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Development of optimization algorithms for the Leaf Community microgrid

Provata Eleni, Kolokotsa Dionysia, Sotirios Papantoniou, Pietrini Maila, Giovannelli Antonio , Romiti Gino

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URIhttp://purl.tuc.gr/dl/dias/6A9A9A38-9975-4096-89BA-A58FA28501B5-
Identifierhttps://doi.org/10.1016/j.renene.2014.08.080-
Languageen-
Extent13en
TitleDevelopment of optimization algorithms for the Leaf Community microgriden
CreatorProvata Elenien
CreatorΠροβατα Ελενηel
CreatorKolokotsa Dionysiaen
CreatorΚολοκοτσα Διονυσιαel
CreatorSotirios Papantoniouen
CreatorΠαπαντωνιου Σωτηριοςel
Creator Pietrini Mailaen
CreatorGiovannelli Antonio en
Creator Romiti Ginoen
PublisherElsevieren
DescriptionΔημοσίευση σε επιστημονικό περιοδικό el
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 (ESS). 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 model, some scenarios were tested. This study concludes that a management of a microgrid can achieve energy and money savings.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-11-05-
Date of Publication2015-
SubjectMicrogriden
SubjectOptimizationen
SubjectNeural networksen
Bibliographic CitationE. Provata, D. Kolokotsa, S. Papantoniou, M. Pietrini, A. Giovannelli, G. Romiti, "Development of optimization algorithms for the Leaf Community microgrid," Renewable Energy, vol. 74, pp. 782–795, Feb. 2015. doi: 10.1016/j.renene.2014.08.080en

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