Transition Matrices for statistical representation of time-varying electrical signals – Application to wind generator currents

Autor: Ignatova, Vanya, Granjon, Pierre, Styczinski, Z., Seddik BACHA
Přispěvatelé: Laboratoire d'électrotechnique de Grenoble (LEG), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG), Laboratoire des images et des signaux (LIS), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Université Joseph Fourier - Grenoble 1 (UJF), Institut of Electrical Power Systems, Laboratoire de Génie Electrique de Grenoble (G2ELab), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS), Otto-von-Guericke University [Magdeburg] (OVGU), Garcia, Sylvie
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Zdroj: HAL
DIGESEC Critical Infrastructures Workshop
DIGESEC Critical Infrastructures Workshop, 2006, Magdeburg, Germany. 5 p
BASE-Bielefeld Academic Search Engine
CRIS
Critical Infrastructures Workshop
Critical Infrastructures Workshop, Dec 2006, Magdeburg, Germany
Popis: International audience; The development of the technology over the years and the liberalization of the en-ergy market have brought many technical and economical profits, but they have also modified power system operation. In order to accurately analyze the new op-erational conditions and characteristics, a voluminous measurement data are re-quired. It is, therefore, very important to store this data in efficient way without loosing any important information. This paper deals with the statistical description of measurement data. A matrix representation is chosen in order to preserve the information about the temporal evolution of the recorded signal. Two matrix forms are investigated: transitions probabilities (Markov) matrix and transitions number matrix. In order to evaluate the degree of preservation of the time information, two applications of the statisti-cal matrices are investigated: reconstruction and prediction. In deed, the availabil-ity of the information about the time evolution of the recorded data can be applied to restore the original signal from its corresponding matrix form. Another possible application is the forecasting of the electrical signals behaviour in the future. The methods are illustrated on real measurement data and applied in the case of wind generator measured currents.
Databáze: OpenAIRE
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