GIS-based data-driven simulation of load profiles in industrial and urban areas
Date Issued
2025
Author(s)
Zabala Figueroa Alejandro
Deutscher Akademischer Austauschdienst, Rijksuniversiteit Groningen, UNION Versicherungsdienst GmbH, Universidad Antonio Nariño, Universidad Nacional de Colombia, University of Applied Sciences Stralsund, University of Groningen
Medjroubi, Wided
Deutsches Zentrum für Luft- und Raumfahrt eV, Rijksuniversiteit Groningen, University of Groningen
Abstract
Despite the increasing use of renewable energy generation in Europe, accounting for 41%,
progress in the decarbonization of the heating sector has been comparatively limited, with
only 25% of the total energy from renewables. To address this disparity, the European Union's
RED III policy framework has been implemented, with the objective of accelerating the
adoption of renewable energy generation, including in the heating sector. The present study
proposes a Geographic Information System (GIS)-based data-driven model, leveraging which
utilizes spatially resolved data to map energy demand in industrial and adjacent urban areas.
The primary objective is to identify energy demand of specific areas of interests in cities, as
well as potential sources of waste heat, which could be used for renewable energy generation.
The model employs Nomenclature of Economic Activities (NACE) classification codes to
provide time series data on heating, cooling and electricity consumption, facilitating the
identification of potential district heating opportunities. The model applies the Kalundborg's
'symbiosis' principle, whereby a waste product from one company becomes a resource for
another, benefiting both the environment and the economy, while also meeting the RED III
objective of identifying renewable energy sites, thereby helping local stakeholders to
efficiently identify zero-carbon solutions for the region's energy transition. In order to verify
the application of the model, it is applied to the industrial area around the steel company in
Bremen.
progress in the decarbonization of the heating sector has been comparatively limited, with
only 25% of the total energy from renewables. To address this disparity, the European Union's
RED III policy framework has been implemented, with the objective of accelerating the
adoption of renewable energy generation, including in the heating sector. The present study
proposes a Geographic Information System (GIS)-based data-driven model, leveraging which
utilizes spatially resolved data to map energy demand in industrial and adjacent urban areas.
The primary objective is to identify energy demand of specific areas of interests in cities, as
well as potential sources of waste heat, which could be used for renewable energy generation.
The model employs Nomenclature of Economic Activities (NACE) classification codes to
provide time series data on heating, cooling and electricity consumption, facilitating the
identification of potential district heating opportunities. The model applies the Kalundborg's
'symbiosis' principle, whereby a waste product from one company becomes a resource for
another, benefiting both the environment and the economy, while also meeting the RED III
objective of identifying renewable energy sites, thereby helping local stakeholders to
efficiently identify zero-carbon solutions for the region's energy transition. In order to verify
the application of the model, it is applied to the industrial area around the steel company in
Bremen.
Subjects
Heating
;
cooling
;
renewables
;
GIS
;
district heating
;
waste heat
Publisher
Aalborg University
Institution
Type
journal article
Journal/Edited collection
Book of Abstracts 2025: 11th International Conference on Smart Energy Systems
Language
English