Theisinger, Lukas ; Borst, Fabian ; Kohne, Thomas ; Weigold, Matthias (2023)
Concept development for industrial heating networks under consideration of low temperature waste heat: a data-driven decision support.
In: Procedia CIRP, 116
doi: 10.1016/j.procir.2023.02.057
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Over the last decade, governments throughout the world set ambitious goals for decarbonisation to reduce the impacts of humanity on climate. Here, the industrial sector is of particular importance as it accounts for over one third of the global CO2 emissions. Even though being exceeded by higher temperature levels, low temperature heating accounts for up to 26 % of the total useful energy demand, depending on the specific industry sector. Those lower temperature levels tend to be beneficial for decarbonisation measures like utilization of industrial waste heat or electrification via heat pumps. In this work, we present a data-driven decision support which aims at supporting decision-makers in the concept phase of large-scale industrial heating networks in a bottom-up approach. For this purpose, we utilize heating and cooling demand data which are condensed into key metrics to recommend supply concepts (e.g., consumer, producer, prosumer) within the context of those systems. Concurrently, we ensure user-orientation through adaptability and transparency in the decision-making process. Throughout this paper, our approach is outlined using the example and operational data of a real industrial site.
Typ des Eintrags: | Artikel |
---|---|
Erschienen: | 2023 |
Autor(en): | Theisinger, Lukas ; Borst, Fabian ; Kohne, Thomas ; Weigold, Matthias |
Art des Eintrags: | Bibliographie |
Titel: | Concept development for industrial heating networks under consideration of low temperature waste heat: a data-driven decision support |
Sprache: | Englisch |
Publikationsjahr: | 18 April 2023 |
Verlag: | Elsevier B.V. |
Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Procedia CIRP |
Jahrgang/Volume einer Zeitschrift: | 116 |
DOI: | 10.1016/j.procir.2023.02.057 |
URL / URN: | https://www.sciencedirect.com/science/article/pii/S221282712... |
Kurzbeschreibung (Abstract): | Over the last decade, governments throughout the world set ambitious goals for decarbonisation to reduce the impacts of humanity on climate. Here, the industrial sector is of particular importance as it accounts for over one third of the global CO2 emissions. Even though being exceeded by higher temperature levels, low temperature heating accounts for up to 26 % of the total useful energy demand, depending on the specific industry sector. Those lower temperature levels tend to be beneficial for decarbonisation measures like utilization of industrial waste heat or electrification via heat pumps. In this work, we present a data-driven decision support which aims at supporting decision-makers in the concept phase of large-scale industrial heating networks in a bottom-up approach. For this purpose, we utilize heating and cooling demand data which are condensed into key metrics to recommend supply concepts (e.g., consumer, producer, prosumer) within the context of those systems. Concurrently, we ensure user-orientation through adaptability and transparency in the decision-making process. Throughout this paper, our approach is outlined using the example and operational data of a real industrial site. |
Freie Schlagworte: | key performance indicator, low temperature heating, supply concept, thermal integration |
Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) > ETA Energietechnologien und Anwendungen in der Produktion |
Hinterlegungsdatum: | 21 Apr 2023 05:44 |
Letzte Änderung: | 15 Mai 2023 08:11 |
PPN: | 507761758 |
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