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Short-term load forecasting based on the Kalman filter and the neural-fuzzy network (ANFIS)

Stavrakakis Georgios, Triantafyllia G. Nikolaou, Stelios A. Markoulakis

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URIhttp://purl.tuc.gr/dl/dias/792573C3-2104-49B5-BCE1-92F6C106EA37-
Αναγνωριστικόhttp://www.wseas.us/e-library/conferences/2006evia/papers/516-164.pdf-
Γλώσσαen-
Μέγεθος5 pagesen
ΤίτλοςShort-term load forecasting based on the Kalman filter and the neural-fuzzy network (ANFIS)en
ΔημιουργόςStavrakakis Georgiosen
ΔημιουργόςΣταυρακακης Γεωργιοςel
ΔημιουργόςTriantafyllia G. Nikolaouen
ΔημιουργόςStelios A. Markoulakisen
ΠερίληψηIn this article the possibilities of the KALMAN filter as well as the neural-fuzzy network ANFIS (adaptive neural-fuzzy inference system) for the short-term load forecasting are presented and compared. In any case, the load forecasting for one entire day as well as the load forecasting for one or more hours ahead are possible. The approach followed in this case is as follows: considering that the medium hourly load is divided in 24 distinguishable time series (each time-series concerns the load history for one concrete hour of the day in the duration of a year).One can take the corresponding 24 models (distinguishable between them) aiming at the forecast of the medium hourly electric load for each hour separately. The evaluation of the precision (quality) of the forecasts is realised via their comparison with the corresponding real values of the hourly load of the electric consumption of the Crete Island, which have not been used for the training of the forecast modelsen
ΤύποςΠλήρης Δημοσίευση σε Συνέδριοel
ΤύποςConference Full Paperen
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-10-16-
Ημερομηνία Δημοσίευσης2006-
Θεματική ΚατηγορίαElectric island networksen
Θεματική Κατηγορίαisland networks electricityen
Θεματική Κατηγορίαelectric island networksen
Βιβλιογραφική ΑναφοράT. G . Nikolaou, G.S. Stavrakakis ,S. E. Markoulakis.(2006).Short-term load forecasting based on the Kalman filter and the neural-fuzzy network (ANFIS).Presented at International Conference on Energy and Environmental Systems. [online].Available:http://www.wseas.us/e-library/conferences/2006evia/papers/516-164.pdfen

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