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CN-122001081-A - Intelligent operation and maintenance management platform method, device, equipment and medium for transformer substation

CN122001081ACN 122001081 ACN122001081 ACN 122001081ACN-122001081-A

Abstract

The invention relates to the technical field of operation and maintenance management of a transformer substation, and discloses a method, a device, equipment and a medium for intelligent operation and maintenance management platform of the transformer substation, wherein the data is acquired; the method comprises the steps of collecting and preprocessing data, analyzing the data, extracting key features of the running state of the equipment, establishing a reference model of the normal running state of the equipment, monitoring in real time, formulating a processing strategy based on the running state information of the equipment provided by data processing and analysis, analyzing the collected running data of the equipment, accurately extracting the key features of the running of the equipment and identifying abnormal modes, realizing early warning and accurate diagnosis of faults, reducing false alarm and missing report, and enabling the use of resources to be more efficient, avoiding resource waste, reducing manual intervention by real-time monitoring, improving the running efficiency and safety, and overcoming the defect that transformer substation workers need to frequently conduct on-site inspection.

Inventors

  • ZHOU JIAN

Assignees

  • 巨硕电力建设有限公司

Dates

Publication Date
20260508
Application Date
20260211

Claims (10)

  1. 1. The intelligent operation and maintenance management platform method for the transformer substation is characterized by comprising the following steps of, Data acquisition, namely acquiring operation data of equipment in the transformer substation in real time through data acquisition; Preprocessing, namely completing data collection and preprocessing of the collected operation data by utilizing a plurality of sensors; data processing and analysis, namely analyzing the data, extracting key characteristics of the running state of the equipment, and establishing a reference model of the normal running state of the equipment; real-time monitoring, namely setting a threshold range of key parameters by real-time monitoring the transformer substation based on equipment running state information provided by data processing and analysis, and sending out an alarm when the monitored equipment parameters exceed the threshold; Diagnosing and predicting, namely diagnosing and predicting faults by utilizing the operation characteristics and abnormal data modes of the equipment extracted by data processing and analysis; and (3) strategy formulation, namely formulating a processing strategy according to diagnosis and prediction results.
  2. 2. The intelligent operation and maintenance management platform method for the transformer substation according to claim 1, wherein the specific steps of data processing and analysis and data analysis comprise, Constructing a state vector X k and an observation vector Z k , wherein X k represents the state of the device at the time k, and Z k represents the observation data of the device at the time k; The state vector is predicted by using the state transition matrix F k and the control matrix B k , and the expression of the predicted state vector is that, ; Wherein, the Indicating the predicted state of the device at time k, Representing a posterior state estimate of the device at time k-1, u k representing a control input; The observation vector is predicted by using an observation matrix H k , the predicted observation vector is, ; Then, the Kalman gain is calculated, ; Wherein, the Representing the prediction error covariance of the prediction error, Representing observed noise covariance, T representing transpose operation of the matrix and vector; The update state vector and the error covariance are such that, ; ; Wherein I represents an identity matrix; and then, extracting key characteristics of the running state of the equipment, and establishing a reference model of the normal running state of the equipment, wherein the key characteristics comprise current, voltage fluctuation characteristics, temperature change trend characteristics and correlation characteristics among the equipment.
  3. 3. The intelligent operation and maintenance management platform method of transformer substation according to claim 2, wherein the state vector X k comprises the current I k , the voltage V k , the temperature T k and the power P k of the equipment, namely, ; The observation vector Z k includes the current I meas,k , voltage V meas,k and temperature T meas,k measured by the sensor, i.e., 。
  4. 4. The intelligent operation and maintenance management platform method for transformer substation according to claim 3, wherein the state transition matrix F k and the control matrix B k are set according to the physical characteristics and operation rules of the equipment, specifically, ; Wherein, the Representing a time step; The observation matrix H k is set according to the measurement characteristics of the sensor, specifically, ; Wherein, the 、 And The noise variance of the current, voltage and temperature sensors are shown, respectively.
  5. 5. The intelligent operation and maintenance management platform method of transformer substation according to claim 4, wherein the prediction error covariance is obtained by using a method of the intelligent operation and maintenance management platform The updated formula of (c) is given by, ; Wherein, the Representing process noise covariance, based on uncertainty in device operation and environmental disturbance settings.
  6. 6. The intelligent operation and maintenance management platform method for the transformer substation according to claim 2 or 5, wherein the extraction of the key features comprises, Current fluctuation characteristics, calculating the average value of current And standard deviation And extracting the fluctuation range of the current ; Voltage fluctuation characteristics, calculating average value of voltage And standard deviation And extracting the fluctuation range of the voltage ; Temperature change trend feature, calculating temperature change rate through time sequence analysis Extracting the rising or falling trend of the temperature; The specific step of monitoring the transformer substation in real time comprises the steps of setting a threshold range of key parameters, wherein the key parameters comprise current I, voltage V, temperature T and power P, and the threshold range of each parameter is as follows Wherein L param ,U param represents the lower and upper thresholds of the parameter, respectively; Acquiring equipment operation state information provided by data processing and analysis in real time, wherein the equipment operation state information comprises key parameter values I k 、V k 、T k and P k at the current moment k; Threshold judgment is carried out on each key parameter; when I k <L I or I k ＞U I , the current parameter is out of the threshold range; When V k <L V or V k ＞U V , the voltage parameter is beyond the threshold range; When T k <L T or T k ＞U T , the temperature parameter is beyond the threshold range; when P k <L P or P k ＞U P , the power parameter is out of the threshold range; when any one of the key parameters exceeds the corresponding threshold range, an alarm signal is sent out, wherein the alarm signal comprises an alarm type, a parameter name exceeding the threshold, a current parameter value and an exceeding timestamp.
  7. 7. The intelligent operation and maintenance management platform method of the transformer substation according to claim 6, wherein the setting of the threshold range is based on a benchmark model of the normal operation state of the equipment and historical operation data statistical analysis, specifically comprising, Calculating a historical mean μ param and σ param for each key parameter; the threshold value range is set to be such that, ; ; The constant 3 is a safety coefficient set according to the running stability and reliability requirements of the equipment and is a value according to historical data analysis; The specific steps of diagnosing and predicting faults by utilizing the data processing and analyzing the extracted equipment operation characteristics and abnormal data patterns comprise, Extracting equipment operation characteristics and constructing fault characteristic vectors based on the extracted equipment operation characteristics, wherein each characteristic value represents a specific fault characteristic; Calculating an abnormality score of each feature, and evaluating the degree of abnormality by comparing the deviation of the feature value from a reference value in a normal operation state; Judging whether the equipment operation data has an abnormal mode or not according to the abnormal score; Comparing the similarity of the current abnormal mode and the known fault mode, and identifying the fault type; predicting the possible occurrence time of faults according to the equipment operation trend and the historical fault data; generating detailed fault reports including fault type, probability of occurrence of fault, expected time of occurrence, impact range and maintenance advice; the specific steps of formulating a treatment strategy based on the diagnostic and predictive results include, Setting fault type grades, and dividing the faults into four grades according to the severity degree and the influence range of the faults; formulating a corresponding processing strategy according to the fault level; Then, the fault handling result is evaluated and fed back.
  8. 8. An intelligent operation and maintenance management platform device for a transformer substation, which is characterized by comprising: the data acquisition module is used for acquiring the operation data of equipment in the transformer substation in real time through a plurality of sensors; the preprocessing module is connected with the data acquisition module and is used for filtering, denoising and formatting the acquired operation data; The data processing and analyzing module is connected with the preprocessing module and is used for storing the preprocessed data, analyzing the data based on a Kalman filtering algorithm, extracting key characteristics of the running state of the equipment and establishing a reference model of the normal running state of the equipment; The real-time monitoring module is connected with the data processing and analyzing module and is used for comparing the current running state in real time according to the reference model and sending out an alarm when the key parameters exceed the threshold range; the diagnosis prediction module is connected with the data processing and analyzing module and is used for diagnosing and predicting faults according to the extracted characteristics and the abnormal data mode and generating a fault report; and the strategy making module is connected with the diagnosis prediction module and is used for making a grading processing strategy according to the fault grade and pushing the strategy to the operation and maintenance terminal.
  9. 9. Intelligent operation and maintenance management platform equipment of transformer substation, characterized by comprising: A memory for storing a computer program; A processor for executing the computer program to implement the steps of the substation intelligent operation and maintenance management platform method according to any one of claims 1-7; the communication interface is used for carrying out data interaction with the multi-sensor, the remote operation and maintenance terminal and the standby system in the transformer substation; And when the processor executes the computer program, the full-flow automatic operation of data acquisition, preprocessing, kalman filtering state estimation, key feature extraction, threshold comparison, fault diagnosis prediction and hierarchical strategy generation is completed.
  10. 10. A medium which is a computer readable storage medium and is characterized by comprising the steps of storing a device upgrade program on the computer readable storage medium, wherein the device upgrade program is executed by a processor to realize the intelligent operation and maintenance management platform of the transformer substation according to any one of claims 1-9.

Description

Intelligent operation and maintenance management platform method, device, equipment and medium for transformer substation Technical Field The invention relates to the technical field of operation and maintenance management of substations, in particular to a method, a device, equipment and a medium for intelligent operation and maintenance management platform of substations. Background Early defects such as insulation degradation, contact looseness or internal partial discharge of primary equipment of a transformer substation are usually expressed as continuous and weak drifting of macroscopic parameters such as current, voltage, temperature and the like, and then abrupt change into perceptible faults. In the engineering field, the operation and maintenance department still mainly relies on periodic inspection by operators and supplementary monitoring by a handheld infrared thermometer or a partial discharge tester, and is limited by inspection routes and sensor distribution points, the obtainable data is single in dimension and low in time resolution, and continuous depiction of an electric-thermal-mechanical field coupling evolution process inside equipment cannot be formed, so that early latent defect characteristics are covered by statistical fluctuation, and the rate of missing report and false report is high. Meanwhile, the inspection interval usually takes a week or month as a unit, the labor investment is large, the response is slow, and once the defect develops into a fault between two inspection, the power failure loss is increased, and the cost is also increased by Gao Yunwei. Disclosure of Invention The method, the device, the equipment and the medium for intelligent operation and maintenance management of the transformer substation are provided for solving the technical problems that in the prior art, the periodic inspection, the infrared temperature measurement, the partial discharge test and other means are relied on for supplementation, early-stage latent defects are difficult to find due to limited monitoring points and single data dimension, dynamic evolution of an internal physical field of the equipment cannot be described, and meanwhile, the inspection period is long and the labor cost is high. In order to achieve the aim, the intelligent operation and maintenance management platform method of the transformer substation comprises the following technical scheme that data acquisition is adopted, and operation data of equipment in the transformer substation are acquired in real time through the data acquisition; the collected operation data is collected by utilizing a plurality of sensors and is preprocessed; data processing and analysis, namely analyzing the data, extracting key characteristics of the running state of the equipment, and establishing a reference model of the normal running state of the equipment; real-time monitoring, namely setting a threshold range of key parameters by real-time monitoring the transformer substation based on equipment running state information provided by data processing and analysis, and sending out an alarm when the monitored equipment parameters exceed the threshold; Diagnosing and predicting, namely diagnosing and predicting faults by utilizing the operation characteristics and abnormal data modes of the equipment extracted by data processing and analysis; strategy formulation, namely formulating a processing strategy according to diagnosis and prediction results; The preprocessing comprises filtering, denoising and formatting, wherein the filtering comprises low-pass filtering and moving average filtering, the denoising comprises wavelet transform denoising and median filtering, and the formatting comprises data normalization and data interpolation. As a preferable scheme of the intelligent operation and maintenance management platform method of the transformer substation, the specific steps of data processing and analysis for data analysis comprise, Building state vectorsAnd an observation vectorWhereinZ k represents the observed data of the device at the time k; The state vector is predicted by using the state transition matrix F k and the control matrix B k, and the expression of the predicted state vector is that, Wherein, the Indicating the predicted state of the device at time k,Representing a posterior state estimate of the device at time k-1, u k representing a control input; The observation vector is predicted by using an observation matrix H k, the predicted observation vector is, ; Then, the Kalman gain is calculated, ; Wherein, the Representing the prediction error covariance of the prediction error,Representing observed noise covariance, T representing transpose operation of the matrix and vector; The update state vector and the error covariance are such that, ; ; Wherein I represents an identity matrix; and then, extracting key characteristics of the running state of the equipment, and establishing a reference model of the normal runnin