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Development of optimization algorithms for a smart grid community

Provata Eleni

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URIhttp://purl.tuc.gr/dl/dias/32E4BEEA-C3FE-4E15-8562-C1028B8BCFBA-
Identifierhttps://doi.org/10.26233/heallink.tuc.23781-
Languageen-
Extent111 pagesen
TitleDevelopment of optimization algorithms for a smart grid communityen
CreatorProvata Elenien
CreatorΠροβατα Ελενηel
Contributor [Thesis Supervisor]Kolokotsa Dionysiaen
Contributor [Thesis Supervisor]Κολοκοτσα Διονυσιαel
Contributor [Committee Member]Kalaitzakis Konstantinosen
Contributor [Committee Member]Καλαϊτζακης Κωνσταντινοςel
Contributor [Committee Member]Karatzas Giorgosen
Contributor [Committee Member]Καρατζας Γιωργοςel
PublisherTechnical University of Creteen
PublisherΠολυτεχνείο Κρήτηςel
Academic UnitTechnical University of Crete::School of Environmental Engineeringen
Academic UnitΠολυτεχνείο Κρήτης::Σχολή Μηχανικών Περιβάλλοντοςel
Content SummaryThe aim of this work is the development of an optimization model in order to minimize the cost of Leaf Community microgrid. This cost is a sum of energy cost and the maintenance cost of the Energy storage system. The developed objective function is constrained and the problem here is solved by using the method of genetic algorithms at Matlab. The genetic algorithm decides about the transportation of the energy from or to the ESS and it calculates an optimum cost. The optimization time horizon is 24 h ahead, thus the prediction of energy production and consumption was necessary. This was achieved by using neural networks. In order to verify the performance of the developed optimization model, some scenarios were tested evaluated. This study concludes that a management of a microgrid can achieve energy and money savings. en
Type of ItemΜεταπτυχιακή Διατριβήel
Type of ItemMaster Thesisen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2014-12-15-
Date of Publication2014-
SubjectGreen energy investmenten
SubjectInvestment in clean energyen
Subjectclean energy investmenten
Subjectgreen energy investmenten
Subjectinvestment in clean energyen
SubjectOptimization, Constraineden
Subjectconstrained optimizationen
Subjectoptimization constraineden
SubjectIndustrial energy consumptionen
Subjectindustries energy consumptionen
Subjectindustrial energy consumptionen
SubjectArtificial neural networksen
SubjectNets, Neural (Computer science)en
SubjectNetworks, Neural (Computer science)en
SubjectNeural nets (Computer science)en
Subjectneural networks computer scienceen
Subjectartificial neural networksen
Subjectnets neural computer scienceen
Subjectnetworks neural computer scienceen
Subjectneural nets computer scienceen
SubjectAlternate energy sourcesen
SubjectAlternative energy sourcesen
SubjectEnergy sources, Renewableen
SubjectRenewable energy resourcesen
SubjectSustainable energy sourcesen
Subjectrenewable energy sourcesen
Subjectalternate energy sourcesen
Subjectalternative energy sourcesen
Subjectenergy sources renewableen
Subjectrenewable energy resourcesen
Subjectsustainable energy sourcesen
Bibliographic CitationEleni Provata, "Development of optimization algorithms for a smart grid community", Master Thesis, School of Environmental Engineering, Technical University of Crete, Chania, Greece, 2014en
Bibliographic CitationΕλένη Προβατά, "Development of optimization algorithms for a smart grid community", Μεταπτυχιακή Διατριβή, Σχολή Μηχανικών Περιβάλλοντος, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2014el

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