Abstract
Data accuracy and completeness of the wind farm has great significance in wind power research. Because of the wind farm in the process of gathering data and transmission appears distorted and missing, and that leads the accuracy and integrity of data is greatly reduced, so the need for a wind farm data, outlier detection and missing data imputation. This paper outlier detection by statistical method based on 3σ criterion under the normal distribution, and use of the effectiveness of the recently distance interpolation and regression interpolation for missing data, outliers and replacement and interpolation, filled after data and accuracy are improved.
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