Very short term wind power prediction: A data mining approach

IEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES

Volumn , Issue , 2008, Pages

  Negnevitsky, M ^a,b   Johnson, P ^a,b  

^a IEEE

^b UNIVERSITY OF TASMANIA   (Australia)

Author keywords

Data generation; Data mining; Intelligent systems; Very short term forecasting; Wind power

Indexed keywords

DECISION SUPPORT SYSTEMS; ELECTRIC LOAD FORECASTING; ENERGY CONVERSION; FORECASTING; INFORMATION MANAGEMENT; POTENTIAL ENERGY; POTENTIAL ENERGY SURFACES; RENEWABLE ENERGY RESOURCES; SEARCH ENGINES;

21ST CENTURY; APPROPRIATE TECHNIQUES; DATA AVAILABILITY; DATA CHARACTERISTICS; DATA GENERATION; DATA MINING; ELECTRICAL ENERGY; GENERIC APPROACHES; INTELLIGENT SYSTEMS; SHORT TERM; TIME FRAMES; VERY SHORT TERM FORECASTING; WIND POWER FORECASTING; WIND POWER PREDICTION;

WIND POWER;

EID: 52349118133     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PES.2008.4596604     Document Type: Conference Paper

References (9)

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8. M. Negnevitsky and C. W. Potter, "Innovative shortterm wind generation prediction techniques," in Proceedings of the IEEE/PES General Meeting. Montreal, Canada: IEEE, 2006.
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