Blind Kalman Filtering for Short-Term Load Forecasting

In this work we address the problem of short-term load forecasting. We propose a generalization of the linear state-space model where the evolution of the state and the observation matrices is unknown. The proposed blind Kalman filter algorithm proceeds via alternating the estimation of these unknow...

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Veröffentlicht in:	IEEE transactions on power systems Jg. 35; H. 6; S. 4916 - 4919
Hauptverfasser:	Sharma, Shalini, Majumdar, Angshul, Elvira, Victor, Chouzenoux, Emilie
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.11.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Institute of Electrical and Electronics Engineers
Schlagworte:	Algorithms Batch processing Computer Science Electric power Engineering Sciences expectation-minimization algorithm Filtering algorithms Forecasting Kalman filtering Kalman filters Load forecasting Load modeling Machine Learning Peak load Signal and Image processing State space models State-space methods state-space model state-space model Kalman filtering expectation-minimization algorithm load forecasting
ISSN:	0885-8950, 1558-0679
Online-Zugang:	Volltext
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