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Energy-constrained model for scheduling of battery storage systems in joint energy and ancillary service markets based on the energy throughput concept

2021Journal article Open access
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dc.contributor.authorKhojasteh, Meysam
dc.contributor.authorFaria, Pedro
dc.contributor.authorVale, Zita
dc.date.accessioned2022-01-11T15:35:35Z
dc.date.available2022-01-11T15:35:35Z
dc.date.issued2021
dc.description.abstractAmong different local renewable resources, using battery energy storage (BES) has grown more than other technologies. The main reasons for this growth are flexibility and schedulability of BES. The fast ramp-rate of BES systems provides the opportunity of effective participation of these resources in the regulation ancillary service. However, continuous charging and discharging cycles of BES could decrease its lifetime and the expected profit, consequently. Therefore, the lifespan is a crucial parameter that shall be considered in the scheduling of BES. In this paper, an energy-constrained model is proposed for the scheduling of BES in joint energy and ancillary service markets. Moreover, the Energy Throughput (ET) concept is proposed for modeling the lifetime in the short-term scheduling strategy. In the proposed strategy, the uncertainties of energy prices in energy and regulation markets are modeled by Robust Optimization (RO) methodology. The scheduling problem is linearized and formulated based on the mixed-integer linear programming (MILP) method. The proposed model determines the optimal scheduling of BES based on the profit maximization, operational constraints, lifespan, and the defined risk level. Finally, the performance of model is evaluated vie case study results.pt_PT
dc.description.sponsorshipThis work has received funding from the EU Horizon 2020 research and innovation program under project TradeRES (grant agreement No 864276) and from FEDER Funds through COMPETE program and from National Funds through FCT under the projects UIDB/00760/2020 and CEECIND/02887/2017 CIND.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.ijepes.2021.107213pt_PT
dc.identifier.issn0142-0615
dc.identifier.urihttp://hdl.handle.net/10400.22/19396
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationCEECIND/02887/2017pt_PT
dc.relationResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S014206152100452X?via%3Dihubpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectBattery energy storagept_PT
dc.subjectEnergy throughputpt_PT
dc.subjectLifetimept_PT
dc.subjectRegulation servicept_PT
dc.subjectRobust optimizationpt_PT
dc.subjectUncertaintypt_PT
dc.titleEnergy-constrained model for scheduling of battery storage systems in joint energy and ancillary service markets based on the energy throughput conceptpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00760%2F2020/PT
oaire.citation.startPage107213pt_PT
oaire.citation.titleInternational Journal of Electrical Power & Energy Systemspt_PT
oaire.citation.volume133pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameFaria
person.familyNameVale
person.givenNamePedro
person.givenNameZita
person.identifier632184
person.identifier.ciencia-idB212-2309-F9C3
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0002-5982-8342
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id7004115775
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication35e6a4ab-f644-4bc5-b6fc-9fd89c23d6c6
relation.isAuthorOfPublicationff1df02d-0c0f-4db1-bf7d-78863a99420b
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