Main transformer oil conservator state prediction method and device based on digital twinning and electronic equipment

Abstract

The invention discloses a main transformer oil conservator state prediction method and device based on digital twinning and electronic equipment. The method comprises the following steps: establishing a digital twinning main transformer oil conservator model; establishing a target variable prediction model, a quantifiable influence factor prediction model and a total influence factor prediction model; running the digital twin main transformer oil conservator model, and acquiring detection data; respectively inputting the detection data into the target variable prediction model, the quantifiable influence factor prediction model and the total influence factor prediction model, and respectively obtaining a first oil temperature prediction trend line, a second oil temperature prediction trend line and a third oil temperature prediction trend line; and according to the first oil temperature prediction trend line, the second oil temperature prediction trend line and the third oil temperature prediction trend line, conducting state prediction of the main transformer oil conservator. According to the method, the future health state of the main transformer oil conservator can be effectively predicted and analyzed, and a solution is provided for reliable operation of equipment.

Description

technical field [0001] The invention relates to the technical field of power equipment operation and maintenance, in particular to a digital twin-based main transformer oil conservator state prediction method, device and electronic equipment. Background technique [0002] A digital twin is a virtual model created digitally for a physical object to simulate its behavior in a real-world environment, thus reflecting the entire life cycle process of the corresponding physical device. After the digital twin substation is completed, the intelligent cloud platform can be used to fully perceive the operation status of the substation and achieve real-time monitoring. Through this "twin" substation, the data of the power station can be easily obtained, analyzed and processed, which completely solves the problems of lack of a unified data platform, lack of data analysis, and difficulty in judging equipment risks, and realizes the management of the whole domain and the whole life cycle ...

AI Technical Summary

Problems solved by technology

[0003] During the operation of the transformer, various types of defects or faults will cause temperature rise, such as: the transformer withstands short-circuit current impact for too long, internal pressure increases, mechanical damage, etc.; if the short-circuit current is large, relay protection If the action is delayed or even refused, the deformation will be serious, and even the winding will be damaged. If the temperature continues to rise, it will cause damage to the equipment, cause abnormal power outages, and affect personal safety and power supply stability. As one of the most important characteristics, it is particularly important to predict the trend of conservator oil temperature in advance

[0004] In traditional power operation and maintenance work, the health status of equipment is often judged by means of daily equipment inspections, power monitoring system measurement point data collection, and electrical maintenance tests. However, when equipment failures are detected by these methods, the failures have often developed. To a more serious extent, it will bring great difficulties to maintenance. Since the future health status of the equipment cannot be predicted and analyzed, the operation and maintenance personnel can only perform passive maintenance on the equipment, that is, provide solutions for the defects or failures that have occurred , which greatly affects the reliability of equipment operation

[0005] The patent document "A Temperature Monitoring and Early Warning System for Transformers" (CN11584216B) discloses that temperature sensors are installed in the transformer oil conservator, and temperature sensors are arranged in other parts of the transformer. The temperature information collected by each temperature sensor is used to monitor the temperature of the transformer. Monitoring and early warning, however, this solution only provides early warning by monitoring the temperature. Only when the oil temperature is about to reach the critical point of decomposition or is about to reach the critical point of insulation failure, can it be noticed, and it cannot predict the future oil temperature of the main transformer oil conservator. It is impossible to predict the changing trend of the main transformer oil conservator

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