Method for compressing data of status monitoring system of wind turbine generator system

Abstract

The invention provides a method for compressing data of a status monitoring system of a wind turbine generator system. Strong features are extracted in the mode that mathematical modeling is conducted on the monitoring data locally in the wind turbine generator system, and data compression and recovery are conducted according to a high compression ratio. The method comprises the following steps of collection of the wind electricity status monitoring data, identification of operating conditions of the wind turbine generator system, filtration of the wind electricity status monitoring data, local collating of monitoring data information, wind electricity status storage mode selection, identification and matching of intelligent modeling structures, estimation of parameters of the intelligent modeling structures, local primary processing of the monitoring data and upper monitoring terminal secondary processing. By means of the method, mass data on-line transmission and long-term continuous monitoring storage are achieved.

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...

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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

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