

You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Data Analysis of Heating Systems for Buildings—A Tool for Energy Planning, Policies and Systems Simulation

doi: 10.3390/en11010233
handle: 11583/2699610 , 11573/1067736
Heating and cooling in buildings is a central aspect for adopting energy efficiency measures and implementing local policies for energy planning. The knowledge of features and performance of those existing systems is fundamental to conceiving realistic energy savings strategies. Thanks to Information and Communication Technologies (ICT) development and energy regulations’ progress, the amount of data able to be collected and processed allows detailed analyses on entire regions or even countries. However, big data need to be handled through proper analyses, to identify and highlight the main trends by selecting the most significant information. To do so, careful attention must be paid to data collection and preprocessing, for ensuring the coherence of the associated analyses and the accuracy of results and discussion. This work presents an insightful analysis on building heating systems of the most populated Italian region—Lombardy. From a dataset of almost 2.9 million of heating systems, selected reference values are presented, aiming at describing the features of current heating systems in households, offices and public buildings. Several aspects are considered, including the type of heating systems, their thermal power, fuels, age, nominal and measured efficiency. The results of this work can be a support for local energy planners and policy makers, and for a more accurate simulation of existing energy systems in buildings.
- Delft University of Technology Netherlands
- Sapienza University of Rome Italy
- Polytechnic University of Turin Italy
690, Technology, building energy efficiency, Building energy efficiency; Conventional and condensing boilers; Natural gas; Open energy data; Space heating; Thermal systems; Urban energy planning; Computer Science (all); Renewable Energy, Sustainability and the Environment; Energy Engineering and Power Technology; Energy (miscellaneous), T, conventional and condensing boilers, urban energy planning, open energy data, natural gas, open energy data; thermal systems; conventional and condensing boilers; natural gas; urban energy planning; building energy efficiency; space heating, building energy efficiency; conventional and condensing boilers; natural gas; open energy data; space heating; thermal systems; urban energy planning; computer science; renewable energy, sustainability and the environment; energy engineering and power technology; energy, space heating, thermal systems
690, Technology, building energy efficiency, Building energy efficiency; Conventional and condensing boilers; Natural gas; Open energy data; Space heating; Thermal systems; Urban energy planning; Computer Science (all); Renewable Energy, Sustainability and the Environment; Energy Engineering and Power Technology; Energy (miscellaneous), T, conventional and condensing boilers, urban energy planning, open energy data, natural gas, open energy data; thermal systems; conventional and condensing boilers; natural gas; urban energy planning; building energy efficiency; space heating, building energy efficiency; conventional and condensing boilers; natural gas; open energy data; space heating; thermal systems; urban energy planning; computer science; renewable energy, sustainability and the environment; energy engineering and power technology; energy, space heating, thermal systems
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).31 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10% visibility views 9 download downloads 2 - 9views2downloads
Data source Views Downloads TU Delft Repository 9 2


