A Prediction Method for Wind Speed Based on the Correlation Analysis of Measured Data of Adjacent Wind Turbine
| Autor: | Yinsong Wang, Ziqing Su |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Correlation coefficient
Computer science Astrophysics::High Energy Astrophysical Phenomena Turbine Wind speed Pearson product-moment correlation coefficient symbols.namesake Wind profile power law Physics::Space Physics Redundancy (engineering) symbols Astrophysics::Solar and Stellar Astrophysics Time series Physics::Atmospheric and Oceanic Physics Reliability (statistics) Marine engineering |
| Zdroj: | Proceedings of the 2015 Chinese Intelligent Automation Conference ISBN: 9783662464687 |
| DOI: | 10.1007/978-3-662-46469-4_9 |
| Popis: | Wind speed prediction is very important for the control of wind power generation. Former studies for wind speed prediction are limited to measuring their own historical data to achieve the future wind speed prediction. Compared with this situation, this paper presents a prediction method to get the specified point’s wind speed predicting value from the adjacent point’s historical wind speed data. Using Pearson correlation coefficient to show the relativity between the adjacent measuring points, the method of regression analysis based on correlation coefficient is introduced, and we chose the wind speed data of ten points from an actual wind field to simulate and verify this method. Simulation result shows that this method can guarantee the accuracy of wind forecasting, and it can improve the redundancy and reliability of wind measuring equipments effectively. |
| Databáze: | OpenAIRE |
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