Method and device for judging abnormal wind speed data

Abstract

Provided is a method and device for judging abnormal wind speed data, the method comprising: obtaining historical wind speed data within a predetermined time period at predetermined time intervals, and calculating a first difference value between historical wind speed data at adjacent time points; Segment the historical wind speed data and the first differential value respectively, and count the distribution quantity of the historical wind speed data in each differential segment in each wind speed segment; obtain a predetermined number of wind speed data to be measured according to the predetermined time interval, and calculate The second differential value between the wind speed data to be measured at adjacent time points; calculate the average value of the absolute value of the second differential value calculated for all the wind speed data to be measured; based on the historical wind speed data and each wind speed data to be measured Corresponding to the quantity distributed in each difference segment in each wind speed segment, calculate the difference threshold; if the calculated average value is greater than the difference threshold, then determine that the predetermined number of wind speed data to be measured is abnormal wind speed data.

Description

technical field [0001] The present invention relates to the field related to wind, in particular to a method and device for judging whether the wind speed data to be measured is abnormal data by using historical wind speed data. Background technique [0002] With the large-scale development of wind power, wind power has gradually become an important energy role, and the total installed capacity of wind power is also increasing. And our understanding of wind is getting deeper and deeper with the development of wind power. In fields related to wind power, meteorology, and other wind-related fields, it is necessary to monitor the wind speed data collected by sensors in real time. Therefore, we often need to be able to find out whether the wind speed measurement data is abnormal in time during the process of real-time wind speed measurement. [0003] In the actual judgment process, some special outliers can be easily judged, for example, the measured wind speed is a negative n...

AI Technical Summary

Problems solved by technology

But there are still times when the judgment of outliers is not an easy task.

Because the wind speed is changing all the time, its value has been fluctuating randomly. It may be a normal phenomenon that it becomes larger or smaller at a certain moment, and it cannot be directly judged as an abnormality.

Therefore, it is difficult for us to determine whether a wind speed data within the normal value range is a real fluctuation, or an abnormal value caused by instrument error, network transmission and other problems

[0004] In reality, there are very few in-depth studies on wind speed outlier monitoring methods. Generally, it is only for the judgment of particularly obvious outliers, and does not involve the judgment of non-obvious anomalies.

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