Πρόβλεψη ηλεκτρικής κατανάλωσης σε σύμπλεγμα εμπορικών κτιρίων με την χρήση μεθόδων χρονικής συνάθροισης

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dc.contributor.author Φακίνος, Γεώργιος Ν. el
dc.contributor.author Fakinos, Georgios N. en
dc.date.accessioned 2016-09-09T09:12:45Z
dc.date.available 2016-09-09T09:12:45Z
dc.date.issued 2016-09-09
dc.identifier.uri http://dspace.lib.ntua.gr/xmlui/handle/123456789/43452
dc.identifier.uri http://dx.doi.org/10.26240/heal.ntua.12999
dc.rights Default License
dc.subject Ενέργεια el
dc.subject Μέθοδοι προβλέψεων el
dc.subject Χρονική συνάθροιση el
dc.subject Ιεραρχική συνάθροιση el
dc.subject Αξιολόγηση προβλέψεων el
dc.title Πρόβλεψη ηλεκτρικής κατανάλωσης σε σύμπλεγμα εμπορικών κτιρίων με την χρήση μεθόδων χρονικής συνάθροισης el
heal.type bachelorThesis
heal.classification Ενέργεια el
heal.classification Προβλέψεις el
heal.language el
heal.access free
heal.recordProvider ntua el
heal.publicationDate 2016-06-13
heal.abstract Εξατάζεται η πρόβλεψη κατανάλωσης ηλεκτρικής ενέργειας σε σύμπλεγμα εμπορικών κτιρίων. Γίνεται ο συνδυασμός μεθόδων ιεραρχικής (top down, bottom up, optimal) και χρονικής (MAPA) συνάθροισης με σκοπό να εξακριβωθεί το κατά πόσο συμβάλουν στην βελτίωση της ακρίβειας και στην μείωση της προκατάληψης των προβλέψεων. el
heal.abstract This paper examines the prediction electricity consumption buildings using temporal aggregation methods, i.e. the transition of the original data into multiple lower frequencies produce estimates in each of them separately. The aim is to ascertain to what extent these methods can help to achieve more accurate and unbiased estimations, taking advantage of the extra information that is hidden in each frequency studied. The study was done in a bank building complex and because the data we have are organized per energy use as well as per individual buildings of the bank the reconciliation of individual predictions is required to produce predictions at the lower levels of hierarchy summed in these higher. That requires the use of hierarchical data aggregation methods hierarchical aggregation). So the aim of this is to fill the gap that exists in the literature regarding production forecasts by combining temporal and hierarchical aggregation methods. In what ways can this be done and what will be the impact on the forecasts features are some of the questions that will be answered in this paper. What does energy consumption mean, what is the need and the steps taken for the study and this reduction and its importance for today's societies. Then we analyze the forecast methods, time series models and their characteristics and the analysis is done before the forecasting process. Aggregation methods and error indicators, that are used for the evaluation of methods, are then in depth analyzed. Finally we describe the methodology used in the study and briefly analyze the programming environment RStudio, which was used to export the results. To test the effect of the methods concerning the efficiency and accuracy of the forecast, a case study in five buildings of a bank is executed. en
heal.advisorName Ασημακόπουλος, Βασίλειος el
heal.advisorName Σπηλιώτης, Ευάγγελος el
heal.committeeMemberName Ασημακόπουλος, Βασίλειος el
heal.committeeMemberName Ψαρράς, Ιωάννης el
heal.committeeMemberName Ασκούνης, Δημήτριος el
heal.academicPublisher Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών. Τομέας Ηλεκτρικών Βιομηχανικών Διατάξεων και Συστημάτων Αποφάσεων el
heal.academicPublisherID ntua
heal.numberOfPages 94 σ.
heal.fullTextAvailability true

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