Short-term wind power forecasting and uncertainty analysis using a hybrid intelligent method

IET Renewable Power Generation

Volumn 11, Issue 5, 2017, Pages 678-687

  Huang, Chao Ming ^a   Kuo, Chung Jen ^a   Huang, Yann Chang ^b  

^a KUN SHAN UNIVERSITY   (Taiwan)

^b CHENG SHIU UNIVERSITY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTRIC POWER GENERATION; FORECASTING; REGRESSION ANALYSIS; RISK ASSESSMENT; UNCERTAINTY ANALYSIS; WEATHER FORECASTING; WIND; WIND EFFECTS; WIND POWER; WIND TURBINES;

CENTRAL WEATHER BUREAUX; CONFIDENCE INTERVAL; FORECASTING ACCURACY; HYBRID INTELLIGENT METHOD; SHORT-TERM WIND POWER FORECASTING; SUPPORT VECTOR REGRESSION (SVR); WIND POWER GENERATION SYSTEMS; WIND POWER PREDICTIONS;

ELECTRIC POWER TRANSMISSION NETWORKS;

EID: 85019740878     PISSN: 17521416     EISSN: 17521424     Source Type: Journal    
DOI: 10.1049/iet-rpg.2016.0672     Document Type: Article

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