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A Framework for Enabling Manufacturing Flexibility and Optimizing Industrial Demand Response Services

Authors: Paul Kengfai Wan; Matteo Ranaboldo; Alessandro Burgio; Chiara Caccamo; Giuseppe Fragapane;

A Framework for Enabling Manufacturing Flexibility and Optimizing Industrial Demand Response Services

Abstract

The energy industry is experiencing significant changes in terms of sustainability and competition, primarily driven by the introduction of renewable energy targets and emission limits. Demand response is a potential solution to reduce the critical peak; however, its implementation in industries can be challenging due to their production requirements. Technology enablers such as digital twin technology can enhance energy flexibility and optimize manufacturing and service processes. In this study, we aim to develop a framework that can help the manufacturing industry to optimise industrial demand response services and achieve a seamless interaction of different layers such as the physical, data infrastructure, digital twin, management, and aggregator. A systematic literature review and workshops were conducted to identify key technologies, decision areas and methods to enable both manufacturing and energy flexibility to reach demand response. Based on the results, an energy-flexible framework for manufacturing industries was developed.

Country
Spain
Keywords

Digital Twin, Demand response, Àrees temàtiques de la UPC::Enginyeria mecànica::Processos de fabricació mecànica, 330, Manufacturing flexibility, Energy flexibility, 620

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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
2
Top 10%
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