Wind turbine generator system state monitoring system data compressing method

Abstract

The invention provides a data modeling based wind turbine generator system state monitoring system data compressing method. Monitoring data are subjected to mathematical modeling in a local wind turbine generator system so as to extract strong features and compress and restore data in a high compression ratio mode. The method includes the following steps of wind power state monitoring data collection, wind turbine generator system operation condition identification, wind power state monitoring data screen, monitoring data information local settlement, wind power state storage mode selection, intelligent modeling structure identification matching, intelligent modeling structure parameter estimation, monitoring data local primary processing, and upper monitoring terminal secondary processing. By means of the wind turbine generator system state monitoring system data compressing method, problems existing in on-line transmission and long-term continuous monitoring and storage of mass data are solved.

Description

technical field [0001] The invention belongs to the technical field of wind power generation, in particular to the technical field of data compression for a state monitoring system of a wind power generating set for data modeling. Background technique [0002] In the existing monitoring methods of wind power generation status, the status monitoring system of wind power generating units needs to monitor the status information of all units in the wind farm, and the amount of monitoring is huge. Therefore, if you want to reflect the state changes of wind power generation units through continuous state monitoring, you need to store a large amount of long-term monitoring data, which requires extremely high memory storage capacity, and the efficiency of storage and query is low, especially when it is necessary to monitor long-term wind power equipment state changes. During the analysis, massive data needs to be analyzed intensively, which greatly occupies the data analysis resourc...

AI Technical Summary

Problems solved by technology

[0002]In the existing wind power generation state monitoring methods, the wind power generation unit state monitoring system needs to monitor the state information of all units in the wind farm, and the amount of monitoring is huge. However, due to the short-term The time-domain characteristics and frequency-domain characteristics of wind farm monitoring data are difficult to change significantly. Therefore, in order to reflect the state changes of wind turbines through continuous state monitoring, a large amount of long-term monitoring data needs to be stored, which requires extremely high memory storage capacity. Storage query Low efficiency, especially when it is necessary to analyze the status changes of long-term wind power equipment, it is necessary to conduct centralized analysis of massive data, which greatly occupies the data analysis resources of monitoring equipment, and the status monitoring effect is poor

Images