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Evaluation of different initial solution algorithms to be used in theheuristics optimization to solve the energy resource scheduling insmart grids

dc.contributor.authorSousa, Tiago
dc.contributor.authorMorais, Hugo
dc.contributor.authorCastro, Rui
dc.contributor.authorVale, Zita
dc.date.accessioned2017-01-25T11:58:37Z
dc.date.embargo2117
dc.date.issued2016
dc.description.abstractOver the last years, an increasing number of distributed resources have been connected to the powersystem due to the ambitious environmental targets, which resulted into a more complex operation ofthe power system. In the future, an even larger number of resources is expected to be coupled which willturn the day-ahead optimal resource scheduling problem into an even more difficult optimization prob-lem. Under these circumstances, metaheuristics can be used to address this optimization problem. Anadequate algorithm for generating a good initial solution can improve the metaheuristic’s performanceof finding a final solution near to the optimal than using a random initial solution. This paper proposestwo initial solution algorithms to be used by a metaheuristic technique (simulated annealing). Thesealgorithms are tested and evaluated with other published algorithms that obtain initial solution. Theproposed algorithms have been developed as modules to be more flexible their use by other metaheuris-tics than just simulated annealing. The simulated annealing with different initial solution algorithms hasbeen tested in a 37-bus distribution network with distributed resources, especially electric vehicles. Theproposed algorithms proved to present results very close to the optimal with a small difference between0.1%. A deterministic technique is used as comparison and it took around 26 h to obtain the optimal one.On the other hand, the simulated annealing was able of obtaining results around 1 min.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.asoc.2016.07.028pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/9394
dc.language.isoengpt_PT
dc.publisherElsevierpt_PT
dc.relation.ispartofseriesApplied Soft Computing;Vol. 48
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S1568494616303544pt_PT
dc.subjectElectric vehiclespt_PT
dc.subjectHybrid metaheuristicpt_PT
dc.subjectOptimal power schedulingpt_PT
dc.subjectSimulated annealingpt_PT
dc.subjectVirtual power playerpt_PT
dc.titleEvaluation of different initial solution algorithms to be used in theheuristics optimization to solve the energy resource scheduling insmart gridspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage506pt_PT
oaire.citation.startPage491pt_PT
oaire.citation.titleApplied Soft Computingpt_PT
oaire.citation.volume48pt_PT
person.familyNameMorais
person.familyNameVale
person.givenNameHugo
person.givenNameZita
person.identifier80878
person.identifier632184
person.identifier.ciencia-id2010-D878-271B
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0001-5906-4744
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id21834170800
person.identifier.scopus-author-id7004115775
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationb159f8c9-5ee1-444e-b890-81242ee0738e
relation.isAuthorOfPublicationff1df02d-0c0f-4db1-bf7d-78863a99420b
relation.isAuthorOfPublication.latestForDiscoveryb159f8c9-5ee1-444e-b890-81242ee0738e

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