Short-term prediction of wind power with a clustering approach

Renewable Energy

Volumn 35, Issue 10, 2010, Pages 2362-2369

  Kusiak, Andrew ^a   Li, Wenyan ^a  

^a UNIVERSITY OF IOWA   (United States)

Author keywords

Clustering; Data mining; Parameter selection; Power prediction; Wind energy; Wind turbine

Indexed keywords

CLUSTERING APPROACH; CLUSTERING DATA; COMPUTATIONAL RESULTS; COMPUTATIONAL TIME; INPUT SPACE; K-MEANS CLUSTERING ALGORITHM; LOW WIND SPEED; PARAMETER SELECTION; PREDICTION ACCURACY; PREDICTION MODEL; SHORT TERM PREDICTION; TIME PERIODS; WIND ENERGY;

CLUSTERING ALGORITHMS; FORECASTING; MATHEMATICAL MODELS; WIND TURBINES;

WIND POWER;

CLUSTER ANALYSIS; DATA MINING; EXPERIMENTAL STUDY; PREDICTION; WIND POWER; WIND TURBINE;

EID: 77954863780     PISSN: 09601481     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.renene.2010.03.027     Document Type: Article

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