<div class="csl-bib-body">
<div class="csl-entry">Fischer, M., & Hofmann, R. (2024). AI for Energy Intensive Industry: A Hybrid Optimization Approach for Flexibility Service Providers. In <i>ASME 2024 18th International Conference on Energy Sustainability collocated with the ASME 2024 Heat Transfer Summer Conference and the ASME 2024 Fluids Engineering Division Summer Meeting</i>. ASME 2024 18th International Conference on Energy Sustainability, Anaheim, CA, United States of America (the). https://doi.org/10.1115/ES2024-123705</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/204788
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dc.description.abstract
This paper presents a hybrid optimization method for industrial prosumers to act as flexibility service providers. The proposed method is applied to an industrial company from the energy intensive industry participating in the European Power Exchange and the Austrian balancing market, specifically focusing on automatic Frequency Restoration Reserve. A company in the food processing industry, with on-site electrical and thermal power generation is used to demonstrate the hybrid approach. There, metaheuristics and Mixed Integer Linear Programming are combined to solve a bidding strategy problem with a subsequent unit commitment problem. As metaheuristics, a Genetic Algorithm and Particle Swarm Optimization were applied and their results compared.
en
dc.description.sponsorship
Klima- und Energiefonds
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dc.language.iso
en
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dc.subject
Flexibility
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dc.subject
Genetic Algorithms
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dc.subject
Hybrid Optimization
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dc.subject
Particle Swarm Optimization
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dc.title
AI for Energy Intensive Industry: A Hybrid Optimization Approach for Flexibility Service Providers
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
TU Wien, Austria
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dc.relation.isbn
9780791887899
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dc.relation.grantno
887780
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
ASME 2024 18th International Conference on Energy Sustainability collocated with the ASME 2024 Heat Transfer Summer Conference and the ASME 2024 Fluids Engineering Division Summer Meeting
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tuw.peerreviewed
true
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tuw.project.title
Industry4Redispatch
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tuw.researchTopic.id
C4
-
tuw.researchTopic.id
C6
-
tuw.researchTopic.id
E3
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tuw.researchTopic.name
Mathematical and Algorithmic Foundations
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tuw.researchTopic.name
Modeling and Simulation
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tuw.researchTopic.name
Climate Neutral, Renewable and Conventional Energy Supply Systems
