Βέλτιστη τοποθέτηση μονάδων μέτρησης φασιθετών με ανοσοποιητικό γενετικό αλγόριθμο

Πουλιόπουλος, Αλκιβιάδης; Pouliopoulos, Alkiviadis

dc.contributor.author	Πουλιόπουλος, Αλκιβιάδης	el
dc.contributor.author	Pouliopoulos, Alkiviadis	en
dc.date.accessioned	2016-05-30T06:14:01Z
dc.date.available	2016-05-30T06:14:01Z
dc.date.issued	2016-05-30
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/42555
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.9913
dc.rights	Default License
dc.subject	Παρατηρησιμότητα δικτύου	el
dc.subject	Γενετικός αλγόριθμος	el
dc.subject	Ανοσοποιητικός γενετικός αλγόριθμος	el
dc.subject	Μονάδες μέτρησης φασιθετών	el
dc.subject	Βέλτιστη τοποθέτηση μονάδων μέτρησης φασιθετών	el
dc.subject	Network observability analysis	en
dc.subject	Genetic algorithm	en
dc.subject	Immunity genetic algorithm	en
dc.subject	Phasor measurement units	en
dc.subject	Optimal PMU placement (OPP) problem	en
dc.title	Βέλτιστη τοποθέτηση μονάδων μέτρησης φασιθετών με ανοσοποιητικό γενετικό αλγόριθμο	el
heal.type	bachelorThesis
heal.classification	Electrical engineering	en
heal.language	el
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2015-10-20
heal.abstract	The current Diploma Thesis deals with the optimal placement problem of Phasor Measurement Units (PMUs), in order to achieve full network observability. The objective of the Optimal PMU Placement (OPP) problem is to minimize the number of PMUs to be installed subject to full network observability. Initially, the Thesis presents the basic features of the PMU, the historical development of the PMU, as well as a comparison with the SCADA technology. Furthermore, this Thesis presents a topological method for full power system observability. Genetic Algorithm and Immunity Genetic Algorithm are proposed to solve the OPP combinatorial optimization problem. Genetic algorithms are meta-heuristic algorithms that mimic the process of natural selection. The proposed methods are implemented by developing appropriate software and graphical user interface (GUI) in MATLAB. The developed software was applied to IEEE 14, 30, 57 and 118-bus systems. The obtained results are analyzed and conclusions are drawn for the efficiency of the two methods.	en
heal.abstract	The current Diploma Thesis deals with the optimal placement problem of Phasor Measurement Units (PMUs), in order to achieve full network observability. The objective of the Optimal PMU Placement (OPP) problem is to minimize the number of PMUs to be installed subject to full network observability. Initially, the Thesis presents the basic features of the PMU, the historical development of the PMU, as well as a comparison with the SCADA technology. Furthermore, this Thesis presents a topological method for full power system observability. Genetic Algorithm and Immunity Genetic Algorithm are proposed to solve the OPP combinatorial optimization problem. Genetic algorithms are meta-heuristic algorithms that mimic the process of natural selection. The proposed methods are implemented by developing appropriate software and graphical user interface (GUI) in MATLAB. The developed software was applied to IEEE 14, 30, 57 and 118-bus systems. The obtained results are analyzed and conclusions are drawn for the efficiency of the two methods.	en
heal.advisorName	Γεωργιλάκης, Παύλος	el
heal.committeeMemberName	Γεωργιλάκης, Παύλος	el
heal.committeeMemberName	Κορρές, Γεώργιος	el
heal.committeeMemberName	Παπαθανασίου, Σταύρος	el
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών. Τομέας Ηλεκτρικής Ισχύος	el
heal.academicPublisherID	ntua
heal.numberOfPages	104 σ.	el
heal.fullTextAvailability	true