Title :
Long term multi-scale analysis of the daily peak load based on the Empirical Mode Decomposition
Author :
Mahmoud, M. Ould Mohamed ; Mhamdi, F. ; Jaïdane-Saïdane, M.
Author_Institution :
Signals & Syst. Res. Unit, Ecole Nat. d´´Ing. de Tunis (ENIT), Tunis, Tunisia
Abstract :
In this paper, an original technique to explore the long term load dynamics using a multi-scale analysis of the daily peak load based on the empirical mode decomposition (EMD) is presented. The signal is decomposed into intrinsic oscillatory components called intrinsic mode functions (IMFs). These modes are derived from the signal itself and not on a specific basis function. In this work, the EMD is used to extract and separate the suitable load component for long term forecast. Physical interpretations and statistical description of the modes are discussed. A comparison is made between load components extracted by the EMD approach and that of a classical multiple linear regression model. The load component predictability was investigated using the mutual information function. Real load data of the Tunisian power systems are used in this study.
Keywords :
load forecasting; regression analysis; classical multiple linear regression model; daily peak load; empirical mode decomposition; intrinsic mode functions; load component predictability; load forecast; long-term multiscale analysis; power systems; statistical mode description; Algorithm design and analysis; Data mining; Linear regression; Load forecasting; Load modeling; Mutual information; Power system analysis computing; Power system modeling; Predictive models; Weather forecasting; Load modeling; empirical mode decomposition; load analysis; model regression; predictability;
Conference_Titel :
PowerTech, 2009 IEEE Bucharest
Conference_Location :
Bucharest
Print_ISBN :
978-1-4244-2234-0
Electronic_ISBN :
978-1-4244-2235-7
DOI :
10.1109/PTC.2009.5281805