Assessing Long-Term Wind Conditions by Combining Different Measure-Correlate-Predict Algorithms: Preprint
This paper significantly advances the hybrid measure-correlate-predict (MCP) methodology, enabling it to account for variations of both wind speed and direction. The advanced hybrid MCP method uses the recorded data of multiple reference stations to estimate the long-term wind condition at a target wind plant site. The results show that the accuracy of the hybrid MCP method is highly sensitive to the combination of the individual MCP algorithms and reference stations. It was also found that the best combination of MCP algorithms varies based on the length of the correlation period.
- Publication Date:
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- Resource Relation:
- Conference: To be presented at the ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 4-7 August 2013, Portland, Oregon
- Research Org:
- National Renewable Energy Laboratory (NREL), Golden, CO.
- Sponsoring Org:
- USDOE Office of Energy Efficiency and Renewable Energy Wind Power Program
- Country of Publication:
- United States
- 17 WIND ENERGY POWER GENERATION; RENEWABLE ENERGY; WIND DISTRIBUTION; WIND RESOURCE ASSESSMENT; NATIONAL RENEWABLE ENERGY LABORATORY; NREL; Wind Energy
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