Hybrid Kalman algorithms for very short-term load forecasting and confidence interval estimation

IEEE PES General Meeting, PES 2010

Volumn , Issue , 2010, Pages

  Guan, Che ^a   Luh, Peter B ^a   Michel, Laurent D ^b   Coolbeth, Matthew A ^b   Friedland, Peter B ^c  

^a UNIVERSITY OF CONNECTICUT   (United States)

^b University of Connecticut   (United States)

^c ISO New England   (United States)

Author keywords

Confidence interval estimation; Extended Kalman filter; Multilevel wavelet neural networks; Unscented Kalman filter; Very short term load forecasting

Indexed keywords

ACCURATE PREDICTION; COMPLEX LOADS; CONFIDENCE INTERVAL; CONFIDENCE INTERVAL ESTIMATION; DIFFERENT FREQUENCY; FORECASTING ACCURACY; HIGH FREQUENCY COMPONENTS; INDIVIDUAL NETWORK; INPUT-OUTPUT FUNCTION; LOAD COMPONENTS; LOAD PREDICTIONS; LOW-FREQUENCY COMPONENTS; MULTI-LEVEL; MULTILEVEL WAVELET NEURAL NETWORKS; NONLINEAR INPUTS; NUMERICAL TESTING; RESOURCE DISPATCH; SHORT TERM LOAD FORECASTING; UNSCENTED KALMAN FILTER; WAVELET NEURAL NETWORKS;

ALGORITHMS; ELECTRIC LOAD FORECASTING; ESTIMATION; EXTENDED KALMAN FILTERS; LOAD TESTING; MATHEMATICAL OPERATORS; NONLINEAR FILTERING; POSITION CONTROL; POWER TRANSFORMERS;

NEURAL NETWORKS;

EID: 78649617768     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PES.2010.5590077     Document Type: Conference Paper

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