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Modelling and control of aqueous parts cleaning machines for demand response

Fuhrländer-Völker, Daniel ; Grosch, Benedikt ; Weigold, Matthias
Hrsg.: Herberger, David ; Hübner, Marco ; Stich, Volker (2023)
Modelling and control of aqueous parts cleaning machines for demand response.
Conference on Production Systems and Logistics: CPSL 2023. Stellenbosch, Südafrika (14.11. - 17.11.23)
doi: 10.15488/13498
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

With the aim of enabling better utilization of renewable power and reducing the environmental impact of industrial sites, we propose an approach for implementing electric demand response. Cleaning machines provide significant potential for demand response due to their large water tanks, which can be used for thermal energy storage. Furthermore, many batch cleaning machines allow process interruptions without impacting the cleaning result. We show that utilizing inherent energy storage and process interruptions are practical ways to implement demand response. Hence, we present a mathematical demand response model of an aqueous parts cleaning machine and integrate it in a cyber-physical production system. The mathematical demand response model is used to determine the energy consumption of the machine resulting from the cleaning process and the tank heater. The model is divided into an event-based part describing the individual steps of the cleaning process and a time-based part representing the energy required by the tank heater to satisfy specified tank temperature limits. In addition to the mathematical model, we present the data model required for communication with the physical machine. We validate the mathematical model and the complete cyber-physical production system including a real machine in a field test in the ETA research factory for their demand response capabilities.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2023
Herausgeber: Herberger, David ; Hübner, Marco ; Stich, Volker
Autor(en): Fuhrländer-Völker, Daniel ; Grosch, Benedikt ; Weigold, Matthias
Art des Eintrags: Bibliographie
Titel: Modelling and control of aqueous parts cleaning machines for demand response
Sprache: Englisch
Publikationsjahr: 2023
Ort: Hannover
Verlag: publish-Ing.
Buchtitel: Proceedings of the Conference on Production Systems and Logistics: CPSL 2023
Veranstaltungstitel: Conference on Production Systems and Logistics: CPSL 2023
Veranstaltungsort: Stellenbosch, Südafrika
Veranstaltungsdatum: 14.11. - 17.11.23
DOI: 10.15488/13498
URL / URN: https://www.repo.uni-hannover.de/handle/123456789/13608
Kurzbeschreibung (Abstract):

With the aim of enabling better utilization of renewable power and reducing the environmental impact of industrial sites, we propose an approach for implementing electric demand response. Cleaning machines provide significant potential for demand response due to their large water tanks, which can be used for thermal energy storage. Furthermore, many batch cleaning machines allow process interruptions without impacting the cleaning result. We show that utilizing inherent energy storage and process interruptions are practical ways to implement demand response. Hence, we present a mathematical demand response model of an aqueous parts cleaning machine and integrate it in a cyber-physical production system. The mathematical demand response model is used to determine the energy consumption of the machine resulting from the cleaning process and the tank heater. The model is divided into an event-based part describing the individual steps of the cleaning process and a time-based part representing the energy required by the tank heater to satisfy specified tank temperature limits. In addition to the mathematical model, we present the data model required for communication with the physical machine. We validate the mathematical model and the complete cyber-physical production system including a real machine in a field test in the ETA research factory for their demand response capabilities.

Freie Schlagworte: carbon neutral production, cyber-physical production System, data model, energy-flexibility, inherent energy storage, model predictive control, single machine scheduling
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
16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) > Management industrieller Produktion
16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) > TEC Fertigungstechnologie
Hinterlegungsdatum: 09 Mai 2023 08:55
Letzte Änderung: 07 Dez 2023 12:59
PPN: 507644522
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