodological paper moves beyond state-of-the-art urban building energy modeling and urban-scale energy models by incorporating an improved place-based approach to address this research gap. This approach allows for a more in-depth understanding of the interactions behind spatial patterns and an increase in the number and quality of energy-related variables. The paper outlines a detailed description of the steps required to create urban energy models and presents sample application results for each model. The pre-modeling phase is highlighted as a critical step in which the geo-database used to create the models is collected, corrected, and integrated. We also discuss the use of spatial auto-correlation within the geo-database, which introduces new spatial-temporal relationships that describe the territorial clusters of complex urban environment systems. This study identifies and redefines three primary types of urban energy modeling, including process-driven, data-driven, and hybrid models, in the context of place-based approaches. The challenges associated with each type are highlighted, with emphasis on data requirements and availability concerns. The study concludes that a place-based approach is crucial to achieving energy self-sufficiency in districts or cities in urban-scale building energy-modeling studies
Feasibility analysis of integrating solar thermal technologies into district heating network with urban building energy modeling
Full text linkThe aim of this work is to study the effects of utilizing cleaner technologies in district heating networks and assess their contribution to the energy transition within densely populated urban areas. In this context, this study presents a methodology using Urban Building Energy Modeling (UBEM) with a place-based approach to assess the potential of integrating solar thermal collectors for space heating and hot water production services. Moreover, it compares their feasibility with photovoltaic panels. The proposed methodology can be applied to various urban contexts with different climate conditions using an open-source tool and available databases. The methodology adopts a bottom-up approach with a building as the territorial unit, and it takes into account site specific climate condition, building characteristics, urban features, and local constraints. The key step presented in this work is a detailed roof segmentation method used to evaluate the available areas on different roof orientations. The results show an increase in self-consumption and self-sufficiency levels when solar production is utilized for multiple energy services compared to a single service. This increase is three-fold in self-consumption index when hot water is added to the space heating service (a rise from 10% to 31%), and double for self-efficiency index, that is, from 12 to 24%. By using energetic, economic and social indicators, this study contributes in defining target indicators and indexes, while considering local constrains, to achieve the overarching goal of sustainability in energy system. This is aligned with the efforts that are being made to create sustainable cities through collective actions
Fire safety performance based approach applied to La Fenice Theatre in Venice (Italy)
No full textPubblicazione Interna del Dipartimento di Energetica del Politecnico di Torino, n. PT DE 480/F
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