Wind power forecasting based on principle component phase space reconstruction

Renewable Energy

Volumn 81, Issue , 2015, Pages 737-744

  Han, Li ^a   Romero, Carlos E ^b   Yao, Zheng ^b  

^a CHINA UNIVERSITY OF MINING AND TECHNOLOGY   (China)

^b LEHIGH UNIVERSITY   (United States)

Author keywords

Phase space construction; Principle component analysis; Resource allocating networks; Wind power forecasting

Indexed keywords

DYNAMICAL SYSTEMS; ELECTRIC POWER TRANSMISSION NETWORKS; FORECASTING; NEURAL NETWORKS; PHASE SPACE METHODS; POWER MARKETS; PRINCIPAL COMPONENT ANALYSIS; WIND POWER;

ADAPTIVE WAVELET NEURAL NETWORK; NATIONAL RENEWABLE ENERGY LABORATORY; PHASE SPACE RECONSTRUCTION; PHASE SPACE RECONSTRUCTIONS (PSR); PHASE SPACES; PRINCIPLE COMPONENT ANALYSIS; RESOURCE ALLOCATING NETWORKS; WIND POWER FORECASTING;

WEATHER FORECASTING;

ELECTRICITY GENERATION; ERROR ANALYSIS; FORECASTING METHOD; NONLINEARITY; PERFORMANCE ASSESSMENT; PREDICTION; PRINCIPAL COMPONENT ANALYSIS; RECONSTRUCTION; RENEWABLE RESOURCE; RESOURCE ALLOCATION; WIND POWER;

EID: 84927737833     PISSN: 09601481     EISSN: 18790682     Source Type: Journal    
DOI: 10.1016/j.renene.2015.03.037     Document Type: Article

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