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Optimal Design of Energy Storage System for Peak-Shaving in Industrial Production

Li, Lixin ORCID iD icon 1,2; Starosta, Anna Sina ORCID iD icon 1,2; Schwarz, Bernhard ORCID iD icon 1,2; Munzke, Nina ORCID iD icon 1,2; Strehle, Hanns-Martin; Richter, Mark; Hiller, Marc 1
1 Elektrotechnisches Institut (ETI), Karlsruher Institut für Technologie (KIT)
2 Batterietechnikum (Batterietechnikum), Karlsruher Institut für Technologie (KIT)

Abstract:

Energy storage systems (ESS) offer a wide range of applications in industrial production, with the potential to significantly reduce electricity power costs through peak-shaving, particularly in Germany. This paper proposes a methodology for designing ESSs specifically for industrial peak shaving from a techno-economic perspective. The proposed approach utilizes mixed-integer linear programming (MILP) to calculate the minimum annualized total operating costs, compares various energy storage technologies (EST) to determine the optimal solution, and performs sensitivity analysis to identify critical impact factors on the optimization problem. A case study is implemented with real-world data. The results indicate that connecting a 38.4 kW/38.4 kWh lithium-ion (Li-ion) battery energy storage system (BESS) to the example factory delivers the greatest economic benefit compared to the other three storage technologies. This results in a total cost saving of 980 €/a and a peak power reduction of 33.8 kW. Additionally, a lookup table is provided to assist the factory in selecting the optimal Li-ion BESS available in the market. © VDE VERLAG GMBH Berlin Offenbach.


Verlagsausgabe §
DOI: 10.5445/IR/1000173121
Veröffentlicht am 06.08.2024
Postprint §
DOI: 10.5445/IR/1000173121/post
Veröffentlicht am 06.08.2024
Cover der Publikation
Zugehörige Institution(en) am KIT Batterietechnikum (Batterietechnikum)
Elektrotechnisches Institut (ETI)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 05.09.2023
Sprache Englisch
Identifikator ISBN: 978-3-8007-6134-0
KITopen-ID: 1000173121
Erschienen in NEIS 2023; Conference on Sustainable Energy Supply and Energy Storage Systems. Ed.: D. Schulz
Veranstaltung Conference on Sustainable Energy Supply and Energy Storage Systems (NEIS 2023), Hamburg, Deutschland, 04.09.2023 – 05.09.2023
Verlag VDE Verlag
Seiten 79-85
Schlagwörter energy storage technology; industrial production; mixed-integer linear programming; peak-shaving
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