A novel Coral Reefs Optimization algorithm with substrate layers for optimal battery scheduling optimization in micro-grids

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dc.contributor.authorSalcedo-Sanz, S.
dc.contributor.authorCamacho-Gómez, C.
dc.contributor.authorMallol-Poyato, R.
dc.contributor.authorJiménez-Fernández, S.
dc.contributor.authorDel Ser, J.
dc.contributor.institutionIA
dc.date.accessioned2024-07-24T12:02:54Z
dc.date.available2024-07-24T12:02:54Z
dc.date.issued2016-11-01
dc.descriptionPublisher Copyright: © 2016, Springer-Verlag Berlin Heidelberg.
dc.description.abstractIn this paper we propose a Coral Reefs Optimization algorithm with substrate layers (CRO-SL) to tackle the battery scheduling optimization problem in micro-grids (MGs). Specifically, we consider a MG that includes renewable generation and different loads, defined by their power profiles, and is equipped with an energy storage device (battery) to address its scheduling (charge/discharge duration and occurrence) in a real scenario of variable electricity prices. The CRO-SL is a recently proposed meta-heuristic which promotes co-evolution of different exploration models within a unique population. We fully describe the proposed CRO-SL algorithm, including its initialization and the different operators implemented in the algorithm. Experiments in a real MG scenario are carried out. To show the good battery scheduling performance of the proposed CRO-SL, we have compared the results with what we called a deterministic procedure. The deterministic charge/discharge approach is defined as a fixed way of using the energy storage device that only depends on the pattern of the loads and generation profiles considered. Hourly values of both generation and consumption profiles have been considered, and the good performance of the proposed CRO-SL is shown for four different weeks of the year (one per season), where the effect of the battery scheduling optimization obtains savings up 10 % of the total electricity cost in the MG, when compared with the deterministic procedure.en
dc.description.sponsorshipThis work has been partially funding by the Spanish Ministerial Commission of Science and Technology, MICYT, Grant Number: TIN2014-54583-C2-2-R and Comunidad de Madrid, Grant Number: S2013ICE-2933_02.
dc.description.statusPeer reviewed
dc.format.extent14
dc.identifier.citationSalcedo-Sanz , S , Camacho-Gómez , C , Mallol-Poyato , R , Jiménez-Fernández , S & Del Ser , J 2016 , ' A novel Coral Reefs Optimization algorithm with substrate layers for optimal battery scheduling optimization in micro-grids ' , Soft Computing , vol. 20 , no. 11 , pp. 4287-4300 . https://doi.org/10.1007/s00500-016-2295-7
dc.identifier.doi10.1007/s00500-016-2295-7
dc.identifier.issn1432-7643
dc.identifier.urihttps://hdl.handle.net/11556/3294
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=84981187923&partnerID=8YFLogxK
dc.language.isoeng
dc.relation.ispartofSoft Computing
dc.relation.projectIDSpanish Ministerial Commission of Science and Technology
dc.relation.projectIDComunidad de Madrid, S2013ICE-2933_02
dc.relation.projectIDMinisterio de Ciencia y Tecnología, MICYT, TIN2014-54583-C2-2-R
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsBattery scheduling optimization
dc.subject.keywordsCoral Reefs Optimization algorithm
dc.subject.keywordsMeta-heuristics
dc.subject.keywordsMicro-grid
dc.subject.keywordsTheoretical Computer Science
dc.subject.keywordsSoftware
dc.subject.keywordsGeometry and Topology
dc.titleA novel Coral Reefs Optimization algorithm with substrate layers for optimal battery scheduling optimization in micro-gridsen
dc.typejournal article
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