Short-term wind speed forecasting based on Gaussian process regression model

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering

Volumn 32, Issue 29, 2012, Pages 104-109

  Sun, Bin ^a   Yao, Haitao ^a   Liu, Ting ^b  

^a NORTHEAST ELECTRIC POWER UNIVERSITY   (China)

^b Equipment Research Institute of Air Force   (China)

Author keywords

Forecasting; Gaussian process; Phase space reconstruction; Wind speed time series

Indexed keywords

ELECTRIC POWER GENERATION; ELECTRIC POWER TRANSMISSION NETWORKS; ELECTRIC UTILITIES; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); NEURAL NETWORKS; PHASE SPACE METHODS; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES; TIME SERIES; WIND EFFECTS; WIND POWER;

ADVERSE EFFECT; AUTOCORRELATION METHODS; BAYESIAN FRAMEWORKS; BP NEURAL NETWORKS; COMPETITION ABILITY; COVARIANCE FUNCTION; DELAY TIME; ELECTRICITY MARKET; EMBEDDING DIMENSIONS; ENGINEERING PRACTICES; FALSE NEIGHBORS; FORECASTING ACCURACY; GAUSSIAN PROCESS; GAUSSIAN PROCESS REGRESSION MODEL; GAUSSIAN PROCESSES; GRID-CONNECTED; LEAST SQUARES SUPPORT VECTOR MACHINES; PHASE SPACE RECONSTRUCTION; POWER GRIDS; SHORT-TERM WIND SPEED FORECASTING; WIND FARM; WIND POWER GENERATION SYSTEMS; WIND SPEED; WIND SPEED FORECASTING;

FORECASTING;

EID: 84869854408     PISSN: 02588013     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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