Method for early warning and dynamic tracking monitoring of power transformation main equipment

Abstract

The invention relates to the technical field of early warning of main power transformation equipment, in particular to a method for early warning and dynamic tracking monitoring of main power transformation equipment, which comprises the following steps of: according to the data fluctuation condition of the same data type as a chain node in an early warning association chain of an abnormal interference risk source in the equipment state information of the main power transformation equipment, determining an abnormal interference risk source according to the data fluctuation condition of the same data type as the chain node in the early warning association chain; and analyzing the risk confidence value of the early warning association chain of each abnormal interference risk source based on the corresponding abnormal interference risk source. According to the invention, the abnormal interference risk source set corresponding to the abnormal state summary information can be locked according to the abnormal fluctuation item in the real-time operation parameter monitoring result of the power transformation main equipment; and an early warning association chain of each abnormal interference risk source in historical maintenance data is combined to dynamically construct an early warning tracking and monitoring object set, an administrator is assisted to generate a power transformation main equipment tracking and monitoring object screening decision, and effective management of early warning and dynamic tracking and monitoring data of the power transformation main equipment is realized.

Description

Technical Field

[0001] The invention relates to the technical field of early warning of main substation equipment, and in particular to a method for early warning and dynamic tracking monitoring of main substation equipment. Background Art

[0002] With the continuous development and expansion of the power system, the safe and stable operation of the main substation equipment is crucial to the reliability of the entire power system. However, the main substation equipment may be affected by many factors during operation, such as environmental factors (humidity, temperature, etc.), equipment aging, improper operation, etc., which may cause equipment failure or accidents. Therefore, early warning and dynamic tracking and monitoring of the main substation equipment are of great significance.

[0003] In the existing early warning and dynamic tracking and monitoring methods for substation main equipment, regular inspections are usually carried out on preset parts of the substation main equipment. However, this inspection method is time-consuming and labor-intensive, and it is impossible to combine the real-time operating parameter monitoring results of the substation main equipment to achieve dynamic locking of the position to be inspected (abnormal interference risk source) of the substation main equipment, and thus it is impossible to screen the early warning tracking and monitoring objects in real time according to the operating parameters of the substation main equipment; therefore, the existing technology has major defects. Summary of the invention

[0004] The purpose of the present invention is to provide a method for early warning and dynamic tracking monitoring of main substation equipment to solve the problems raised in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for early warning and dynamic tracking monitoring of substation main equipment, the method comprising the following steps:

[0006] S1. The equipment operating parameters are collected in real time through the built-in sensors of the main substation equipment to generate the equipment status information of the corresponding main substation equipment; the abnormal fluctuation items in the equipment status information are summarized to obtain the abnormal status summary information; the abnormal interference risk source set corresponding to the abnormal status summary information is locked in combination with the preset table of the database and the historical maintenance data of the main substation equipment;

[0007] S2. Combine historical maintenance data to obtain the associated equipment corresponding to each abnormal interference risk source and the associated items of equipment operation parameters in the corresponding associated equipment, and build an early warning association chain for each abnormal interference risk source;

[0008] S3. Analyze the risk confidence value of the early warning association chain of each abnormal interference risk source based on the corresponding abnormal interference risk source according to the data fluctuation of the same data type as the node in the early warning association chain of the abnormal interference risk source in the equipment status information of the main substation equipment;

[0009] S4. Combining the similarity of the chain nodes in the early warning association chain of different abnormal interference risk sources, the risk confidence value corresponding to the corresponding abnormal interference risk source, and the distance between the corresponding positions of the corresponding abnormal risk source, the elements in the abnormal interference risk source set corresponding to the abnormal state summary information are fused and determined to generate a new abnormal interference risk source set corresponding to the abnormal state summary information;

[0010] S5. Combine the new set of abnormal interference risk sources corresponding to the abnormal status summary information and the early warning association chain of each abnormal interference risk source to build an early warning tracking and monitoring object set, and feed back the obtained early warning tracking and monitoring object set to the administrator to assist in generating substation main equipment tracking and monitoring object screening decisions.

[0011] Furthermore, the device status information of the corresponding substation main device in S1 includes the voltages and currents corresponding to different components of the corresponding substation main device at different time points;

[0012] Each element in the abnormal status summary information corresponds to an abnormal fluctuation item in the equipment status information; the abnormal fluctuation item represents the monitoring result in the corresponding equipment status information that does not belong to the preset monitoring threshold interval corresponding to the corresponding data item, or each monitoring result in the corresponding equipment status information whose monitoring fluctuation change coefficient within the preset unit time is greater than the abnormal fluctuation threshold of the corresponding data item, and the data items include voltage and current; the monitoring fluctuation change coefficient of each monitoring result within the preset unit time is equal to the quotient of the difference between the maximum monitoring result and the minimum monitoring result of the corresponding data item in the most recent unit time divided by the preset unit time; the abnormal fluctuation threshold of the corresponding data item is the average value of each abnormal fluctuation coefficient corresponding to the corresponding data item when the substation main equipment is abnormal in the historical maintenance data.

[0013] In the present invention, when screening abnormal fluctuation items, not only the abnormal data items are taken into account (the monitoring results that do not belong to the preset monitoring threshold interval corresponding to the corresponding data items in the corresponding equipment status information), but also the monitoring fluctuation change coefficient of the monitored data items within the preset unit time are taken into account (the corresponding monitoring fluctuation change coefficient is abnormal but the monitoring data is within the preset monitoring threshold interval. The corresponding data item is also regarded as abnormal); in the process of determining the abnormal fluctuation items for the monitoring fluctuation change coefficient, the abnormal fluctuation threshold of the corresponding data item is dynamically changed, which is the average value of each abnormal fluctuation coefficient corresponding to the corresponding data item when the substation main equipment is abnormal in the historical maintenance data. With the change of the number of abnormalities of the substation main equipment in the historical maintenance data, the abnormal fluctuation threshold of the corresponding data item will also change accordingly.

[0014] Furthermore, in the process of locking the set of abnormal interference risk sources corresponding to the abnormal state summary information in S1, the monitoring positions corresponding to each substation main equipment in the preset table of the database and the data pairs consisting of the abnormal fluctuation items corresponding to the corresponding model of substation main equipment at each maintenance abnormality in the historical maintenance data of the substation main equipment and the abnormal monitoring positions in the maintenance results are obtained; an array of abnormal interference risk sources corresponding to each element in the abnormal state summary information is obtained, the abnormal interference risk source array is an array consisting of the abnormal monitoring positions in the maintenance results in each data pair whose corresponding abnormal fluctuation items in the historical maintenance data of the substation main equipment of the corresponding model are the same as the corresponding elements in the abnormal state summary information; an abnormal monitoring position in a maintenance result corresponding to each abnormal interference risk source in the abnormal interference risk source array; and the set of the abnormal interference risk source array corresponding to each element in the abnormal state summary information is recorded as the locking result of the abnormal interference risk source set corresponding to the abnormal state summary information.

[0015] Further, the S2 includes:

[0016] S21, obtaining associated devices corresponding to each abnormal interference risk source, wherein the associated devices corresponding to the abnormal interference risk source are each substation device connected to the abnormal interference risk source;

[0017] S22, obtaining equipment operation parameter associated items in the corresponding associated equipment in the historical maintenance data, wherein the equipment operation parameter associated items in the corresponding associated equipment are equipment operation parameter items whose monitoring fluctuation change coefficients of the corresponding associated equipment in the preset unit time in the historical maintenance data do not belong to the corresponding fluctuation change coefficient interval in the preset unit time, and the corresponding fluctuation change coefficient interval in the preset unit time is an interval consisting of the maximum value and the minimum value of the fluctuation change coefficients of the corresponding operation parameter items at each time point in the preset unit time;

[0018] S23. Each device operating parameter associated item in the associated device corresponding to the abnormal interference risk source is used as a chain node in the early warning association chain of the corresponding abnormal interference risk source to obtain the early warning association chain of each abnormal interference risk source.

[0019] The early warning association chain of each abnormal interference risk source obtained in the present invention is obtained based on historical maintenance data.

[0020] Furthermore, S3 includes:

[0021] The calculation formula for the risk confidence value of the early warning association chain based on the analysis of each abnormal interference risk source is as follows:

[0022]

[0023] Among them, FRi Indicates that the early warning association chain of the ith abnormal interference risk source in the abnormal interference risk source set corresponding to the abnormal state summary information is based on the risk confidence value of the corresponding abnormal interference risk source; X (i，j) Indicates the monitoring fluctuation variation coefficient of the jth chain node in the early warning association chain of the i-th abnormal interference risk source in the abnormal interference risk source set corresponding to the abnormal state summary information within the preset unit time before the current time; Q (i，j) Indicates the fluctuation change coefficient interval of the jth chain node in the early warning association chain of the ith abnormal interference risk source in the abnormal interference risk source set corresponding to the abnormal state summary information within the preset unit time before the current time; N (i，j) represents the total number of chain nodes in the early warning association chain of the ith abnormal interference risk source in the abnormal interference risk source set corresponding to the abnormal state summary information, and N (i，j) >0; count{} indicates a statistical function; Indicates that the value range of j is in the interval [1, N (i，j) ], the condition is met The number of values ​​of , and j is an integer.

[0024] In the present invention, when analyzing the early warning association chain of each abnormal interference risk source based on the risk confidence value of the corresponding abnormal interference risk source, by analyzing the statistical X (i，j) With Q (i，j) The relationship between them is used to obtain the corresponding risk confidence value, and the value range of the obtained risk confidence value is [0, 1].

[0025] Furthermore, the method for performing fusion determination on the elements in the abnormal interference risk source set corresponding to the abnormal state summary information in S4 comprises the following steps:

[0026] S41, obtaining an early warning association chain corresponding to each element in the abnormal interference risk source set corresponding to the abnormal state summary information, respectively combining any two elements in the abnormal interference risk source set corresponding to the abnormal state summary information to generate different element combination pairs, and recording any element combination as (W1, W2), where W1 represents the first abnormal interference risk source in the corresponding element combination pair, and W2 represents the second abnormal interference risk source in the corresponding element combination pair;

[0027] S42. Calculate the element fusion bias value corresponding to (W1, W2) according to the element determination formula, and the element determination formula is as follows:

[0028] PR (W1 , W2) =E (W1 , W2) ·LB (W1 ,W2) ·[1-(1-FR{W1})·(1-FR{W2})]

[0029] Among them, PR (W1，W2) Indicates the element fusion bias value corresponding to (W1, W2);

[0030] E (W1，W2) represents the similarity of the chain nodes in the early warning association chain corresponding to W1 and W2 respectively; E (W1，W2) =M (W1，W2) / MB (W1，W2) ;M (W1，W2) MB represents the number of identical chain nodes in the early warning association chains corresponding to W1 and W2 respectively; (W1，W2) Represents the total number of elements in the union of the link point sets corresponding to each early warning association chain in W1 and W2;

[0031] FR{W1} represents the risk confidence value of the early warning association chain of W1 based on the corresponding abnormal interference risk source;

[0032] FR{W2} represents the risk confidence value of the early warning association chain of W2 based on the corresponding abnormal interference risk source;

[0033] LB (W1，W2) Represents the quotient of the distance between the corresponding positions of W1 and W2 and the preset fusion determination distance;

[0034] S43, compare the maximum element fusion bias value with the fusion determination factor, where the fusion determination factor is a constant preset in the database; when the maximum element fusion bias value is less than the fusion determination factor, the current corresponding abnormal interference risk source set is transmitted to S44; otherwise, the two elements in the element combination pair with the largest corresponding element fusion bias value are fused, and the fused elements are used to replace the corresponding two elements in the abnormal interference risk source set, and the new abnormal interference risk source set generated by the substitution is transmitted to S41 for iteration;

[0035] S44. Use the transmission result of S43 as a new abnormal interference risk source set corresponding to the abnormal state summary information.

[0036] Furthermore, the fused element in S43 represents a set consisting of corresponding monitoring positions before fusion; the early warning association chain corresponding to the fused element is a summary set of chain nodes in each early warning association chain before fusion; the early warning association chain of the fused element is based on the risk confidence value of the corresponding abnormal interference risk source, which is equal to the difference between 1 and the product of the absolute value of the difference between the risk confidence value corresponding to each element before fusion and 1; the distance between the fused element and the corresponding positions of the remaining abnormal interference risk sources is equal to the minimum value of the distance between each element and the corresponding positions of the remaining abnormal interference risk sources before fusion.

[0037] Further, in the early warning tracking and monitoring object set constructed in S5, each early warning tracking and monitoring object corresponds to an abnormal interference risk source, and each early warning tracking and monitoring object is an array consisting of the corresponding abnormal interference risk source, the early warning association chain of the corresponding abnormal interference risk source, and the risk confidence value corresponding to the corresponding abnormal interference risk source;

[0038] The elements in the early warning tracking and monitoring object set are arranged in descending order according to the risk confidence values ​​corresponding to the corresponding abnormal interference risk sources.

[0039] Compared with the prior art, the beneficial effects achieved by the present invention are: the present invention can lock the set of abnormal interference risk sources corresponding to the abnormal state summary information according to the abnormal fluctuation items in the real-time operating parameter monitoring results of the substation main equipment; and combine the early warning association chain of each abnormal interference risk source in the historical maintenance data to realize the screening of the positions to be inspected (abnormal interference risk sources) of the substation main equipment, dynamically construct an early warning tracking and monitoring object set, assist the administrator in generating the substation main equipment tracking and monitoring object screening decision, and realize the effective management of the early warning and dynamic tracking and monitoring data of the substation main equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0041] Figure 1 The present invention is a flowchart of a method for early warning and dynamic tracking monitoring of main substation equipment. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] See also Figure 1 The present invention provides a technical solution: a method for early warning and dynamic tracking monitoring of substation main equipment, the method comprising the following steps:

[0044] S1. The equipment operating parameters are collected in real time through the built-in sensors of the main substation equipment to generate the equipment status information of the corresponding main substation equipment; the abnormal fluctuation items in the equipment status information are summarized to obtain the abnormal status summary information; the abnormal interference risk source set corresponding to the abnormal status summary information is locked in combination with the preset table of the database and the historical maintenance data of the main substation equipment;

[0045] The equipment status information of the corresponding substation main equipment in S1 includes the voltage and current corresponding to different components of the corresponding substation main equipment at different time points;

[0046] Each element in the abnormal status summary information corresponds to an abnormal fluctuation item in the equipment status information; the abnormal fluctuation item represents the monitoring result in the corresponding equipment status information that does not belong to the preset monitoring threshold interval corresponding to the corresponding data item, or each monitoring result in the corresponding equipment status information whose monitoring fluctuation change coefficient within the preset unit time is greater than the abnormal fluctuation threshold of the corresponding data item, and the data items include voltage and current; the monitoring fluctuation change coefficient of each monitoring result within the preset unit time is equal to the quotient of the difference between the maximum monitoring result and the minimum monitoring result of the corresponding data item in the most recent unit time divided by the preset unit time; the abnormal fluctuation threshold of the corresponding data item is the average value of each abnormal fluctuation coefficient corresponding to the corresponding data item when the substation main equipment is abnormal in the historical maintenance data.

[0047] In the process of locking the set of abnormal interference risk sources corresponding to the abnormal state summary information in S1, the monitoring positions corresponding to each substation main equipment in the preset table of the database and the data pairs consisting of the abnormal fluctuation items corresponding to the corresponding model of substation main equipment at each maintenance abnormality in the historical maintenance data of the substation main equipment and the abnormal monitoring positions in the maintenance results are obtained; the abnormal interference risk source array corresponding to each element in the abnormal state summary information is obtained, and the abnormal interference risk source array is an array consisting of the abnormal monitoring positions in the maintenance results in each data pair corresponding to the abnormal fluctuation items in the historical maintenance data of the corresponding model of substation main equipment and the corresponding elements in the abnormal state summary information; an abnormal monitoring position in a maintenance result corresponding to each abnormal interference risk source in the abnormal interference risk source array; the set of the abnormal interference risk source array corresponding to each element in the abnormal state summary information is recorded as the locking result of the abnormal interference risk source set corresponding to the abnormal state summary information.

[0048] S2. Combine historical maintenance data to obtain the associated equipment corresponding to each abnormal interference risk source and the associated items of equipment operation parameters in the corresponding associated equipment, and build an early warning association chain for each abnormal interference risk source;

[0049] The S2 includes:

[0050] S21, obtaining associated devices corresponding to each abnormal interference risk source, wherein the associated devices corresponding to the abnormal interference risk source are each substation device connected to the abnormal interference risk source;

[0051] S22, obtaining equipment operation parameter associated items in the corresponding associated equipment in the historical maintenance data, wherein the equipment operation parameter associated items in the corresponding associated equipment are equipment operation parameter items whose monitoring fluctuation change coefficients of the corresponding associated equipment in the preset unit time in the historical maintenance data do not belong to the corresponding fluctuation change coefficient interval in the preset unit time, and the corresponding fluctuation change coefficient interval in the preset unit time is an interval consisting of the maximum value and the minimum value of the fluctuation change coefficients of the corresponding operation parameter items at each time point in the preset unit time;

[0052] S23. Each device operating parameter associated item in the associated device corresponding to the abnormal interference risk source is used as a chain node in the early warning association chain of the corresponding abnormal interference risk source to obtain the early warning association chain of each abnormal interference risk source.

[0053] S3. Analyze the risk confidence value of the early warning association chain of each abnormal interference risk source based on the corresponding abnormal interference risk source according to the data fluctuation of the same data type as the node in the early warning association chain of the abnormal interference risk source in the equipment status information of the main substation equipment;

[0054] The S3 includes:

[0055] The calculation formula for the risk confidence value of the early warning association chain based on the analysis of each abnormal interference risk source is as follows:

[0056]

[0057] Among them, FR i Indicates that the early warning association chain of the ith abnormal interference risk source in the abnormal interference risk source set corresponding to the abnormal state summary information is based on the risk confidence value of the corresponding abnormal interference risk source; X (i，j) Indicates the monitoring fluctuation variation coefficient of the jth chain node in the early warning association chain of the i-th abnormal interference risk source in the abnormal interference risk source set corresponding to the abnormal state summary information within the preset unit time before the current time; Q (i，j) Indicates the fluctuation change coefficient interval of the jth chain node in the early warning association chain of the ith abnormal interference risk source in the abnormal interference risk source set corresponding to the abnormal state summary information within the preset unit time before the current time; N (i，j) represents the total number of chain nodes in the early warning association chain of the ith abnormal interference risk source in the abnormal interference risk source set corresponding to the abnormal state summary information, and N (i，j) >0; count{} indicates a statistical function; Indicates that the value range of j is in the interval [1, N (i，j) ], the condition is met The number of values ​​of , and j is an integer.

[0058] S4. Combining the similarity of the chain nodes in the early warning association chain of different abnormal interference risk sources, the risk confidence value corresponding to the corresponding abnormal interference risk source, and the distance between the corresponding positions of the corresponding abnormal risk source, the elements in the abnormal interference risk source set corresponding to the abnormal state summary information are fused and determined to generate a new abnormal interference risk source set corresponding to the abnormal state summary information;

[0059] The method for fusing and determining the elements in the abnormal interference risk source set corresponding to the abnormal state summary information in S4 comprises the following steps:

[0060] S41, obtaining an early warning association chain corresponding to each element in the abnormal interference risk source set corresponding to the abnormal state summary information, respectively combining any two elements in the abnormal interference risk source set corresponding to the abnormal state summary information to generate different element combination pairs, and recording any element combination as (W1, W2), where W1 represents the first abnormal interference risk source in the corresponding element combination pair, and W2 represents the second abnormal interference risk source in the corresponding element combination pair;

[0061] S42. Calculate the element fusion bias value corresponding to (W1, W2) according to the element determination formula, and the element determination formula is as follows:

[0062] PR (W1 , W2) =E (W1 , W2) ·LB (W1 , W2) ·[1-(1-FR{W1})·(1-FR{W2})]

[0063] Among them, PR (W1，W2) Indicates the element fusion bias value corresponding to (W1, W2);

[0064] E (W1，W2) represents the similarity of the chain nodes in the early warning association chain corresponding to W1 and W2 respectively; E (W1，W2) =M (W1，W2) / MB (W1，W2) ;M (W1，W2) MB represents the number of identical chain nodes in the early warning association chains corresponding to W1 and W2 respectively; (W1，W2) Represents the total number of elements in the union of the link point sets corresponding to each early warning association chain in W1 and W2;

[0065] FR{W1} represents the risk confidence value of the early warning association chain of W1 based on the corresponding abnormal interference risk source;

[0066] FR{W2} represents the risk confidence value of the early warning association chain of W2 based on the corresponding abnormal interference risk source;

[0067] LB (W1，W2) Represents the quotient of the distance between the corresponding positions of W1 and W2 and the preset fusion determination distance;

[0068] S43, compare the maximum element fusion bias value with the fusion determination factor, where the fusion determination factor is a constant preset in the database; when the maximum element fusion bias value is less than the fusion determination factor, the current corresponding abnormal interference risk source set is transmitted to S44; otherwise, the two elements in the element combination pair with the largest corresponding element fusion bias value are fused, and the fused elements are used to replace the corresponding two elements in the abnormal interference risk source set, and the new abnormal interference risk source set generated by the substitution is transmitted to S41 for iteration;

[0069] S44. Use the transmission result of S43 as a new abnormal interference risk source set corresponding to the abnormal state summary information.

[0070] In the process of fusion judgment of elements in the abnormal interference risk source set corresponding to the abnormal state summary information in this embodiment, the fused elements will replace the corresponding elements before fusion in the corresponding abnormal interference risk source set, and the replaced elements before fusion in the corresponding abnormal interference risk source set will be deleted; and the abnormal interference risk source set after the element replacement will be used as the transmission data and executed again from S41 to implement the iteration of the corresponding element fusion process, until all elements in the abnormal interference risk source set after the element replacement do not meet the fusion judgment condition, then the iteration of the corresponding element fusion process is stopped, and the new abnormal interference risk source set corresponding to the abnormal state summary information is output through S44.

[0071] The fused element in S43 represents the set formed by the corresponding monitoring positions before fusion; the early warning association chain corresponding to the fused element is the summary set of chain nodes in the early warning association chains before fusion; the early warning association chain of the fused element is based on the risk confidence value of the corresponding abnormal interference risk source, which is equal to the difference between 1 and the product of the absolute value of the difference between the risk confidence value corresponding to each element before fusion and 1; the distance between the fused element and the corresponding positions of the remaining abnormal interference risk sources is equal to the minimum value of the distance between each element and the corresponding positions of the remaining abnormal interference risk sources before fusion.

[0072] S5. Combine the new abnormal interference risk source set corresponding to the abnormal state summary information and the early warning association chain of each abnormal interference risk source to build an early warning tracking and monitoring object set, and feed back the obtained early warning tracking and monitoring object set to the administrator to assist in generating a screening decision for the substation main equipment tracking and monitoring object;

[0073] In the S5, each early warning tracking and monitoring object in the early warning tracking and monitoring object set corresponds to an abnormal interference risk source, and each early warning tracking and monitoring object is an array consisting of the corresponding abnormal interference risk source, the early warning association chain of the corresponding abnormal interference risk source, and the risk confidence value corresponding to the corresponding abnormal interference risk source;

[0074] The elements in the early warning tracking and monitoring object set are arranged in descending order according to the risk confidence values ​​corresponding to the corresponding abnormal interference risk sources.

[0075] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0076] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for early warning and dynamic tracking monitoring of main substation equipment, characterized in that: The method comprises the following steps: S1. The equipment operating parameters are collected in real time through the built-in sensors of the main substation equipment to generate the equipment status information of the corresponding main substation equipment; the abnormal fluctuation items in the equipment status information are summarized to obtain the abnormal status summary information; the abnormal interference risk source set corresponding to the abnormal status summary information is locked in combination with the preset table of the database and the historical maintenance data of the main substation equipment; S2. Combine historical maintenance data to obtain the associated equipment corresponding to each abnormal interference risk source and the associated items of equipment operation parameters in the corresponding associated equipment, and build an early warning association chain for each abnormal interference risk source; S3. Analyze the risk confidence value of the early warning association chain of each abnormal interference risk source based on the corresponding abnormal interference risk source according to the data fluctuation of the same data type as the node in the early warning association chain of the abnormal interference risk source in the equipment status information of the main substation equipment; S4. Combining the similarity of the chain nodes in the early warning association chain of different abnormal interference risk sources, the risk confidence value corresponding to the corresponding abnormal interference risk source, and the distance between the corresponding positions of the corresponding abnormal risk source, the elements in the abnormal interference risk source set corresponding to the abnormal state summary information are fused and determined to generate a new abnormal interference risk source set corresponding to the abnormal state summary information; S5. Combine the new set of abnormal interference risk sources corresponding to the abnormal status summary information and the early warning association chain of each abnormal interference risk source to build an early warning tracking and monitoring object set, and feed back the obtained early warning tracking and monitoring object set to the administrator to assist in generating substation main equipment tracking and monitoring object screening decisions.

2. The method for early warning and dynamic tracking monitoring of main substation equipment according to claim 1 is characterized in that: The equipment status information of the corresponding substation main equipment in S1 includes the voltage and current corresponding to different components of the corresponding substation main equipment at different time points; Each element in the abnormal status summary information corresponds to an abnormal fluctuation item in the device status information; The abnormal fluctuation item represents the monitoring result in the corresponding device status information that does not belong to the preset monitoring threshold interval corresponding to the corresponding data item, or each monitoring result in the corresponding device status information whose monitoring fluctuation change coefficient within the preset unit time is greater than the abnormal fluctuation threshold of the corresponding data item, and the data items include voltage and current.

3. The method for early warning and dynamic tracking monitoring of main substation equipment according to claim 2 is characterized in that: The monitoring fluctuation change coefficient of each monitoring result within the preset unit time is equal to the quotient of the difference between the maximum monitoring result and the minimum monitoring result of the corresponding data item in the most recent unit time divided by the preset unit time; the abnormal fluctuation threshold of the corresponding data item is the average value of the abnormal fluctuation coefficients corresponding to the corresponding data items when the substation main equipment is abnormal in the historical maintenance data.

4. The method for early warning and dynamic tracking monitoring of main substation equipment according to claim 2 is characterized in that: In the process of locking the set of abnormal interference risk sources corresponding to the abnormal state summary information in S1, the monitoring positions corresponding to each substation main equipment in the preset table of the database and the data pairs consisting of the abnormal fluctuation items corresponding to the corresponding model of substation main equipment at each maintenance abnormality in the historical maintenance data of the substation main equipment and the abnormal monitoring positions in the maintenance results are obtained; the abnormal interference risk source array corresponding to each element in the abnormal state summary information is obtained, and the abnormal interference risk source array is an array consisting of the abnormal monitoring positions in the maintenance results in each data pair corresponding to the abnormal fluctuation items in the historical maintenance data of the corresponding model of substation main equipment and the corresponding elements in the abnormal state summary information; an abnormal monitoring position in a maintenance result corresponding to each abnormal interference risk source in the abnormal interference risk source array; the set of the abnormal interference risk source array corresponding to each element in the abnormal state summary information is recorded as the locking result of the abnormal interference risk source set corresponding to the abnormal state summary information.

5. The method for early warning and dynamic tracking monitoring of main substation equipment according to claim 1 is characterized in that: The S2 includes: S21, obtaining associated devices corresponding to each abnormal interference risk source, wherein the associated devices corresponding to the abnormal interference risk source are each substation device connected to the abnormal interference risk source; S22, obtaining equipment operation parameter associated items in the corresponding associated equipment in the historical maintenance data, wherein the equipment operation parameter associated items in the corresponding associated equipment are equipment operation parameter items whose monitoring fluctuation change coefficients of the corresponding associated equipment in the preset unit time in the historical maintenance data do not belong to the corresponding fluctuation change coefficient interval in the preset unit time, and the corresponding fluctuation change coefficient interval in the preset unit time is an interval consisting of the maximum value and the minimum value of the fluctuation change coefficients of the corresponding operation parameter items at each time point in the preset unit time; S23. Each device operating parameter associated item in the associated device corresponding to the abnormal interference risk source is used as a chain node in the early warning association chain of the corresponding abnormal interference risk source to obtain the early warning association chain of each abnormal interference risk source.

6. A method for early warning and dynamic tracking monitoring of main substation equipment according to claim 5, characterized in that: The S3 includes: The calculation formula for the risk confidence value of the early warning association chain based on the analysis of each abnormal interference risk source is as follows: Among them, FR i Indicates that the early warning association chain of the ith abnormal interference risk source in the abnormal interference risk source set corresponding to the abnormal state summary information is based on the risk confidence value of the corresponding abnormal interference risk source; X (i，j) Indicates the monitoring fluctuation variation coefficient of the jth chain node in the early warning association chain of the i-th abnormal interference risk source in the abnormal interference risk source set corresponding to the abnormal state summary information within the preset unit time before the current time; Q (i，j) Indicates the fluctuation change coefficient interval of the jth chain node in the early warning association chain of the ith abnormal interference risk source in the abnormal interference risk source set corresponding to the abnormal state summary information within the preset unit time before the current time; N (i，j) represents the total number of chain nodes in the early warning association chain of the ith abnormal interference risk source in the abnormal interference risk source set corresponding to the abnormal state summary information, and N (i，j) >0; count{} indicates statistical function; Indicates that the value range of j is in the interval [1, N (i，j) ], the condition is met The number of values ​​of , and j is an integer.

7. The method for early warning and dynamic tracking monitoring of main substation equipment according to claim 1 is characterized in that: The method for fusing and determining the elements in the abnormal interference risk source set corresponding to the abnormal state summary information in S4 comprises the following steps: S41, obtaining an early warning association chain corresponding to each element in the abnormal interference risk source set corresponding to the abnormal state summary information, respectively combining any two elements in the abnormal interference risk source set corresponding to the abnormal state summary information to generate different element combination pairs, and recording any element combination as (W1, W2), where W1 represents the first abnormal interference risk source in the corresponding element combination pair, and W2 represents the second abnormal interference risk source in the corresponding element combination pair; S42, calculating the element fusion bias value corresponding to (W1, W2) according to the element determination formula; S43, compare the maximum element fusion bias value with the fusion determination factor, where the fusion determination factor is a constant preset in the database; when the maximum element fusion bias value is less than the fusion determination factor, the current corresponding abnormal interference risk source set is transmitted to S44; otherwise, the two elements in the element combination pair with the largest corresponding element fusion bias value are fused, and the fused elements are used to replace the corresponding two elements in the abnormal interference risk source set, and the new abnormal interference risk source set generated by the substitution is transmitted to S41 for iteration; S44. Use the transmission result of S43 as a new abnormal interference risk source set corresponding to the abnormal state summary information.

8. The method for early warning and dynamic tracking monitoring of main substation equipment according to claim 7 is characterized in that: The element determination formula for calculating the element fusion bias value corresponding to (W1, W2) is as follows: PR (W1 , W2) =E (W1 , W2) LB (W1 , W2) [1-(1-FR{W1}) (1-FR{W2})] Among them, PR (W1，W2) Indicates the element fusion bias value corresponding to (W1, W2); E (W1，W2) represents the similarity of the chain nodes in the early warning association chain corresponding to W1 and W2 respectively; E (W1，W2) =M (W1，W2) / MB (W1，W2) ;M (W1，W2) MB represents the number of identical chain nodes in the early warning association chains corresponding to W1 and W2 respectively; (W1，W2) Represents the total number of elements in the union of the link point sets corresponding to each early warning association chain in W1 and W2; FR{W1} represents the risk confidence value of the early warning association chain of W1 based on the corresponding abnormal interference risk source; FR{W2} represents the risk confidence value of the early warning association chain of W2 based on the corresponding abnormal interference risk source; LB (W1，W2) Represents the quotient of the distance between the corresponding positions of W1 and W2 and the preset fusion judgment distance.

9. The method for early warning and dynamic tracking monitoring of main substation equipment according to claim 7 is characterized in that: The fused element in S43 represents a set of corresponding monitoring positions before fusion; the early warning association chain corresponding to the fused element is a summary set of chain nodes in each early warning association chain before fusion; the early warning association chain of the fused element is based on the risk confidence value of the corresponding abnormal interference risk source equal to 1 minus the product of the absolute value of the difference between the risk confidence value corresponding to each element before fusion and 1; The distance between the fused element and the corresponding positions of the remaining abnormal interference risk sources is equal to the minimum value of the distance between each element and the corresponding positions of the remaining abnormal interference risk sources before fusion.

10. The method for early warning and dynamic tracking monitoring of main substation equipment according to claim 1, characterized in that: In the S5, each early warning tracking and monitoring object in the early warning tracking and monitoring object set corresponds to an abnormal interference risk source, and each early warning tracking and monitoring object is an array consisting of the corresponding abnormal interference risk source, the early warning association chain of the corresponding abnormal interference risk source, and the risk confidence value corresponding to the corresponding abnormal interference risk source; The elements in the early warning tracking and monitoring object set are arranged in descending order according to the risk confidence values ​​corresponding to the corresponding abnormal interference risk sources.

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