Research on Historical Data Model of Wind Farm Based on Computer Missing Data Processing Algorithm

In order to ensure the safe and reliable transmission of wind turbines in the power grid, this topic studies the Kafka wireless communication technology. It can effectively restrain all kinds of unstable factors brought about by power grid operation. This paper realizes the effective protection of power grid signal. Then, the paper uses Thompson quartile method and multi-point interpolation technique to process the abnormal data. First, the abnormal energy value that is cut out or close to 0. It is removed at two different positions of cut out, and it is partitioned. The outliers are partitioned and finely cleaned by Thompson quartile method to reduce the modeling complexity in the process of recognition. The four-point interpolation technique is used to reconstruct the anomaly observation data, and the complete data of wind speed and power are obtained. The practical application and experiment show that the proposed scheme can not only effectively overcome the current network instability, high concurrency and other problems, but also has the advantages of large capacity, high transmission efficiency and scalability. The research results of this project will lay the foundation for the secure and stable transmission of data in the field of wind power, and will also provide a new research method for the relevant information processing in the power sector.