Statistical Building Energy Model from Data Collection, Place-Based Assessment to Sustainable Scenarios for the City of Milan

Mutani, Guglielmina; Alehasin, Maryam; Usta, Yasemin; Fiermonte, Francesco; Mariano, Angelo

doi:10.3390/su152014921

Cited by 4 publications

(4 citation statements)

References 12 publications

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“…Utilizing GIS, UBEM can effectively integrate archetype data, enabling the comprehensive modeling and description of the EUI of buildings. This approach facilitates the spatial representation of all pertinent information about buildings on an urban scale [42].…”

Section: Literature Reviewmentioning

confidence: 99%

“…In Scotland, 24 archetypes were used to review the "energy efficiency standard for social housing" and to reach zero emissions from heating by 2045 [32]. In Italy, previous studies with archetypeand GIS-based UBEM approaches were applied for the cities of Turin [48] and Milan [42]. GIS-based UBEM allows for scaling up characteristics, energy-uses and energy savings of buildings to the urban scale, considering also urban features such as the socio-economic conditions of population and the building density of the built environment.…”

Section: Literature Reviewmentioning

confidence: 99%

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Urban Building Energy Modeling to Support Climate-Sensitive Planning in the Suburban Areas of Santiago de Chile

Mutani,

Alehasin,

Yang

et al. 2024

Buildings

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Greenhouse gas emissions depend on natural and anthropic phenomena; however, to reduce emissions, we can only intervene in terms of anthropic causes. Human activity is very different in various countries and cities. This is mainly due to differences in the type of urban environment, climatic conditions, socioeconomic context, government stability, and other aspects. Urban building energy modeling (UBEM), with a GIS-based approach, allows the evaluation of all the specific characteristics of buildings, population, and urban context that can describe energy use and its spatial distribution within a city. In this paper, a UBEM is developed using the characteristics and consumption of eight typical buildings (archetypes) in the climate zone of Santiago de Chile. The archetype-based UBEM is then applied to the commune of Renca, a critical suburb of Santiago, with the use of QGIS to analyze the energy demand for space heating and the potential for energy saving after four retrofitting interventions. Knowing the costs of the retrofitting interventions and the energy price, the simple payback time was evaluated with the reduction in GHG emissions. Starting from the actual building stock, the results show that the most effective retrofitting intervention for the commune of Renca is the thermal insulation of walls and roofs; due to the type of dwellings, this particular intervention could be more convenient if associated with the installation of solar technologies. This methodology can be replicated with the data used by urban planners and public administrations available for many Chilean cities and in other countries.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Urban Building Energy Modeling to Support Climate-Sensitive Planning in the Suburban Areas of Santiago de Chile

Mutani,

Alehasin,

Yang

et al. 2024

Buildings

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“…A more recent study by Mutani et al (2023) used urban building energy modeling (UBEM) to analyze the production from PV panels using the open-source software Quantum Geographic Information System (QGIS). The presented approach allows the evaluation of spatial distribution of energy consumption and production in urban areas, which is essential to realize smart cities.…”

Section: Research Backgroundmentioning

confidence: 99%

Modeling and mapping solar energy production with photovoltaic panels on Politecnico di Torino university campus

Usta,

Carioni,

Mutani

2024

Energy Efficiency

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Educational institutions have significant impacts on the society and environment they are inhabiting, and they can have a big role in influencing various development fields, including sustainability. The environmental sustainability of universities was critically analyzed recently. These bodies can contribute to the sustainability of cities due to their social role in shaping the future generations. The aim of this work is to analyze Urban Building Energy Modeling with a place-based approach using the open-source software QGIS in predicting energy production with photovoltaic solar technologies on the rooftops of the central university campus of Politecnico di Torino. This modeling can help in assessing the energy security and affordability of current and future sustainable scenarios considering their impact on climate change. This study evaluates the accuracy of urban scale QGIS-based energy modeling with a comparison of measured data available from the monitoring activity of LivingLab of Politecnico di Torino, the free tool PVGIS, and the web tools of ENEA. The QGIS modeling accuracy depends on the different precisions of the Digital Surface Model used to describe the built environment (i.e., 1 m or 5 m) and the climate input data (monthly and annual diffuse-to-global radiation and Linke turbidity factor). Moreover, this assessment can be used to map the results of new photovoltaic systems improving the energy and environmental performance of university campuses. The results of this work shed light on the significance of different input data for energy simulation tools at neighborhood-urban scale. The result shown accuracies in PV production of 10 to 37% with different spatial resolutions of the 3D built environment and of 14 to 15.2% for temporal resolution of solar irradiation variables.

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“…Furthermore, a recent study in Borlänge and Uppsala (Sweden) [36] implemented the automation of a UBEM based on open data, using available energy certificates for the purposes of calibration and validation. Additional research on the city of Milan employed the open-source software QGIS version 3.28.8 to model and calculate various energy-related variables in order to predict space heating, domestic hot water consumption, and potential solar production [37].…”

Section: Introductionmentioning

confidence: 99%

Validating ‘GIS-UBEM’—A Residential Open Data-Driven Urban Building Energy Model

García-López,

Sendra,

Domínguez-Amarillo

2024

Sustainability

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The study of energy consumption in buildings, particularly residential ones, brings with it significant socio-economic and environmental implications, as it accounts for approximately 40% of CO2 emissions, 18% in the case of residential buildings, in Europe. On a number of levels, energy consumption serves as a key parameter in urban sustainability indicators and energy plans. Access to data on energy consumption is crucial for energy planning, management, knowledge generation, and awareness. Urban Building Energy Models (UBEMs), which are emerging tools for simulating energy consumption at neighborhood scale, allow for more efficient intervention and energy rehabilitation planning. However, UBEM validation requires reliable reference data, which are often challenging to obtain at urban scale due to privacy concerns and data accessibility issues. Recent advances, such as automation and open data utilization, are proving promising in addressing these challenges. This study aims to provide a standardized UBEM validation process by presenting a case study that was carried out utilizing open data to develop bottom-up engineering models of residential energy demand at urban scale, with a resolution level of individual buildings, and a subsequent adjustment and validation using reference tools. This study confirms that the validated GIS-UBEM model heating and cooling demands and consumption fall within the confidence bands of ±15% and ±12.5%, i.e., the confidence bands required for the approval of official alternative simulation methods for energy certification. This paves the way for its application in urban-scale studies and practices with a well-established margin of confidence, covering a wide range of building typologies, construction models, and climates comparable to those considered in the validation process. The primary application of this model is to determine the starting point and subsequent evaluation of improvement scenarios at a district scale, examining issues such as massive energy rehabilitation interventions, energy planning, demand analysis, vulnerability studies, etc.

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Statistical Building Energy Model from Data Collection, Place-Based Assessment to Sustainable Scenarios for the City of Milan

Cited by 4 publications

References 12 publications

Urban Building Energy Modeling to Support Climate-Sensitive Planning in the Suburban Areas of Santiago de Chile

Urban Building Energy Modeling to Support Climate-Sensitive Planning in the Suburban Areas of Santiago de Chile

Modeling and mapping solar energy production with photovoltaic panels on Politecnico di Torino university campus

Validating ‘GIS-UBEM’—A Residential Open Data-Driven Urban Building Energy Model

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