Construction method and system of power transformation equipment reliability evaluation model

Abstract

The invention discloses a construction method and system of a power transformation equipment reliability evaluation model. The construction method comprises the steps of obtaining operation parameters of power transformation equipment connected to an operation line; and the real-time operation state of each power transformation device is monitored. According to the invention, real-time monitoring is carried out through each power transformation device connected to an operation line, operation data is collected in real time, analysis is carried out based on historical operation data of the power transformation devices, standard operation data of the devices are obtained, the standard operation data and the real-time operation data are compared, and an early warning signal is sent out according to a comparison result. Early warning signals are divided into three types, namely, normal signals of the equipment, fault signals of the equipment and abnormal signals of the equipment, the abnormal signals possibly become the fault signals finally, so that faults need to be evaluated, finally, evaluation values are fed back to the system, and the system automatically adjusts operation parameters of the abnormal operation equipment, so that the operation efficiency of the equipment is improved. And the equipment can return to normal.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and system for constructing a reliability assessment model for substation equipment. Background Art

[0002] With the continuous improvement of electrification level, the requirements of the country, society and people for power supply reliability are getting higher and higher. These goals require more sophisticated and scientific reliability management of substation equipment. Power reliability management is the comprehensive quality management and full-process safety management of power systems and equipment, and is an important part of the modernization of power industry management. Among them, the reliability of substation equipment is an important part of power reliability management.

[0003] In the prior art, the reliability of substation equipment is usually evaluated through manual inspection. The reliability evaluation of substation equipment using the prior art is not only inefficient, but also easily affected by some subjective and objective factors, resulting in problems such as incomplete inspection coverage, which leads to the failure to timely discover hidden dangers and defects of substation equipment. Summary of the invention

[0004] In order to solve the above technical problems, a method and system for constructing a reliability assessment model for substation equipment are provided. The technical solution solves the problem proposed in the above background technology that the reliability of substation equipment is usually assessed through manual inspection. The reliability assessment of substation equipment using existing technology is not only inefficient, but also easily affected by some subjective and objective factors, resulting in problems such as incomplete inspection coverage, which leads to the failure to timely discover hidden dangers and defects of substation equipment.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A method for constructing a reliability assessment model for substation equipment, comprising:

[0007] Obtain the operating parameters of each substation connected to the operating line;

[0008] Monitor the real-time operating status of each substation equipment and obtain the real-time operating data of each substation equipment, the operating data including operating temperature and operating power;

[0009] Retrieve the historical real-time normal operation data of each substation equipment and obtain the standard operation data of the substation equipment;

[0010] Compare the real-time operation data of the substation equipment in operation with the standard operation data of the substation equipment, and send a monitoring signal according to the comparison result, wherein the monitoring signal includes a normal signal of the substation equipment, a fault signal of the substation equipment and an abnormal signal of the substation equipment;

[0011] Establishing an evaluation model to perform risk failure evaluation on abnormal signals and obtain the failure evaluation probability of substation equipment, wherein the evaluation model takes the abnormal operation index of substation equipment as input and outputs the failure evaluation probability of substation equipment;

[0012] The operating parameters of the substation equipment with a higher evaluation probability are sent to the monitoring platform to obtain real-time instructions and perform real-time regulation on the substation equipment with a higher evaluation probability.

[0013] Preferably, the evaluation model is:

[0014]

[0015] In the formula, y=1 represents a failure of the substation equipment, and y=0 represents normal operation of the substation equipment;

[0016] G is the predicted probability of the probability prediction model;

[0017] M P It is the abnormal operation index of the operating power of the substation equipment;

[0018] M T It is the abnormal operation index of the operating temperature of the substation equipment;

[0019] α, β1 and β2 are the coefficients of the risk prediction model.

[0020] Preferably, the calculation formula of the abnormal operation index is:

[0021] M=∑Δ 偏 ×t

[0022] In the formula, Δ 偏 is the offset of the running data relative to the standard running data,

[0023] t is the time of substation equipment in Δ 偏 The running time in the state.

[0024] Preferably, the calculation method of α, β1 and β2 is:

[0025] Classify the historical operation data according to whether the substation equipment eventually fails, and obtain several groups of historical operation data of the substation equipment that eventually fails and several groups of historical operation data of the substation equipment that eventually does not fail;

[0026] According to the historical operation data of several groups of substation equipment that eventually fail and the historical operation data of several groups of substation equipment that eventually do not fail, α, β1 and β2 are calculated by the maximum likelihood method;

[0027] Test the significance of α, β1 and β2 on the parameters of the evaluation model, and determine whether α, β1 and β2 meet the significance requirements.

[0028] Preferably, the calculation method of the standard operation data of the substation equipment is:

[0029] Arrange the historical operation data of the substation equipment in the operating state in ascending order;

[0030] Determine the detection level and determine the critical value of the kurtosis test based on the detection level;

[0031] Calculate the kurtosis observation value of each historical operation data based on the kurtosis test formula;

[0032] Determine whether the kurtosis observed value of the historical running data is greater than the critical value of the kurtosis test. If so, the point is determined to be an outlier; if not, the point is determined to be a non-outlier;

[0033] The average and standard deviation of the historical operating data of all non-outliers are calculated, and the standard operating data of the substation equipment is: In the formula, is the average value of the historical running data of all non-outlier points, and s' is the standard deviation of the historical running data of all non-outlier points.

[0034] Preferably, the calculation formula for the kurtosis observation value of the historical operation data is:

[0035]

[0036] Where bk(n) is the observed value of the kurtosis of the historical operating data;

[0037] n is the number of historical operation data sorted from small to large;

[0038] It is the average value of all historical running data;

[0039] x i The historical running data before n is arranged in ascending order.

[0040] Preferably, the step of comparing the real-time operation data of the substation equipment in operation with the standard operation data of the substation equipment and issuing a monitoring signal according to the comparison result specifically comprises the following steps:

[0041] Compare the real-time operation data of the real-time substation equipment in the running state with the standard operation data to determine whether the real-time operation data is within the standard operation data range. If so, it is determined that the substation equipment is operating normally and a normal signal of the substation equipment is output; if not, it is determined that the substation equipment is operating abnormally;

[0042] The real-time operating data of the abnormally operating substation equipment is compared with the preset fault threshold to determine whether the real-time operating data exceeds the fault threshold. If so, it is determined that the substation equipment is operating abnormally and a substation equipment fault signal is output. If not, it is determined that the substation equipment is operating abnormally and a substation equipment abnormality signal is output.

[0043] Preferably, the step of sending the operating parameters of the substation equipment with a higher evaluation probability to the monitoring platform to obtain the real-time instruction specifically comprises the following steps:

[0044] Extract and process the operation data of the substation equipment with a relatively high evaluation probability to obtain real-time parameters, which include temperature parameters, voltage parameters, and current parameters;

[0045] Determine whether the temperature parameter is a first preset threshold, and if the temperature parameter is greater than the first preset threshold, obtain a real-time temperature adjustment instruction;

[0046] Determine whether the voltage parameter is greater than a second preset threshold value, and if the voltage parameter is greater than the second preset threshold value, obtain a real-time voltage adjustment instruction;

[0047] It is determined whether the current parameter is greater than a third preset threshold value. If the current parameter is greater than the third preset threshold value, a real-time current adjustment instruction is obtained.

[0048] The real-time control of the substation equipment with a higher evaluation probability specifically includes the following steps:

[0049] Based on the temperature adjustment instructions, voltage adjustment instructions and current adjustment instructions, the operating information parameters of the substation equipment with a higher evaluation probability are adjusted.

[0050] A system for constructing a reliability assessment model for power substation equipment, used to implement a method for constructing a reliability assessment model for power substation equipment as described above, comprising:

[0051] An acquisition module, the acquisition module is used to acquire the operating parameters of each substation connected to the operating line;

[0052] A retrieval module, which is used to retrieve the historical real-time normal operation data of each substation equipment and obtain the standard operation data of the substation equipment;

[0053] The model building module is used to perform risk failure assessment on abnormal signals and obtain failure assessment probability of substation equipment.

[0054] Preferably, it also includes:

[0055] A monitoring module, the monitoring module is used to compare the real-time operating data of the substation equipment in the operating state with the standard operating data of the substation equipment, and send a monitoring signal according to the comparison result;

[0056] A control module is used to perform real-time control on substation equipment with a higher evaluation probability.

[0057] Compared with the prior art, the present invention provides a method and system for constructing a reliability assessment model for substation equipment, which has the following beneficial effects:

[0058] The present invention monitors the substation equipment connected to the operating line in real time, collects operating data in real time, analyzes the historical operating data of the substation equipment, obtains the standard operating data of the equipment, compares the standard operating data with the real-time operating data, and issues a warning signal according to the comparison result. The present invention divides the warning signal into three types: a normal signal of the equipment, a fault signal of the equipment, and an abnormal signal of the equipment. Since the abnormal signal may eventually become a fault signal, it is necessary to evaluate the fault. Finally, by feeding back the evaluation value to the system, the system automatically adjusts the operating parameters of the abnormally operating equipment to ensure that the equipment can return to normal. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a schematic diagram of the method flow of the present invention;

[0060] Figure 2 It is a flow chart of a method for calculating standard operation data of a power substation in the present invention;

[0061] Figure 3 It is a flow chart of the method for sending a monitoring signal according to the comparison result in the present invention;

[0062] Figure 4 The present invention is a flowchart of a method for sending operating parameters of a substation device with a relatively high evaluation probability to a monitoring platform to obtain real-time instructions. DETAILED DESCRIPTION

[0063] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0064] Please refer to Figure 1-Figure 4 As shown, a method for constructing a reliability assessment model for substation equipment includes:

[0065] Obtain the operating parameters of each substation connected to the operating line;

[0066] Monitor the real-time operating status of each substation equipment and obtain the real-time operating data of each substation equipment, including operating temperature and operating power;

[0067] Retrieve the historical real-time normal operation data of each substation equipment and obtain the standard operation data of the substation equipment;

[0068] Compare the real-time operation data of the substation equipment in operation with the standard operation data of the substation equipment, and send monitoring signals according to the comparison results. The monitoring signals include normal signals of the substation equipment, fault signals of the substation equipment and abnormal signals of the substation equipment;

[0069] Establish an evaluation model to evaluate the risk of abnormal signals and obtain the probability of failure assessment of substation equipment. The evaluation model takes the abnormal operation index of substation equipment as input and outputs the probability of failure assessment of substation equipment.

[0070] The operating parameters of the substation equipment with a higher evaluation probability are sent to the monitoring platform to obtain real-time instructions and perform real-time regulation on the substation equipment with a higher evaluation probability.

[0071] The present invention monitors the substation equipment connected to the operating line in real time, collects operating data in real time, analyzes the historical operating data of the substation equipment, obtains the standard operating data of the equipment, compares the standard operating data with the real-time operating data, and issues a warning signal according to the comparison result. The present invention divides the warning signal into three types: a normal signal of the equipment, a fault signal of the equipment and an abnormal signal of the equipment. Since the abnormal signal may eventually become a fault signal, it is necessary to evaluate the fault. Finally, by feeding the evaluation value back to the system, the system automatically adjusts the operating parameters of the abnormally operating equipment to ensure that the equipment can return to normal. If the equipment still does not change, the staff is required to inspect and repair it to prevent unnecessary trouble.

[0072] The evaluation model is:

[0073]

[0074] In the formula, y=1 represents a failure of the substation equipment, and y=0 represents normal operation of the substation equipment;

[0075] G is the predicted probability of the probability prediction model;

[0076] M P It is the abnormal operation index of the operating power of the substation equipment;

[0077] M T It is the abnormal operation index of the operating temperature of the substation equipment;

[0078] α, β1 and β2 are the coefficients of the risk prediction model.

[0079] The evaluation model proposed in this scheme is based on the principle of Logistic regression model to establish a fault evaluation model. Logistic regression model is a generalized linear regression analysis model, which is often used in data mining, result prediction and other fields;

[0080] The fault risk prediction model proposed in this scheme predicts the abnormal operating indicators of the substation equipment in abnormal operating state to calculate the probability of failure of the substation equipment, and judges whether the substation equipment is at risk of failure based on the predicted probability of failure of the substation equipment. It can promptly and quickly troubleshoot the potential faults of the substation equipment in the system.

[0081] The calculation formula of abnormal operation index is:

[0082] M=ΣΔ 偏 ×t

[0083] In the formula, Δ 偏 is the offset of the running data relative to the standard running data,

[0084] t is the time of substation equipment in Δ 偏 The running time in the state.

[0085] During the operation of the substation equipment, when abnormal operating data occurs, the greater the difference from the standard abnormal data and the longer the deviation operation time, the greater the risk of failure. Therefore, this scheme accumulates the product of the offset of all abnormal operating data and the abnormal operation time occurring during the operation of the substation equipment as the abnormal operation indicator of the substation equipment.

[0086] The calculation method of α, β1 and β2 is:

[0087] Classify the historical operation data according to whether the substation equipment eventually fails, and obtain several groups of historical operation data of the substation equipment that eventually fails and several groups of historical operation data of the substation equipment that eventually does not fail;

[0088] According to the historical operation data of several groups of substation equipment that eventually fail and the historical operation data of several groups of substation equipment that eventually do not fail, α, β1 and β2 are calculated by the maximum likelihood method;

[0089] Test the significance of α, β1 and β2 on the parameters of the evaluation model, and determine whether α, β1 and β2 meet the significance requirements.

[0090] The calculation method of standard operation data of substation equipment is:

[0091] Arrange the historical operation data of the substation equipment in the operating state in ascending order;

[0092] Determine the detection level and determine the critical value of the kurtosis test based on the detection level;

[0093] Calculate the kurtosis observation value of each historical operation data based on the kurtosis test formula;

[0094] Determine whether the kurtosis observed value of the historical running data is greater than the critical value of the kurtosis test. If so, the point is determined to be an outlier; if not, the point is determined to be a non-outlier;

[0095] The average and standard deviation of the historical operating data of all non-outliers are calculated, and the standard operating data of the substation equipment is: In the formula, is the average value of the historical running data of all non-outlier points, and s' is the standard deviation of the historical running data of all non-outlier points.

[0096] The calculation formula for the kurtosis observation value of historical operation data is:

[0097]

[0098] Where bk(n) is the observed value of the kurtosis of the historical operating data;

[0099] n is the sorting number of historical operation data from small to large;

[0100] It is the average value of all historical running data;

[0101] x i The historical running data before n is arranged in ascending order.

[0102] By eliminating outliers through the historical operating data of substation equipment and calculating the standard operating data of substation equipment based on non-outlier data, the influence of interference variables in the historical operating data on the detection results can be effectively reduced, and the reliability of the calculation of standard operating data can be improved, thereby greatly ensuring the monitoring accuracy of the power system and improving the monitoring sensitivity of the monitoring system to the abnormal operating status of substation equipment.

[0103] The real-time operation data of the substation equipment in operation is compared with the standard operation data of the substation equipment, and a monitoring signal is issued according to the comparison result, which specifically includes the following steps:

[0104] Compare the real-time operation data of the real-time substation equipment in the running state with the standard operation data to determine whether the real-time operation data is within the standard operation data range. If so, it is determined that the substation equipment is operating normally and a normal signal of the substation equipment is output; if not, it is determined that the substation equipment is operating abnormally;

[0105] The real-time operating data of the abnormally operating substation equipment is compared with the preset fault threshold to determine whether the real-time operating data exceeds the fault threshold. If so, it is determined that the substation equipment is operating abnormally and a substation equipment fault signal is output. If not, it is determined that the substation equipment is operating abnormally and a substation equipment abnormality signal is output.

[0106] This scheme adopts a hierarchical approach to monitor the operating data of substation equipment. First, it determines whether the real-time operating data is within the standard operating data range. At this time, it can be determined that the substation equipment is in a normal operating state. For real-time operating data outside the standard operating data range, it is determined whether it exceeds the fault threshold, and whether the substation equipment has failed is output based on the judgment result.

[0107] Sending the operating parameters of the substation equipment with a high probability of evaluation to the monitoring platform and obtaining real-time instructions specifically includes the following steps:

[0108] Extract and process the operating data of substation equipment with a high evaluation probability to obtain real-time parameters, including temperature parameters, voltage parameters, and current parameters;

[0109] Determine whether the temperature parameter is a first preset threshold, and if the temperature parameter is greater than the first preset threshold, obtain a real-time temperature adjustment instruction;

[0110] Determine whether the voltage parameter is greater than a second preset threshold value, and if the voltage parameter is greater than the second preset threshold value, obtain a real-time voltage adjustment instruction;

[0111] It is determined whether the current parameter is greater than a third preset threshold value. If the current parameter is greater than the third preset threshold value, a real-time current adjustment instruction is obtained.

[0112] The specific steps of real-time control of substation equipment with a higher evaluation probability are as follows:

[0113] Based on the temperature adjustment instructions, voltage adjustment instructions and current adjustment instructions, the operating information parameters of the substation equipment with a higher evaluation probability are adjusted.

[0114] In this solution, if the temperature of a substation equipment rises abnormally and the temperature continues to rise, when the temperature is greater than a first preset threshold value, the temperature data and the alarm signal are transmitted to the control terminal. The control terminal adjusts the substation equipment according to the temperature rise, reduces the load rate of the substation equipment or stops the operation of the substation equipment. If the temperature of the substation equipment stops dropping after the load rate is reduced and a rebound occurs, it indicates that the substation equipment may be aging, and maintenance personnel need to be sent to repair the substation equipment and provide corresponding solutions.

[0115] A system for constructing a reliability assessment model for power substation equipment, used to implement a method for constructing a reliability assessment model for power substation equipment as described above, comprising:

[0116] An acquisition module, which is used to acquire the operating parameters of each substation connected to the operating line;

[0117] The retrieval module is used to retrieve the historical real-time normal operation data of each substation equipment and obtain the standard operation data of the substation equipment;

[0118] The model building module is used to perform risk fault assessment on abnormal signals and obtain the failure assessment probability of substation equipment.

[0119] The monitoring module is used to compare the real-time operation data of the substation equipment in operation with the standard operation data of the substation equipment, and send a monitoring signal according to the comparison result;

[0120] The control module is used to perform real-time control on substation equipment with a higher evaluation probability.

[0121] In summary, the present invention monitors the substation equipment connected to the operating line in real time, collects operating data in real time, analyzes the historical operating data of the substation equipment, obtains the standard operating data of the equipment, compares the standard operating data with the real-time operating data, and issues a warning signal based on the comparison result. The present invention divides the warning signal into three types: normal signal of the equipment, fault signal of the equipment and abnormal signal of the equipment. Since the abnormal signal may eventually become a fault signal, it is necessary to evaluate the fault. Finally, by feeding the evaluation value back to the system, the system automatically adjusts the operating parameters of the abnormally operating equipment to ensure that the equipment can return to normal. If the equipment still does not change, the staff is required to inspect and repair it to prevent unnecessary trouble.

[0122] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for constructing a reliability assessment model for substation equipment, characterized in that: include: Obtain the operating parameters of each substation connected to the operating line; Monitor the real-time operating status of each substation equipment and obtain the real-time operating data of each substation equipment, the operating data including operating temperature and operating power; Retrieve the historical real-time normal operation data of each substation equipment and obtain the standard operation data of the substation equipment; Compare the real-time operation data of the substation equipment in operation with the standard operation data of the substation equipment, and send a monitoring signal according to the comparison result, wherein the monitoring signal includes a normal signal of the substation equipment, a fault signal of the substation equipment and an abnormal signal of the substation equipment; Establishing an evaluation model to perform risk failure evaluation on abnormal signals and obtain the failure evaluation probability of substation equipment, wherein the evaluation model takes the abnormal operation index of substation equipment as input and outputs the failure evaluation probability of substation equipment; The operating parameters of the substation equipment with a higher evaluation probability are sent to the monitoring platform to obtain real-time instructions and perform real-time regulation on the substation equipment with a higher evaluation probability.

2. The method for constructing a reliability assessment model for substation equipment according to claim 1, characterized in that: The evaluation model is: In the formula, y=1 represents a failure of the substation equipment, and y=0 represents normal operation of the substation equipment; G is the predicted probability of the probability prediction model; M P It is the abnormal operation index of the operating power of the substation equipment; M T It is the abnormal operation index of the operating temperature of the substation equipment; α, β1 and β2 are the coefficients of the risk prediction model.

3. The method for constructing a reliability assessment model for substation equipment according to claim 1, characterized in that: The calculation formula of the abnormal operation index is: M=∑Δ 偏 ×t In the formula, Δ 偏 is the offset of the running data relative to the standard running data, t is the time of substation equipment in Δ 偏 The running time in the state.

4. The method for constructing a reliability assessment model for substation equipment according to claim 1, characterized in that: The calculation method of α, β1 and β2 is: Classify the historical operation data according to whether the substation equipment eventually fails, and obtain several groups of historical operation data of the substation equipment that eventually fails and several groups of historical operation data of the substation equipment that eventually does not fail; According to the historical operation data of several groups of substation equipment that eventually fail and the historical operation data of several groups of substation equipment that eventually do not fail, α, β1 and β2 are calculated by the maximum likelihood method; Test the significance of α, β1 and β2 on the parameters of the evaluation model, and determine whether α, β1 and β2 meet the significance requirements.

5. The method for constructing a reliability assessment model for substation equipment according to claim 1, characterized in that: The calculation method of the standard operation data of the substation equipment is as follows: Arrange the historical operation data of the substation equipment in the operating state in ascending order; Determine the detection level and determine the critical value of the kurtosis test based on the detection level; Calculate the kurtosis observation value of each historical operation data based on the kurtosis test formula; Determine whether the kurtosis observed value of the historical running data is greater than the critical value of the kurtosis test. If so, the point is determined to be an outlier; if not, the point is determined to be a non-outlier; The average and standard deviation of the historical operating data of all non-outliers are calculated, and the standard operating data of the substation equipment is: In the formula, is the average value of the historical running data of all non-outlier points, and s' is the standard deviation of the historical running data of all non-outlier points; The calculation formula of the kurtosis observation value of the historical operation data is: Where bk(n) is the observed value of the kurtosis of the historical operating data; n is the sorting number of historical operation data from small to large; It is the average value of all historical running data; x i The historical running data before n is arranged in ascending order.

6. The method for constructing a reliability assessment model for substation equipment according to claim 1, characterized in that: The step of comparing the real-time operation data of the substation equipment in operation with the standard operation data of the substation equipment and issuing a monitoring signal according to the comparison result specifically includes the following steps: Compare the real-time operation data of the real-time substation equipment in the running state with the standard operation data to determine whether the real-time operation data is within the standard operation data range. If so, it is determined that the substation equipment is operating normally and a normal signal of the substation equipment is output; if not, it is determined that the substation equipment is operating abnormally; The real-time operating data of the abnormally operating substation equipment is compared with the preset fault threshold to determine whether the real-time operating data exceeds the fault threshold. If so, it is determined that the substation equipment is operating abnormally and a substation equipment fault signal is output. If not, it is determined that the substation equipment is operating abnormally and a substation equipment abnormality signal is output.

7. The method for constructing a reliability assessment model for substation equipment according to claim 1, characterized in that: The step of sending the operating parameters of the substation equipment with a higher evaluation probability to the monitoring platform and obtaining the real-time instruction specifically includes the following steps: Extract and process the operation data of the substation equipment with a relatively high evaluation probability to obtain real-time parameters, which include temperature parameters, voltage parameters, and current parameters; Determine whether the temperature parameter is a first preset threshold, and if the temperature parameter is greater than the first preset threshold, obtain a real-time temperature adjustment instruction; Determine whether the voltage parameter is greater than a second preset threshold value, and if the voltage parameter is greater than the second preset threshold value, obtain a real-time voltage adjustment instruction; It is determined whether the current parameter is greater than a third preset threshold value. If the current parameter is greater than the third preset threshold value, a real-time current adjustment instruction is obtained.

8. The method for constructing a reliability assessment model for substation equipment according to claim 1, characterized in that: The real-time control of the substation equipment with a higher evaluation probability specifically includes the following steps: Based on the temperature adjustment instructions, voltage adjustment instructions and current adjustment instructions, the operating information parameters of the substation equipment with a higher evaluation probability are adjusted.

9. A system for constructing a reliability assessment model for substation equipment, used to implement a method for constructing a reliability assessment model for substation equipment as described in claims 1 to 9, characterized in that: include: An acquisition module, the acquisition module is used to acquire the operating parameters of each substation connected to the operating line; A retrieval module, which is used to retrieve the historical real-time normal operation data of each substation equipment and obtain the standard operation data of the substation equipment; The model building module is used to perform risk failure assessment on abnormal signals and obtain failure assessment probability of substation equipment.

10. A system for constructing a reliability assessment model for substation equipment according to claim 1, characterized in that: It is characterized by further comprising: A monitoring module, the monitoring module is used to compare the real-time operating data of the substation equipment in the operating state with the standard operating data of the substation equipment, and send a monitoring signal according to the comparison result; A control module is used to perform real-time control on substation equipment with a higher evaluation probability.

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