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dc.contributor.authorHaug, Martin
dc.contributor.authorBordin, Chiara
dc.contributor.authorMishra, Sambeet
dc.contributor.authorMoisan, Julien
dc.date.accessioned2024-01-05T11:26:16Z
dc.date.available2024-01-05T11:26:16Z
dc.date.issued2023-12-08
dc.description.abstractThis paper presents the state-of-the-art and latest advances in implementing multi-use practices on BESS applications to the power system grid. Representative papers on modeling and optimization methods were selected, most of them working with realistic use cases, but none reporting on real-world implementations. Some major findings from reviewing key representative papers are that current optimization methods were able to handle uncertainty related to prices and other parameters either in the look-ahead planning stage or real-time control for obtaining an optimal dispatch schedule, thus addressing previously pointed-out gaps. Further, a recommendation for future work is to implement current multi-use methods, found to be mature enough, to real-world BESS use cases for validation and gaining experimental experience. Furthermore, the multi-use performance can further be improved by joining the strong contributions from each paper's method. Current methods have shown great potential for bringing simultaneous benefits to the grid, as well as being economical for the owner. A continued exploration and inclusion of new future BESS applications in prescriptive analytics for BESS multi-use suggest robustness for future market changes. However, further assessments are needed to evaluate whether the technology is economical and green for each particular use case and also for a potential systematic upscaling of the technology as a means to facilitate the green shift.en_US
dc.identifier.citationHaug, Bordin, Mishra, Moisan. Prescriptive analytics for optimal multi-use battery energy storage systems operation: State-of-the-art and research directions . Procedia Computer Science. 2023;225:676-685en_US
dc.identifier.cristinIDFRIDAID 2214208
dc.identifier.doi10.1016/j.procs.2023.10.053
dc.identifier.issn1877-0509
dc.identifier.urihttps://hdl.handle.net/10037/32344
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.journalProcedia Computer Science
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2023 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)en_US
dc.titlePrescriptive analytics for optimal multi-use battery energy storage systems operation: State-of-the-art and research directionsen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Med mindre det står noe annet, er denne innførselens lisens beskrevet som Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)