A novel hybrid approach for predicting wind farm power production based on wavelet transform, hybrid neural networks and imperialist competitive algorithm

Energy Conversion and Management

Volumn 121, Issue , 2016, Pages 232-240

  Aghajani, Afshin ^a   Kazemzadeh, Rasool ^a   Ebrahimi, Afshin ^a  

^a SAHAND UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Forecasting engine; Imperialist competitive algorithm; Neural networks; Wavelet transform; Wind power forecasting

Indexed keywords

ALGORITHMS; BAYESIAN NETWORKS; ELECTRIC POWER SYSTEM INTERCONNECTION; ELECTRIC POWER SYSTEMS; ELECTRIC UTILITIES; ENGINES; ERRORS; FORECASTING; HEURISTIC METHODS; MEAN SQUARE ERROR; MULTILAYER NEURAL NETWORKS; NEURAL NETWORKS; NONLINEAR PROGRAMMING; OPTIMIZATION; RADIAL BASIS FUNCTION NETWORKS; WAVELET TRANSFORMS; WIND; WIND EFFECTS; WIND POWER;

BROYDEN-FLETCHER-GOLDFARB-SHANNO; ELECTRIC POWER PRODUCTION; IMPERIALIST COMPETITIVE ALGORITHM (ICA); IMPERIALIST COMPETITIVE ALGORITHMS; MEAN ABSOLUTE PERCENTAGE ERROR; MULTILAYER PERCEPTRON NEURAL NETWORKS; RADIAL BASIS FUNCTION NEURAL NETWORKS; WIND POWER FORECASTING;

WEATHER FORECASTING;

EID: 84969542921     PISSN: 01968904     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enconman.2016.05.024     Document Type: Article

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