A method for mapping areas potentially suitable for district heating systems. An application to Canton Ticino (Switzerland)

Pampuri, Luca; Belliardi, Marco; Bettini, Albedo; Cereghetti, Nerio; Curto, Ivan; Caputo, Paola

doi:10.1016/j.energy.2019.116297

Cited by 9 publications

(7 citation statements)

References 12 publications

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“…To ensure reliable and up-to-date energy data, a list of available databases and their data availability was compiled. The authors relied on their experience in similar works ( [7], [8], [9], [10]) and their knowledge of available databases in Switzerland. Municipal, cantonal and federal databases were ordered for inclusion in the list.…”

Section: Analysis and Collection Of The Available Databasesmentioning

confidence: 99%

“…The program allows for the variation of areas between 100 hectares and 50 hectares to identify the densest areas. The thermal needs are evaluated on a theoretical level, taking into consideration the heat indices described in [9] and [10]. Additionally, there is the option to manually modify the thermal needs of building, based on more reliable information obtained from the databases.…”

Section: District Heatingmentioning

confidence: 99%

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Digitisation and analysis of energy data at municipal scale: an application to the municipality of Mendrisio

Belliardi,

Cereghetti,

Bettini

et al. 2023

J. Phys.: Conf. Ser.

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The concept of Smart Cities has gained significant attention in recent years due to the increasing need for efficient energy management in urban areas. This paper describes a digital platform for the management of energy databases that aims to synchronize, update, and analyze different energy installations and uses in the municipality of Mendrisio 1according to the Smart City concept. The platform interweaves and compares various energy databases to ensure better efficiency in the use of thermal and electrical energy, as well as optimize the consumption and production of renewable energies. The geodigital platform created is capable of conducting energy assessments for the development of new district heating projects in the municipality and the creation of local energy communities. This paper presents the design and functionalities of the proposed digital platform, highlighting its potential for improving energy management in Smart Cities and facilitating the transition to more sustainable energy practices. The results of this study, financed by Swiss Energy together with Canton Ticino and AIM (Aziende Industriali Mendrisio), contribute to the growing body of research on digital technologies for energy management in urban areas and provide insights for policymakers and urban planners seeking innovative solutions for sustainable energy development.

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Section: Analysis and Collection Of The Available Databasesmentioning

confidence: 99%

Section: District Heatingmentioning

confidence: 99%

Digitisation and analysis of energy data at municipal scale: an application to the municipality of Mendrisio

Belliardi,

Cereghetti,

Bettini

et al. 2023

J. Phys.: Conf. Ser.

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“…However, the datasets are not publicly available at the time of the submission of this paper. Moreover, the Heat Roadmap Europe project, a robust body of scientific literature (e.g., [15][16][17][18][19][20][21][22][23][24][25]) on similar yet more locally focused projects, is available. The heat density maps developed in the frame of the comprehensive assessments at the national level also belong to this category.…”

Section: Spacial Levels Of Heating and Cooling Planningmentioning

confidence: 99%

Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28

Müller

Hummel²,

Kranzl

et al. 2019

Energies

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The planning of heating and cooling supply and demand is key to reaching climate and sustainability targets. At the same time, data for planning are scarce for many places in Europe. In this study, we developed an open source dataset of gross floor area and energy demand for space heating and hot water in residential and tertiary buildings at the hectare level for EU28 + Norway, Iceland, and Switzerland. This methodology is based on a top-down approach, starting from a consistent dataset at the country level (NUTS 0), breaking this down to the NUTS 3 level and further to the hectare level by means of a series of regional indicators. We compare this dataset with data from other sources for 20 places in Europe. This process shows that the data for some places fit well, while for others, large differences up to 45% occur. The discussion of these results shows that the other data sources used for this comparison are also subject to considerable uncertainties. A comparison of the developed data with maps based on municipal building stock data for three cities shows that the developed dataset systematically overestimates the gross floor area and heat demand in low density areas and vice versa. We conclude that these data are useful for strategic purposes on aggregated level of larger regions and municipalities. It is especially valuable in locations where no detailed data is available. For detailed planning of heating and cooling infrastructure, local data should be used instead. We believe our work contributes towards a transparent, open source dataset for heating and cooling planning that can be regularly updated and is easily accessible and usable for further research and planning activities.

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“…For instance, in the literature, it is possible to find studies concerning the spatial assessments and/or estimations of the urban energy demand, either at district or urban scales. Applications have been found for Bologna [7], St. Gallen and Zernez (Switzerland) [8], Milan [9], Geneva [10], Ladispoli (Italy) [11], Houston [12], New York [13,14], Lisbon [15], Turin [16], Gleisdorf (Austria) [17], Borlänge (Sweden) [18], London [19], Settimo Torinese (Italy) [20], Busan (Korea) [21], and the Canton Ticino area (Switzerland) [22,23]. Other surveyed studies have also provided to the spatial assessments of the potential energy savings from buildings retrofit, such as in the studies of Caputo and Pasetti [24], applied to the Italian city of Senago; and of Mastrucci et al [25], applied to Rotterdam city.…”

Section: Introductionmentioning

confidence: 99%

“…As extensively discussed in the review of Reinhart and Davila [28], to implement an energy model of urban buildings, it is necessary to obtain a large amount of data concerning the definition of climate, orography, and urban texture, and the technological and physical characteristics of buildings. For instance, in the study of Pampuri et al [23], even thirteen different databases were used for modeling the urban energy demand and identifying areas potentially suitable for district heating networks; in the study of Sarralde [26], eighteen indicators were derived in order to analyze the urban morphology toward investigating the solar energy potential. Given the recent growing diffusion of public spatial data, some of these are already available in several contexts, but there is still an ongoing issue regarding their integration when coming from different sources, due to rare mutual consistency [29] and raw data quality [30].…”

Section: Introductionmentioning

confidence: 99%

Mapping Buildings’ Energy-Related Features at Urban Level toward Energy Planning

et al. 2021

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To boost energy efficiency in the building sector at urban and district scales, the use of a Geographic Information System (GIS) for data collection and energy spatial analysis is relevant. As highlighted in many studies on this topic reported in literature, the correlation among available databases is complex due to the different levels of information. As the first part of a wide research aimed at estimating the energy demand of urban buildings, we present in this article a focus on the details of the GIS-based procedure developed to assess the main energy-related features of existing building stocks. The procedure is based on the elaboration of data from the Italian Topographic Databases, under provision at the national level according to the INSPIRE European Directive and the national General Census of Population and Houses. It enables one to calculate and map the urban built volume characterized by mostly diffuse use categories in an urban context (residential and offices), to which different equipment and building usage patterns can be associated, and by construction periods, featuring different technological solutions. The method has been applied to the city of Milan (Italy). An insight into the outcomes from the overall method of the wider research is also reported.

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A method for mapping areas potentially suitable for district heating systems. An application to Canton Ticino (Switzerland)

Cited by 9 publications

References 12 publications

Digitisation and analysis of energy data at municipal scale: an application to the municipality of Mendrisio

Digitisation and analysis of energy data at municipal scale: an application to the municipality of Mendrisio

Open Source Data for Gross Floor Area and Heat Demand Density on the Hectare Level for EU 28

Mapping Buildings’ Energy-Related Features at Urban Level toward Energy Planning

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