Converter valve cooling capacity multidimensional analysis early-warning method and system

Abstract

The invention discloses a converter valve cooling capacity multidimensional analysis early-warning method and system and relates to the field of converter valve monitoring technologies. The system comprises early-warning units, a man-machine interaction device, a central processing unit and a data collection module, wherein the data collection module is used for collecting a state quantity of a converter valve cooling system and transmitting the state quantity to the central processing unit through a data collection interface; the central processing unit is used for assessing the cooling capacity of the state quantity and outputting an early-warning signal of the assessment result through an advanced early-warning unit, a first early-warning unit and a second early-warning unit respectively; and the man-machine interaction device is used for inputting a user instruction and displaying a monitored value of the state quantity. According to the method, a cooling capacity quantitative model is established from different dimensions, cooling capacity quantitative assessment indexes are formed, and a converter station valve cooling system defect early-warning model based on multidimensional analysis is established.

Description

technical field [0001] The invention relates to the technical field of converter valve monitoring, in particular to a method and system for multi-dimensional analysis and early warning of converter valve cooling capacity. Background technique [0002] The valve cooling system can discharge the heat generated by the power consumption of each component on the converter valve to the outside of the valve hall through heat exchange, so as to ensure that the converter valve operates in a normal temperature range. Whether the valve cooling system can work normally will affect the safe operation of the entire high-voltage direct current transmission system (HVDC). At present, the evaluation of the operating status of the valve cooling system mainly depends on the monitoring data information provided by various sensors and measuring components, and compares and judges with the threshold value to determine whether to issue an alarm message or perform linkage according to the logic set...

AI Technical Summary

Problems solved by technology

At present, the evaluation of the operating status of the valve cooling system mainly depends on the monitoring data information provided by various sensors and measuring components, and compares and judges with the threshold value to determine whether to issue an alarm message or perform linkage according to the logic setting. However, due to the Due to the differences in operating environments and working conditions, the thresholds set by current relevant operating specifications have certain limitations in abnormal diagnosis, and are affected by factors such as load, temperature, and component defects in the valve cooling system. Abnormalities are sometimes hidden in the fluctuations of normal monitoring signals and are difficult to identify; at the same time, the method of threshold or change rate is used for defect diagnosis, the algorithm logic is single, and the application of artificial intelligence is insufficient. It is difficult to quantitatively evaluate whether the cooling capacity of the valve cooling system is sufficient

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