Guglielmina Mutani | Politecnico di Torino (original) (raw)

Papers by Guglielmina Mutani

Atmosphere , 2024

This study evaluates the effectiveness of sustainable urban regeneration projects in mitigating U... more This study evaluates the effectiveness of sustainable urban regeneration projects in mitigating Urban Heat Island (UHI) effects through a place-based approach. Geographic Information Systems (GIS) and satellite imagery were integrated with machine learning (ML) models to analyse the urban environment, human activities, and climate data in Turin, Italy. A detailed analysis of the ex-industrial Teksid area revealed a significant reduction in Surface Urban Heat Island Intensity (SUHII), with decreases of −0.94 in summer and −0.54 in winter following regeneration interventions. Using 17 variables in the Random Forest model, key determinants influencing SUHII were identified, including building density, vegetation cover, and surface albedo. This study quantitatively highlights the impact of increasing green spaces and enhancing surface materials to improve solar reflectivity, with findings showing a 19.46% increase in vegetation and a 3.09% rise in albedo after mitigation efforts. Furthermore, the results demonstrate that integrating Local Climate Zones (LCZs) into urban planning, alongside interventions targeting these key variables, can further optimise UHI mitigation and assess changes. This comprehensive approach provides policymakers with a robust tool to enhance urban resilience and guide sustainable planning strategies in response to climate change.

Energy Efficiency, 2024

This work proposes a new model to evaluate the air changes per hour (ach) due to natural infiltra... more This work proposes a new model to evaluate the air changes per hour (ach) due to natural infiltrations in buildings. This modeling already exists at building scale, but the new model will implement the hourly ventilation load in a physical-based modeling for space heating and cooling in buildings at urban scale. The proposed improvement considers the wind and buoyancy effects in the calculation of hourly achs in a high-density urban context. A three-zone air flow lumped modeling is applied to describe the air flow in buildings; the air flow rate due to infiltrations is calculated depending only on leakages’ characteristics and pressure variations in various climate conditions. The non-linear equations system of mass and energy conservation is solved by an iterative procedure using the Newton-Raphson numerical method. Besides, two different methodologies are compared to evaluate the external dynamic and static pressure conditions on building façades: experimental values (pressure coefficients Cp) and CFD simulations. For the latter, the air flow field in the urban canyons is described by the windy conditions and by imposing a temperature gradient due to solar irradiation between the windward
and leeward facades. This methodology is applied to three urban canyons in Turin, with typical aspect ratios and orientations for some local climate conditions considering both heating and cooling seasons. Comparing the results of hourly ach obtained from the Cp method, the CFD technique allows to modulate the ach considering the impact of the canyon dimension, wind and buoyancy effect of non-isothermal condition, in varying the wind speed on the façades of buildings for different scenarios. t also overcomes the limit of field of applications of Cp, especially in high-density built urban environments. The encouraging results of this work will ead to future developments of the three-zone lumped model and its numerical solution techniques.

Mathematical Modelling of Engineering Problems, 2024

This study investigates the predictive capabilities of process-driven (PD) energy modeling and Ma... more This study investigates the predictive capabilities of process-driven (PD) energy modeling and Machine Learning techniques, specifically Light Gradient Boosting Machine (LGBM) and Random Forest (RF) algorithms, in analyzing building energy consumption patterns. Leveraging a comprehensive dataset encompassing diverse building characteristics, energy-related variables, and operational configurations, the comparative performances of these methodologies is explored. Results reveal that while all approaches demonstrate promising predictive accuracies, LGBM exhibits a slight advantage over RF and the process-driven model. Moreover, the process-driven model showcases efficacy in colder seasons and for buildings of extreme ages, while encountering limitations in accurately modeling energy consumption for structures constructed during 1970s to 1990s. Conversely, Machine Learning models demonstrate consistent performance (with relative errors of 5-10%) across varied building ages, underscoring their adaptability and potential for capturing nuanced energy dynamics. However, a notable constraint lies in the availability of sufficient data for training Machine Learning models, posing challenges for model testing. These findings contribute to advancing our understanding of energy modeling methodologies at urban scale and offer insights for optimizing building energy efficiency strategies for a sustainable development of urban environments.
To download: https://www.iieta.org/journals/mmep/paper/10.18280/mmep.111003

2020 IEEE 3rd International Conference and Workshop in Óbuda on Electrical and Power Engineering (CANDO-EPE), 2020

This work presents a project of hi-tech and supergreen ‘nZEB casale’ in Italy. The ‘nZEB casale’ ... more This work presents a project of hi-tech and supergreen ‘nZEB casale’ in Italy. The ‘nZEB casale’ is located in Matera, in the south of Italy. The project concerns the renovation of a medieval ‘casale’, a group of rural houses for residential use. The shape of the new nZEB is in the style of old light-colored buildings, compact and with projections and shielding elements to reduce the summer thermal loads. The use of local and certified materials for the construction of buildings has resulted in a low environmental impact of buildings and an excellent winter and summer energy performance reaching the best energy class A4. Finally, this work presents an environmental protocol to be applied to nZEBs in order to take into account the other benefits of these constructions, as well as the energy benefits.

12th International Conference on Improving Energy Efficiency in Commercial Buildings and Smart Communities, 2024

Urbanization trends have intensified the focus on predicting building energy consumption within u... more Urbanization trends have intensified the focus on predicting building energy consumption within urban areas for sustainable development. Urban Building Energy Modeling (UBEM) offers a valuable approach to simulating and evaluating building energy efficiency within urban contexts, considering various physical and climatic factors.
This paper explores the application of data-driven UBEM in urban energy planning, with the case study of Turin, Italy. It is due to the fact that traditional physics-based UBEM models face limitations in large-scale urban settings, prompting the adoption of data-driven approaches. The study evaluates the effectiveness of Machine Learning (ML) algorithms, particularly Light Gradient-Boosting Machine (LightGBM) and Random Forest (RF), in predicting energy consumption for space heating at both monthly and hourly time steps.
Using a comprehensive dataset of 44,290 buildings and building blocks and the District Heating Network (DHN) in Turin with 6146 connected buildings, the study demonstrates the superior predictive performance of LightGBM over Random Forest, particularly at the urban scale. In the stable operational months from December 2022 to March 2023, LightGBM showed a maximum relative error of 2% for monthly energy consumption prediction, while RF had a maximum relative error of 9%. For buildings’ hourly energy consumption profile, despite challenges associated with space heating cut-off during a day, both algorithms exhibit robust performance, with relative errors below ±20% for most of the hours. These results highlight the robustness of both ML models in accurately predicting monthly energy consumption, particularly for urban application.
https://publications.jrc.ec.europa.eu/repository/handle/JRC137722

Energy efficiency, 2024

Educational institutions have significant impacts on the society and environment they are inhabit... more 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 neighborhoodurban 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.

Lecture Notes in Civil Engineering, 2024

The construction sector is facing very important economic, environmental, technological, and soci... more The construction sector is facing very important economic, environmental, technological, and social challenges, mainly related to climate change and extreme weather events, excess energy consumption, vulnerability of buildings and consequential damage, overpopulation, intensive urbanization, overuse of resources, social inequalities and energy poverty. Sectoral approaches that consider and value individual building performance (e.g., energy efficiency, sustainability, etc.) and not reciprocal interactions and integrations, are not functional to ensure well-being and comfort for the occupants, functionality and efficiency, performance synergy, decarbonization, and sustainable development of the city. It is well known the importance of moving from the widely prevailing paradigm of considering these dimensions in an almost unrelated way to a new paradigm that deals with a holistic view of building sustainability that integrates all relevant aspects in an efficient and implemented way. This work describes how a holistic approach and effective urban modeling, and tools can be used to ensure the implementation of that all potential synergies through technological options, economic and market instruments and measures and behavioral changes. The interactions between buildings and districts, energy communities, cities, ensuring sharing energy and data to reach a high value of self-consumption and self-sufficiency, will be analyzed. The work demonstrates the real application of the holistic approach in supporting a Renewable Energy Community in the town of Termoli in Molise, as a use case in living lab, taking in account the existing technological, governance and legal barriers.

2023 IEEE 6th International Conference and Workshop Óbuda on Electrical and Power Engineering (CANDO-EPE), 2023

This article delves into the integration of district heating systems into urban planning for sust... more This article delves into the integration of district heating systems into urban planning for sustainable development in regions with moderate to cold climates. The study introduces the Data-driven Urban Energy modeling framework, which aims to bridge the gap between conventional engineering-based energy simulation models and emerging data-driven machine learning (ML) models. By doing so, it provides accurate and comprehensive insights into urban energy demand (ED) patterns. The methodology involves evaluating engineering and ML model's generalization power, revealing its ability to predict energy demand accurately at both building and urban scales. Machine learning algorithms, including LightGBM (LGBM) and Random Forest (RF) regression, are employed to fine-tune the energy-use model for future energy demand predictions. The results demonstrate the model's exceptional accuracy and suitability for diverse urban scenarios. Incorporating a more straightforward approach like Multiple Linear Regression (MLR) into the methodology also highlights its capability to predict energy demand in less complex research scenarios and offer valuable insights for effective urban energy planning. Overall, this article emphasizes the significance of datadriven approaches and machine learning techniques in optimizing energy demand, promoting sustainable urban development, and guiding informed decision-making for energy-efficient cities. The findings have implications for urban planners, policymakers, and energy analysts seeking to enhance energy efficiency and contribute to a greener and more sustainable future for urban communities.

Buildings 2024, 14, 185, 2024

Greenhouse gas emissions depend on natural and anthropic phenomena; however, to reduce emissions,... more 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.

2018 International IEEE Conference and Workshop in Óbuda on Electrical and Power Engineering (CANDO-EPE), 2018

Some straw buildings, which combine eco-sustainability with versatility, low cost, and fast const... more Some straw buildings, which combine eco-sustainability with versatility, low cost, and fast construction times, have recently been built in Northern Italy. In this work, the technologies used to build straw houses are presented, and the characteristics of the raw materials, the straw bales, and the construction techniques are dealt with. Two straw buildings, which have different characteristics and types of application, are analyzed. The first building is a residential, nearly zero-energy building, which was built in Saluggia (Vercelli) in 2012. This house is presently inhabited by a family and is heated with a wood stove. The second building was built in 2014 in Verres (Aosta) and is a pre-assembled demonstration prototype used for teaching purposes. The thermal performance of the straw envelopes was evaluated during the heating season by measuring the thermal conductance of the straw walls through two experimental campaigns. Straw bale walls offer good insulating performance, as well as high thermal inertia, and can be used in green buildings since straw is derived from agricultural waste, does not require an industrial process, and is degradable. Finally, these characteristics of straw can be combined with its low cost. Local economic development in this field may be possible.

Sustainability, 2023

Building energy modeling plays an important role in analyzing the energy efficiency of the ex-ist... more Building energy modeling plays an important role in analyzing the energy efficiency of the ex-isting building stock, helping in enhancing it by testing possible retrofit scenarios. This work presents an urban-scale and place-based approach that utilizes energy performance certificates to develop a statistical energy model. The objective is to describe the energy modeling methodology for evaluating the energy performance of residential buildings in Milan; besides, a comprehensive reference dataset for input data from available open databases in Italy is provided—a critical step in assessing energy consumption and production at territorial scale. The study employs open-source software QGIS to model and calculate various energy-related variables such as space heating, domestic hot water consumptions, and potential solar production. By analyzing de-mand/supply profiles, the research aims to increase energy self-consumption and self-sufficiency in the urban context using solar technologies. The presented methodology is validated by com-paring simulation results with measured data, achieving a Mean Absolute Percentage Error (MAPE) of 11%, which is acceptable, especially considering city-scale modeling. The analysis sheds light on key parameters affecting building energy consumption, such as volume, sur-face-area-to-volume ratio, construction period, systems' efficiency, and solar exposition. Addi-tionally, this assessment consents to evaluate the spatial distribution of energy-use and produc-tion within urban environments, contributing to plan and realize smart cities.

Building energy modeling plays an important role in analyzing the energy efficiency of the existi... more Building energy modeling plays an important role in analyzing the energy efficiency of the existing building stock, helping in enhancing it by testing possible retrofit scenarios. This work presents an urban-scale and place-based approach that utilizes energy performance certificates to develop a statistical energy model. The objective is to describe the energy modeling methodology for evaluating the energy performance of residential buildings in Milan; besides, a comprehensive reference dataset for input data from available open databases in Italy is provided-a critical step in assessing energy consumption and production at territorial scale. The study employs open-source software QGIS to model and calculate various energy-related variables for the prediction of space heating, domestic hot water consumptions, and potential solar production. By analyzing demand/supply profiles, the research aims to increase energy self-consumption and self-sufficiency in the urban context using solar technologies. The presented methodology is validated by comparing simulation results with measured data, achieving a Mean Absolute Percentage Error (MAPE) of 5.2 %, which is acceptable especially considering city-scale modeling. The analysis sheds light on key parameters affecting building energy consumption/production, such as type of user, volume, surface-to-volume ratio, construction period, systems' efficiency, solar exposition and roof area. Additionally, this assessment consents to evaluate the spatial distribution of energy-use and production within urban environments, contributing to plan and realize smart cities.

International Journal of Sustainable Development and Planning, 2023

Decarbonisation policies are often implemented in cities through the promotion of rooftop solar r... more Decarbonisation 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.

Urbanistica Dossier Vol. 27, 2022

http://www.inuedizioni.com/it/prodotti/rivista/n-027-urbanistica-dossier La prima crisi energet... more http://www.inuedizioni.com/it/prodotti/rivista/n-027-urbanistica-dossier
La prima crisi energetica mondiale è stata provocata dalla guerra del Kippur, chiamata così perché iniziò nel giorno del perdono Yom Kippur del calendario ebraico nell’ottobre 1973. Egitto e Siria tentarono di invadere Israele e vennero respinti; i paesi dell’Opec quindi aumentarono il costo del greggio e quindi di tutti i prodotti petroliferi. La storia delle politiche energetiche ed ambientali si può dire che nasca nel 1973, appena 50 anni fa ed è una questione globale che riguarda tutti i paesi del mondo. Da allora le politiche energetiche cercano di favorire uno sviluppo sostenibile dei paesi e si distinguono in: quelle per i paesi in via di sviluppo, in cui si cerca di fornire e distribuire energia in tutto il territorio per coprire l’attuale e la futura domanda di energia; per gli altri paesi, come quelli europei, si cerca di ridurre i consumi, differenziare le fonti energetiche, ridurre l’impatto ambientale dei servizi energetici e limitare la dipendenza energetica dall’estero. L’utilizzo dell’energia ha diverse ripercussioni sul territorio e tali effetti si devono poter misurare anche attraverso alcuni indicatori tra cui: l’indipendenza energetica, la sicurezza energetica, i costi dell’energia, le emissioni pro-capite, ecc. Le strategie adottate per lo sviluppo sostenibile e la pianificazione energetica di un territorio si basano sull’utilizzo di grandi databases e di modelli energetici che consentono di valutare questi indicatori a scala urbana, comunale, provinciale, regionale o anche nazionale. Tra i modelli più accurati, ci sono quelli place-based che consentono di geolocalizzare le informazioni e le variabili locali che influenzano i consumi o la produzione di energia. I modelli place-based vengono utilizzati ad esempio per le città, che sono i territori più critici da un punto di vista energetico ed ambientale, e per le comunità energetiche che aggregano utenti diversi per autoprodursi e scambiare energia, al fine di rendere le comunità autosufficienti e ridurre la dipendenza energetica dall’estero e dalle fonti fossili. In questo paragrafo verranno descritti i principali modelli energetici place-based, le problematiche e le prospettive delle banche-dati territoriali, alcuni strumenti e piattaforme che ha sviluppato Enea e infine due esempi di comunità energetiche pilota in Molise e in Piemonte.

Energies, 2023

Urban building energy models present a valuable tool for promoting energy efficiency in building ... more Urban 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.

Energy Efficiency, 2023

Increasing building efficiency is a key topic in territorial policies at different scales, for wh... more Increasing 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 socioeconomic 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.

Building Simulation Applicationc BSA 2022, 2022

Urban-scale evaluations of aerodynamic and morphological parameters allow to correct the wind spe... more Urban-scale evaluations of aerodynamic and morphological parameters allow to correct the wind speed within the urban boundary layer, as the wind profile is strongly influenced by the presence of roughness elements. This can have important implications in defining urban strategies for the reduction of buildings’ energy consumption and the improvement of air quality and liveability of outdoor spaces. Among the current models for assessing the air flow rate by natural ventilation in buildings at urban scale, this study aims to define a GIS-based methodology, using existing databases and an open source QGIS plug- in. From a digital surface elevation dataset, and considering prevalent wind directions, the displacement height (zd) has been determined. The wind speed has been corrected, applying the logarithmic or turbulent laws of wind profile, respectively above and below zd. This method can determine the spatial distribution of wind speed, considering each building façade characteristics and its surrounding. Resulting wind pressure on windward and leeward facades drives the air flow rate inside the buildings. Further developments of this work will improve the air flow modelling in buildings with other tools for applications at urban scale.

International Journal of Heat and Technology, 2022

Climate changes and urban population growth are increasing the heat island effects in cities, mak... more Climate changes and urban population growth are increasing the heat island effects in cities, making the urban outdoor environment less comfortable for people. Consequently, improving the thermal comfort conditions of urban open spaces could be considered one important challenge that cities can pursue in the upcoming years. As a first step, this work aims to assess which GIS tools are most useful for evaluating place-based outdoor thermal comfort conditions at urban scale. The UMEP-SOLWEIG (QGIS) tool was described and compared with ENVI-met, to calculate the thermal comfort indexes in different outdoor spaces, during extreme summer and winter conditions, in the city of Turin. These tools can be easily implemented in platforms to represent the spatial distribution of thermal comfort conditions in cities for prioritizing strategies and defining effective actions within land-use plans. This type of representation is crucial as it provides very comprehensible results to urban or regional planners and policy-makers. In this study, UMEP-SOLWEIG appeared to be the most suitable tool since it is the best compromise between simulation time and accuracy at urban scale.

2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2022

This work aims to propose a case study for the calculation of the energy performance of lighting ... more This work aims to propose a case study for the calculation of the energy performance of lighting systems in a retirement home. The proposed methodology evaluates the energy consumption of lighting systems in the presence of daytime lighting and occupancy control strategies with the Lighting Energy Numerical Indicator (LENI). The effect of natural light, the LED sources, the external obstructions, as well as building orientation and shading systems, can influence the energy consumption of the lighting systems. The case study analysed was the "Brancaccio retirement home" located in Matera (Southern part of Italy). The results of this work refer to both annual and monthly energy consumptions, and underline how important it is to evaluate the amount of energy throughout the year in the presence of control systems, given the considerable monthly variation. Furthermore, the LED source is able to significantly reduce energy consumption compared to fluorescent lamps, and this energy saving can be further increased in the presence of control systems.

International Journal of Sustainable Development and Planning, 2022

Renewable energy communities (RECs) are non-profit organizations made up of members who join to p... more Renewable energy communities (RECs) are non-profit organizations made up of members who join to produce and exchange clean energy for sustainable development. This work analyzes different REC scenarios, considering energetic, economic, and environmental perspectives. The case study is a typical condominium of eight apartments with a low energy class in Cagliari (Italy). This study considers the condominium with different energy efficiency levels before and after retrofit interventions together with solar technologies to produce energy. Future scenarios include both the share of energy between the eight apartments within the condominium and a REC composed of two neighboring condominiums. At condominium scale, results showed better outcomes in aggregating the energy share from the PV generation into a single point of sharing (PoS). In the REC scenario with a neighboring building, and after retrofit interventions, the self-sufficiency index was increased by 26% with a decrease of 23% in GHG emissions, which shows the importance of having retrofitted and smart buildings boosting the renewable energy sources in achieving a more sustainable built environment. The methodology of this work with a new software can be a useful decision-making tool to test the effectiveness of RECs and it can be applied to building, neighborhood, or district scales.

Atmosphere , 2024

Energy Efficiency, 2024

Mathematical Modelling of Engineering Problems, 2024

2020 IEEE 3rd International Conference and Workshop in Óbuda on Electrical and Power Engineering (CANDO-EPE), 2020

12th International Conference on Improving Energy Efficiency in Commercial Buildings and Smart Communities, 2024

Energy efficiency, 2024

Lecture Notes in Civil Engineering, 2024

2023 IEEE 6th International Conference and Workshop Óbuda on Electrical and Power Engineering (CANDO-EPE), 2023

Buildings 2024, 14, 185, 2024

2018 International IEEE Conference and Workshop in Óbuda on Electrical and Power Engineering (CANDO-EPE), 2018

Sustainability, 2023

International Journal of Sustainable Development and Planning, 2023

Urbanistica Dossier Vol. 27, 2022

Energies, 2023

Energy Efficiency, 2023

Building Simulation Applicationc BSA 2022, 2022

International Journal of Heat and Technology, 2022

2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), 2022

International Journal of Sustainable Development and Planning, 2022

CANDO-EPE 2024 • IEEE 7th International Conference and Workshop in Óbuda on Electrical and Power Engineering , 2024

The adoption of key directives by the EU Commission for reaching the ambitious energy and climate... more The adoption of key directives by the EU Commission for reaching the ambitious energy and climate targets by 2050 and to reduce greenhouse gas emissions by 55% by 2030, allowed to an increasingly use of renewable energies in the last years. In this framework, sharing of renewable energies through energy communities plays an important role in fastest reaching the energy transition. Renewable Energy Communities (RECs) aim to generate, distribute, share and consume renewable energies collectively. This work deals with the identification of the areas where RECs are more suitable in Italy through the use of an energy platform. This platform monitors actual energy consumption and production but also the territorial constraints and the availability to exploit all the renewable resources still available. A focus on the use of geothermal energy, which could be used to share both thermal energy and electricity within RECs, is presented. Areas with the greatest geothermal potential have been shown, explaining also how geothermal energy can be exploited through specific technologies. Considerations on how it is the social perception in using geothermal energy and why it is not still use as it should be, have been also introduced.

CANDO-EPE 2024 • IEEE 7th International Conference and Workshop in Óbuda on Electrical and Power Engineering • October 17–18, 2024 , 2024

Energy represents a fundamental requirement for the development process, while buildings are beco... more Energy represents a fundamental requirement for the development process, while buildings are becoming essential consumers in urban landscapes. Given the global need to optimize energy use, urban planners and decision-makers are placing increasing emphasis on energy efficiency in urban planning. The focus of this project is on developing predictive energy consumption models that are tailored to different building characteristics and thus offer differentiated insights into energy dynamics. Using a data-centric approach, the study draws on a comprehensive dataset of building characteristics and weather information, with a focus on residential space heating and domestic hot water consumption. The key to this research is the use of district-level gas consumption data as the dependent variable for modeling purposes. Given the different scales of other datasets, a top-down modeling technique was used. In addition, to strengthen the robustness of the analysis and improve understanding of energy consumption patterns, dependent variables were normalized based on factors that have the greatest influence on gas consumption. These factors include urban altitude, population density, number of families, building area, and volume. Another critical aspect of this study concerns the various independent variables that reflect the quality and characteristics of buildings in Mendoza City. Given the heterogeneous nature of the districts, efforts have been made to delineate homogeneous districts with similar consumption patterns through K-means clustering. Examining the relationship between dependent and independent variables required the use of correlation analysis and then applying multilinear regression to create the model.

Changsha, Hunan (China), , 2001

IEEE Cando Conference 2020, 2021

Building geometry, urban morphology and local climate are crucial aspects to optimize the energy ... more Building geometry, urban morphology and local climate are crucial aspects to optimize the energy performance of buildings at neighborhoods scale. In addition, urban form is a key parameter in modifying solar availability in densely built-up areas. This paper explores relationships between urban form and energy performance with implications for solar energy production on building roofs. This study investigated six neighborhoods of Turin (Italy) analyzing the urban morphology and the solar potential, taking into account the urban block typologies found across the city. From the energy simulations-made with the use of an urban-scale energy model-it has been found that in densely urban context, the optimal shape of the building-with low energy consumption and high solar energy production-must have a surface-to-volume ratio that varies between 0.37 m 2 /m 3 for favorable orientated buildings and 0.35 m 2 /m 3 for unfavorable oriented ones. These results could help in the design phase of new neighborhoods or in the reuse of existing buildings and empty spaces to promote the transition to low-carbon energy.

IEEE Cando Conference 2020, 2021

The purpose of this work is to define a place-based methodology to support the Energy Communities... more The purpose of this work is to define a place-based methodology to support the Energy Communities to evaluate the energy performance and energy saving potential of the buildings stock in the different areas in a territory. This work proposes an Atlas to improve energy efficiency interventions and low-carbon technologies on buildings based on a statistical analysis of the Energy Performance Certificates Database. The results of this analysis can be applied to the real buildings in order to define the best solution considering the territorial and buildings' characteristics. The final goal of this work is to support energy policies with a decision support tool. Keywords-energy community, sustainable development, atlases and place-based methodology, energy efficiency measures, renewable energy sources, energy performance certificate, residential buildings.

12th International Conference on Improving Energy Efficiency in Commercial Buildings and Smart Communities, 2024

Urbanistica Dossier, 2022

http://www.inuedizioni.com/it/prodotti/rivista/n-027-urbanistica-dossier A partire dal 2016 il te... more http://www.inuedizioni.com/it/prodotti/rivista/n-027-urbanistica-dossier A partire dal 2016 il territorio pinerolese si è impegnato su diversi fronti per attuare a livello locale un processo di transizione energetica che coinvolgesse tutti gli attori del territorio: cittadini, scuole, comuni e imprese. Questo processo ha visto la partecipazione attiva di due soggetti molto importanti: il Consorzio Pinerolo Energia (CPE), di cui fanno parte tutti i comuni del territorio che sono beneficiari dei servizi dell’azienda Acea che produce energia e gestisce servizi legati ai rifiuti e all’acqua. In questo ambito era partita una collaborazione con il Politecnico di Torino per uno studio e una campagna di raccolta dati per valutare consumi e produzione di energia [26, 27]. Nel 2018, la Regione Piemonte recepisce la Direttiva RED II 2018/2001 e promuove l’istituzione delle comunità energetiche con la Legge Regionale 12/2018 e l’iniziativa del pinerolese diventa uno dei quattro casi pilota nella regione. La Regione Piemonte ha cercato di trovare alcuni strumenti che potessero far sì che il territorio si muovesse in maniera coordinata verso un processo di transizione energetica. Tra questi strumenti il pinerolese utilizza la Oil Free Zone facendo riferimento alla Legge 221/2015, che definisce le aree territoriali in cui i comuni sottoscrivono un atto di indirizzo (protocollo di intesa) che prevede la progressiva dismissione del petrolio e degli altri combustibili fossili con energia prodotta da fonti rinnovabili. Nel 2019, 27 dei 47 dei Comuni del pinerolese sottoscrivono un protocollo di intesa e, nei mesi successivi, 6 Comuni vengono scelti come nucleo fondatore di una prima comunità energetica (in Figura 12). Questi Comuni partecipano a un bando della Regione Piemonte sulle Comunità Energetiche e nel febbraio 2020 lo vincono insieme ad altre tre realtà sul territorio regionale: CE Val Susa, CE Valli Maira e Grana, CE Consorzio Monviso.

The challenge to make cities and human settlements inclusive, safe, and resilient, including miti... more The challenge to make cities and human settlements inclusive, safe, and resilient, including mitigation and adaptation strategies against disaster, is a central issue in achieving sustainability. This research proposes a tool to measure local vulnerability from a multi-risk approach. The municipality of Moncalieri, Italy, was used as a case study within the research activities of the Responsible Risk Resilience Centre from the
Polytechnic of Turin to test the vulnerability matrix. The tool consists of a mathematical framework for the territorial vulnerability assessment that integrates multiple indicators clustered into three factors defined as sensitivity, pressures, and hazards, weighted according to a participatory procedure. Space-dependent
analyses using the Geographical Information System were developed from the multiple nested indicators to project the vulnerability index onto a homogeneous grid in the territory of interest. Thematic maps referring to the systemic vulnerability by different sensitivity components were generated. The tool not only contributes to increasing the awareness of territorial vulnerability but also offers support to resilience-based decision-making in designing technical measures of policies at a local scale. Further research is required to implement the framework in different scenarios and develop the model's temporal behaviour.