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Distributed energy resource short-term scheduling using signaled particle swarm optimization

2012Journal article Open access
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dc.contributor.authorSoares, João
dc.contributor.authorSilva, Marco
dc.contributor.authorSousa, Tiago
dc.contributor.authorVale, Zita
dc.contributor.authorMorais, H.
dc.date.accessioned2013-04-16T14:45:07Z
dc.date.available2013-04-16T14:45:07Z
dc.date.issued2012
dc.date.updated2013-04-12T10:52:34Z
dc.description.abstractDistributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.por
dc.identifier.doi10.1016/j.energy.2012.03.022pt_PT
dc.identifier.issn0360-5442
dc.identifier.urihttp://hdl.handle.net/10400.22/1360
dc.language.isoengpor
dc.publisherElsevierpor
dc.relation.ispartofseriesEnergy; Vol. 42, Issue 1
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S0360544212002137por
dc.subjectDistributed energy resource schedulingpor
dc.subjectMixed integer non-linear programmingpor
dc.subjectParticle swarm optimizationpor
dc.subjectShort-term schedulingpor
dc.titleDistributed energy resource short-term scheduling using signaled particle swarm optimizationpor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issueIssue 1
oaire.citation.titleEnergy
oaire.citation.volumeVol. 42
person.familyNameSoares
person.familyNameVale
person.givenNameJoão
person.givenNameZita
person.identifier1043580
person.identifier632184
person.identifier.ciencia-id1612-8EA8-D0E8
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0002-4172-4502
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id35436109600
person.identifier.scopus-author-id7004115775
rcaap.rightsopenAccesspor
rcaap.typearticlepor
relation.isAuthorOfPublication9ece308b-6d79-4cec-af91-f2278dcc47eb
relation.isAuthorOfPublicationff1df02d-0c0f-4db1-bf7d-78863a99420b
relation.isAuthorOfPublication.latestForDiscoveryff1df02d-0c0f-4db1-bf7d-78863a99420b

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