A kind of wind direction clustering method, device and electronic equipment

A wind direction and clustering technology, applied in the field of data clustering, can solve problems such as inapplicability, achieve the effect of ensuring reliability and authenticity, and avoiding subjectivity
CN113052256BActive Publication Date: 2022-07-19NORTH CHINA ELECTRIC POWER UNIV (BAODING) +1
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Patents(China)
Current Assignee / Owner
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
Publication Date
2022-07-19

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Abstract

The invention provides a wind direction clustering method, device and electronic equipment, wherein the method includes: acquiring periodic wind direction data of each wind turbine in a wind farm; determining a similarity measure index suitable for the periodic wind direction data according to the periodic wind direction data ; Based on the similarity measurement index, select k cluster centers, and divide the periodic wind direction data into k clusters; determine the error sum of squares criterion function based on the periodic wind direction data; The clustering effect is evaluated to determine the final clustering effect. Among them, the similarity measurement index and the error sum of squares criterion function suitable for the periodic wind direction data are determined by the periodic wind direction data, which solves the disadvantage that the traditional K-means algorithm is not suitable for the periodic wind direction data clustering, and ensures the clustering results. reliability and authenticity, and reliable and reasonable fan division can be obtained according to the clustering results, avoiding the subjectivity of artificial division of sectors.
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Description

technical field

[0001] The present invention relates to the technical field of data clustering, and in particular, to a wind direction clustering method, device and electronic equipment. Background technique

[0002] At present, my country's wind power generation is in a period of rapid and steady development. However, wind energy has randomness and volatility, resulting in greater uncertainty in the output power of wind farms. Existing research mainly focuses on the influence of wind speed characteristics on wind power output, and wind direction is also an important factor affecting wind power output. In the study of wind direction factors, in order to avoid the disadvantage of artificial division of sectors with a certain degree of subjectivity, a clustering algorithm is used to cluster the wind direction data recorded by the fan data acquisition and monitoring system, and the wind direction sectors are divided according to the clustering results.

[0003] Commonly used c...

Claims

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