Wind Power Plant Prediction by Using Neural Networks
Conference
·
· IEEE Energy Conversion Congress and Exposition (ECCE)
This paper introduces a method of short-term wind power prediction for a wind power plant by training neural networks based on historical data of wind speed and wind direction. The model proposed is shown to achieve a high accuracy with respect to the measured data.
- Research Organization:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
- DOE Contract Number:
- AC36-08GO28308
- OSTI ID:
- 1050093
- Report Number(s):
- NREL/CP-5500-55871; TRN: US201218%%467
- Journal Information:
- IEEE Energy Conversion Congress and Exposition (ECCE), Vol. 2012; Conference: IEEE Energy Conversion Conference and Exposition, Raleigh, NC (United States), 15-20 Sep 2012; ISSN 2329-3721
- Publisher:
- IEEE
- Country of Publication:
- United States
- Language:
- English
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