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Solar radiation time-series prediction based on empirical mode decomposition and artificial neural networks

Zervakis Michalis, Petros-Fotios Alvanitopoulos, Nikolaos Nikolaidis, Ioannis Andreadis, Nikolaos Georgoulas

Απλή Εγγραφή

URIhttp://purl.tuc.gr/dl/dias/687B5ABB-AEDF-4B21-99B5-8A4F18BAF850-
Αναγνωριστικόhttps://doi.org/10.1007/978-3-662-44654-6_44-
Γλώσσαen-
Μέγεθος9 pagesen
ΤίτλοςSolar radiation time-series prediction based on empirical mode decomposition and artificial neural networksen
ΔημιουργόςZervakis Michalisen
ΔημιουργόςΖερβακης Μιχαληςel
ΔημιουργόςPetros-Fotios Alvanitopoulosen
ΔημιουργόςNikolaos Nikolaidisen
Δημιουργός Ioannis Andreadisen
Δημιουργός Nikolaos Georgoulasen
ΕκδότηςSpringer Verlagen
ΠερίληψηThis paper presents a new model for daily solar radiation prediction. In order to capture the hidden knowledge of existing data, a time-frequency analysis on past measurements of the solar energy density is carried out. The Hilbert-Huang transform (HHT) is employed for the representation of the daily solar irradiance time series. A set of physical measurements and simulated signals are selected for the time series analysis. The empirical mode decomposition is applied and the adaptive basis of each raw signal is extracted. The decomposed narrow-band amplitude and frequency modulated signals are modelled by using dynamic artificial neural networks (ANNs). Nonlinear autoregressive networks are trained with the average daily solar irradiance as exogenous (independent) input. The instantaneous value of solar radiation density is estimated based on previous values of the time series and previous values of the independent input. The results are promising and they reveal that the proposed system can be incorporated in intelligent systems for better load management in photovoltaic systems.en
ΤύποςΠλήρης Δημοσίευση σε Συνέδριοel
ΤύποςConference Full Paperen
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-10-25-
Ημερομηνία Δημοσίευσης2014-
Βιβλιογραφική ΑναφοράP. F. Alvanitopoulos, I. Andreadis, N. Georgoulas, M. Zervakis, N. Nikolaidis ,"Solar radiation time-series prediction based on empirical mode decomposition and artificial neural networks ," in 2014 10th IFIP WG 12.5 Inter.l Conf.,pp.447-455.doi:10.1007/978-3-662-44654-6_44en

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