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Combined dynamic programming and region-elimination technique algorithm for optimal sizing and management of lithium-ion batteries for photovoltaic plants

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dc.contributor.authorBerrueta Irigoyen, Alberto
dc.contributor.authorHeck, Michael
dc.contributor.authorJantsch, Martin
dc.contributor.authorUrsúa Rubio, Alfredo
dc.contributor.authorSanchis Gúrpide, Pablo
dc.contributor.departmentIngeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzareneu
dc.contributor.departmentInstitute for Advanced Materials and Mathematics - INAMAT2en
dc.contributor.departmentIngeniería Eléctrica, Electrónica y de Comunicaciónes_ES
dc.contributor.funderGobierno de Navarra / Nafarroako Gobernua PI038 INTEGRA-RENOVABLESes
dc.date.accessioned2019-06-05T08:20:45Z
dc.date.available2020-06-19T23:00:17Z
dc.date.issued2018
dc.description.abstractThe unpredictable nature of renewable energies is drawing attention to lithium-ion batteries. In order to make full utilization of these batteries, some research works are focused on the management of existing systems, while others propose sizing techniques based on business models. However, in order to optimise the global system, a comprehensive methodology that considers both battery sizing and management at the same time is needed. This paper proposes a new optimisation algorithm based on a combination of dynamic programming and a region elimination technique that makes it possible to address both problems at the same time. This is of great interest, since the optimal size of the storage system depends on the management strategy and, in turn, the design of this strategy needs to take account of the battery size. The method is applied to a real installation consisting of a 100 kWp rooftop photovoltaic plant and a Li-ion battery system connected to a grid with variable electricity price. Results show that, unlike conventional optimisation methods, the proposed algorithm reaches an optimised energy dispatch plan that leads to a higher net present value. Finally, the tool is used to provide a sensitivity analysis that identifies key informative variables for decision makersen
dc.description.sponsorshipThe authors would like to acknowledge the support of the Spanish State Research Agency and FEDER-UE under grants DPI2016-80641-R and DPI2016-80642-R; of Government of Navarra through research project PI038 INTEGRA-RENOVABLES; and the FPU Program of the Spanish Ministry of Education, Culture and Sport (FPU13/00542).en
dc.embargo.lift2020-06-19
dc.embargo.terms2020-06-19
dc.format.extent14 p.
dc.format.mimetypeapplication/pdfen
dc.identifier.doi10.1016/j.apenergy.2018.06.060
dc.identifier.issn0306-2619
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/33235
dc.language.isoengen
dc.publisherElsevieren
dc.relation.ispartofApplied Energy, 228 (2018) 1-11en
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/1PE/DPI2016-80641en
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/1PE/DPI2016-80642en
dc.relation.publisherversionhttps://doi.org/10.1016/j.apenergy.2018.06.060
dc.rights© 2018. Elsevier Ltd. The manuscript version is made available under the CC BY-NC-ND 4.0 license.en
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectEnergy storage systemen
dc.subjectLithium-ion batteryen
dc.subjectOptimal energy dispatch schedulingen
dc.subjectDynamic programming methoden
dc.subjectEnergy arbitrageen
dc.subjectRenewable energyen
dc.titleCombined dynamic programming and region-elimination technique algorithm for optimal sizing and management of lithium-ion batteries for photovoltaic plantsen
dc.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/acceptedVersionen
dc.type.versionVersión aceptada / Onetsi den bertsioaes
dspace.entity.typePublication
relation.isAuthorOfPublicatione2fc78a7-4a1b-45eb-86f4-fe9ad125c1a9
relation.isAuthorOfPublicationb0612ced-717d-455f-b411-6b3d3affcde0
relation.isAuthorOfPublicationeb28ad46-ad2e-4415-a048-6c3f2fe48916
relation.isAuthorOfPublication.latestForDiscoverye2fc78a7-4a1b-45eb-86f4-fe9ad125c1a9

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