Energy supply scheduling in manufacturing systems using Quantum Annealing
- Optimizing a manufacturing company's in-house energy demand amidst fluctuating electricity prices and uncertainties in renewable energy supply as well as volatile manufacturing planning situations is a challenging task. To tackle this issue, a novel approach is developed for scheduling the energy supply in manufacturing systems with the objective of reducing energy costs. The approach employs Quantum Annealing to determine the optimal mix of in-house generation, purchased electricity, and energy storage. The effectiveness and scalability of the approach are demonstrated through the validation using two simplified use cases, showcasing its potential in solving complex energy supply optimization problems.
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| Author: | Philipp SchwormORCiD |
|---|---|
| URN: | urn:nbn:de:hbz:386-kluedo-78536 |
| DOI: | https://doi.org/10.1016/j.mfglet.2023.09.005 |
| ISSN: | 2213-8463 |
| Parent Title (English): | Manufacturing Letters |
| Publisher: | Elsevier |
| Document Type: | Article |
| Language of publication: | English |
| Date of Publication (online): | 2023/09/22 |
| Year of first Publication: | 2023 |
| Publishing Institution: | Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau |
| Date of the Publication (Server): | 2024/03/21 |
| Page Number: | 5 |
| First Page: | 47 |
| Last Page: | 51 |
| Source: | https://www.sciencedirect.com/science/article/pii/S2213846323002146?via%3Dihub |
| Faculties / Organisational entities: | Kaiserslautern - Fachbereich Maschinenbau und Verfahrenstechnik |
| DDC-Cassification: | 6 Technik, Medizin, angewandte Wissenschaften / 620 Ingenieurwissenschaften und Maschinenbau |
| Collections: | Open-Access-Publikationsfonds |
| Licence (German): |  Creative Commons 4.0 - Namensnennung (CC BY 4.0) |