A new wind power prediction method based on chaotic theory and Bernstein Neural Network

Energy

Volumn 117, Issue , 2016, Pages 259-271

  Wang, Cong ^a   Zhang, Hongli ^a   Fan, Wenhui ^b   Fan, Xiaochao ^a  

^a XINJIANG UNIVERSITY   (China)

^b TSINGHUA UNIVERSITY   (China)

Author keywords

Bernstein neural network; Chaotic theory; Primal dual; State transition algorithm; Wind power prediction

Indexed keywords

CHAOS THEORY; ELECTRIC POWER GENERATION; ELECTRIC POWER SYSTEM ECONOMICS; ERRORS; FORECASTING; LYAPUNOV METHODS; PHASE SPACE METHODS; WIND POWER;

CHAOTIC THEORY; LARGEST LYAPUNOV EXPONENT; PHASE SPACE RECONSTRUCTIONS (PSR); PRIMAL-DUAL; SECURITY AND ECONOMIES; STATE TRANSITIONS; WIND POWER FORECASTING; WIND POWER PREDICTIONS;

WEATHER FORECASTING;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; CHAOS THEORY; POWER GENERATION; PREDICTION; WIND POWER;

EID: 84994037319     PISSN: 03605442     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.energy.2016.10.041     Document Type: Article

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