A new chaotic time series hybrid prediction method of wind power based on EEMD-SE and full-parameters continued fraction

Energy

Volumn 138, Issue , 2017, Pages 977-990

  Wang, Cong ^a   Zhang, Hongli ^a   Fan, Wenhui ^b   Ma, Ping ^a  

^a XINJIANG UNIVERSITY   (China)

^b TSINGHUA UNIVERSITY   (China)

Author keywords

EEMD SE; Full parameters continued fraction; Primal dual state transition algorithm; Wind power prediction

Indexed keywords

ELECTRIC POWER GENERATION; FORECASTING; PARAMETER ESTIMATION; TIME SERIES; WIND POWER;

CHAOTIC TIME SERIES PREDICTION; CONTINUED FRACTION; ENSEMBLE EMPIRICAL MODE DECOMPOSITION; FORECAST IMPROVEMENTS; FORECASTING MODELING; INVERSE DIFFERENCES; STATE TRANSITIONS; WIND POWER PREDICTIONS;

WEATHER FORECASTING;

ALGORITHM; CHAOTIC DYNAMICS; EMPIRICAL ANALYSIS; ENSEMBLE FORECASTING; ERROR ANALYSIS; MODEL TEST; OPTIMIZATION; POWER GENERATION; PREDICTION; TIME SERIES; WIND POWER;

CHINA; XINJIANG UYGUR;

EID: 85026436770     PISSN: 03605442     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.energy.2017.07.112     Document Type: Article

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