Credibility correction method and device, equipment, storage medium and program product

Abstract

The invention relates to a credibility correction method and device, equipment, a storage medium and a program product. The method comprises the following steps: determining a power failure study and judgment result of each sampling moment in each time period according to a current value of each sampling moment in different time periods of a transformer area and a first number of the sampling moments, determining a second number of each study and judgment type in each time period according to the power failure study and judgment result of each sampling moment in each time period, and determining the basic step length of the same study and judgment type based on the second number of the same study and judgment type in each time period, and finally correcting the initial credibility according to the basic step length corresponding to each study and judgment type, and the initial credibility and the matching degree coefficient of the power failure study and judgment result. The matching degree coefficient can reflect the recent load change condition of the transformer area, so that the credibility of the power failure research and judgment result can be corrected according to the recent power failure research and judgment result of the transformer area and the load change condition, and the accuracy of the credibility of the power failure research and judgment result is improved.

Description

Technical Field

[0001] The present application relates to the technical field of power outage analysis and judgment, and in particular to a credibility correction method, device, equipment, storage medium and program product. Background Art

[0002] With the improvement of people's quality of life, the demand for power supply reliability is gradually increasing. In the power supply system, power outages are an inevitable phenomenon. Therefore, it is extremely important to quickly and accurately judge the power outage events and obtain the power outage judgment results, and take timely response measures based on the power outage judgment results to reduce the impact of power outages on users.

[0003] At present, it is usually necessary to calculate the credibility of the power outage assessment results in order to evaluate the power outage assessment results through the credibility. However, the credibility of the calculated power outage assessment results may have a low accuracy problem. Therefore, how to correct the credibility of the power outage assessment results to improve the accuracy of the credibility of the corrected power outage assessment results has become a key problem to be solved in this field. Summary of the invention

[0004] Based on this, it is necessary to provide a credibility correction method, device, equipment, storage medium and program product that can correct the credibility of power outage assessment results to improve the accuracy of the credibility of the corrected power outage assessment results in response to the above technical problems.

[0005] In a first aspect, the present application provides a credibility correction method. The method comprises:

[0006] Determine the power outage analysis result at each sampling moment in each time period according to the current value at each sampling moment in different time periods of the substation and the first number at the sampling moment;

[0007] Determine the second quantity of each determination type in each time period according to the power outage determination result at each sampling moment in each time period;

[0008] Determining a basic step length of the same analysis type based on the second number of the same analysis type in each of the time periods;

[0009] The initial credibility is corrected according to the basic step size corresponding to each judgment type, the initial credibility and the matching coefficient of the power outage judgment result; the matching coefficient is a coefficient determined according to the load of the most recent preset number of days.

[0010] In one embodiment, the power outage analysis result at each sampling moment in each time period is determined according to the current value at each sampling moment in different time periods of the substation and the first number of the sampling moments, including:

[0011] For each target sampling moment in each time period, determine the difference between the current value at the target sampling moment and the current value at a sampling moment before the target sampling moment; the target sampling moment is any sampling moment in each time period except the first sampling moment;

[0012] The power outage analysis result at the target sampling moment is determined based on the difference and the preset current difference threshold.

[0013] In one embodiment, the second number of each determination type in each time period is determined according to the power outage determination result at each sampling moment in each time period, including:

[0014] Obtaining the actual power outage results at each sampling time within each time period;

[0015] For each of the time periods, the second quantity of each analysis type in the time period is determined according to the actual power outage result at each sampling moment in the time period and the corresponding power outage analysis result.

[0016] In one embodiment, the basic step length of the same judgment type is determined based on the second number of the same judgment type in each time period, including:

[0017] Determine an initial basic step length based on a second number of the same judgment type in each of the time periods and a preset threshold; the preset threshold includes a first threshold and a second threshold;

[0018] Determine a first coefficient corresponding to the initial basic step length according to the second number corresponding to the first time period in each of the time periods, the second number corresponding to the second time period, and two different first preset coefficients;

[0019] Determine a second coefficient corresponding to the initial basic step length based on the second number corresponding to the second time period in each of the time periods, the second number corresponding to the third time period, and two different second preset coefficients;

[0020] Determine a third coefficient corresponding to the initial basic step length based on the second number corresponding to the third time period in each of the time periods, the second number corresponding to the fourth time period, and two different third preset coefficients;

[0021] A first product of the initial basic step length, the first coefficient, the second coefficient, and the third coefficient is determined, and the basic step length is determined according to the first product.

[0022] In one embodiment, the initial credibility is corrected according to the basic step size corresponding to each judgment type, the initial credibility and the matching coefficient of the power outage judgment result, including:

[0023] Determine a second product of a second number of misjudgment types corresponding to the first time period and a basic step length corresponding to the misjudgment type;

[0024] Determine a third product of a second number of missed detection types corresponding to the first time period and a basic step length corresponding to the missed detection type;

[0025] Determine a fourth product of a second number of positive judgment types corresponding to the first time period and a basic step length corresponding to the positive judgment type;

[0026] Determine a comprehensive step length according to the second product, the third product, and the fourth product;

[0027] According to the comprehensive step length, the initial credibility of the power outage analysis result and the matching coefficient, the initial credibility is corrected.

[0028] In one embodiment, the initial credibility is corrected according to the comprehensive step length, the initial credibility of the power outage analysis result and the matching coefficient, including:

[0029] determining a fifth product between the matching coefficient and the integrated step length;

[0030] The sum of the fifth product and the initial credibility is determined as the target credibility to correct the initial credibility.

[0031] In a second aspect, the present application also provides a credibility correction device. The device comprises:

[0032] A first determination module is used to determine the power outage analysis result at each sampling moment in each time period according to the current value at each sampling moment in different time periods of the substation and the first number of the sampling moment;

[0033] A second determination module is used to determine the second quantity of each determination type in each time period according to the power outage determination result at each sampling moment in each time period;

[0034] A third determination module is used to determine a basic step length of the same determination type based on the second number of the same determination type in each of the time periods;

[0035] The correction module is used to correct the initial credibility of the power outage judgment result according to the basic step size corresponding to each judgment type, the initial credibility and the matching coefficient; the matching coefficient is a coefficient determined according to the load of the last preset number of days.

[0036] In a third aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any of the above methods when executing the computer program.

[0037] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of any of the above methods when executed by a processor.

[0038] In a fifth aspect, the present application also provides a computer program product, including a computer program, which implements the steps of any of the above methods when executed by a processor.

[0039] The above-mentioned credibility correction method, device, equipment, storage medium and program product determine the power outage judgment result at each sampling moment in each time period according to the current value at each sampling moment in different time periods of the substation and the first number of sampling moments, determine the second number of each judgment type in each time period according to the power outage judgment result at each sampling moment in each time period, determine the basic step length of the same judgment type based on the second number of the same judgment type in each time period, and finally correct the initial credibility according to the basic step length corresponding to each judgment type, the initial credibility of the power outage judgment result and the matching coefficient. Since the matching coefficient in the embodiment of the present application is determined based on the load of the most recent preset number of days, the matching coefficient can reflect the recent changes in the load of the substation, so that the credibility of the power outage judgment result can be corrected according to the recent power outage judgment result and the load changes in the substation, thereby improving the accuracy of the credibility of the power outage judgment result. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is an internal structure diagram of a computer device provided in an embodiment of the present application;

[0041] Figure 2 It is a flow chart of a credibility correction method provided in an embodiment of the present application;

[0042] Figure 3 It is a flowchart of a method for determining a matching coefficient provided in an embodiment of the present application;

[0043] Figure 4 It is a flowchart of a method for determining a power outage analysis result provided by an embodiment of the present application;

[0044] Figure 5 It is a flowchart of another method for determining a power outage analysis result provided in an embodiment of the present application;

[0045] Figure 6 is a flow chart of a second quantity determination method provided in an embodiment of the present application;

[0046] Figure 7 is a flowchart of another second quantity determination method provided in an embodiment of the present application;

[0047] Figure 8It is a flowchart of a basic step length determination method provided in an embodiment of the present application;

[0048] Fig. 9 is a flowchart of another basic step length determination method provided in an embodiment of the present application;

[0049] Fig.10 It is a flowchart of an initial credibility correction method provided in an embodiment of the present application;

[0050] Fig.11 It is a flowchart of another initial credibility correction method provided in an embodiment of the present application;

[0051] Fig.12 It is a structural block diagram of a credibility correction device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0053] With the improvement of people's quality of life, the demand for power supply reliability is gradually increasing. In the power supply system, power outages are an inevitable phenomenon. Therefore, it is extremely important to quickly and accurately judge the power outage events and obtain the power outage judgment results, and take timely response measures based on the power outage judgment results to reduce the impact of power outages on users.

[0054] At present, it is usually necessary to calculate the credibility of the power outage assessment results in order to evaluate the power outage assessment results through the credibility. However, the credibility of the calculated power outage assessment results may have a low accuracy problem. Therefore, how to correct the credibility of the power outage assessment results to improve the accuracy of the credibility of the corrected power outage assessment results has become a key problem to be solved in this field.

[0055] The credibility correction method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Figure 1 is an internal structure diagram of a computer device provided in an embodiment of the present application. The computer device may be a server, and its internal structure diagram may be as follows Figure 1As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a credibility correction method is implemented.

[0056] Those skilled in the art will understand that Figure 1 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0057] In one embodiment, Figure 2 As shown, Figure 2 is a flow chart of a credibility correction method provided in an embodiment of the present application, which can be applied to Figure 1 The computer device comprises the following steps:

[0058] S201, determining a power outage analysis result at each sampling moment in each time period according to the current value at each sampling moment in different time periods of the substation and the first number of sampling moments.

[0059] For example, four time periods can be determined, namely, the previous day, the previous week, the previous month, and the previous three months. In each time period, a sampling moment is determined every 15 minutes, that is, there are 96 sampling moments in the previous day, 7×96 sampling moments in the previous week, and so on. Then, the first number of sampling moments in each time period is determined, for example, the first number of sampling moments in the previous day is 96. (It should be noted that the first number of sampling moments in the previous day is 96, which is an ideal condition. If there is an abnormality during sampling, the first number of sampling moments in the previous day may be less than 96).

[0060] Optionally, for each sampling moment in each time period, the power outage analysis result at the sampling moment can be determined based on the current value at the sampling moment, the current value at the sampling moment before the sampling moment, and a preset current difference threshold.

[0061] Taking the time period of the previous day as an example, starting from the second sampling moment in the previous day, each sampling moment is determined as the target sampling moment in turn. Then determine the current difference between the current value at the target sampling moment and the current value at the previous sampling moment of the target sampling moment. If the current difference is greater than the preset current difference threshold, the power outage judgment result at the target sampling moment is determined to be no power outage; if the current difference is not greater than the preset current difference threshold, the power outage judgment result at the target sampling moment is determined to be a power outage. When calculating the power outage judgment results at each sampling moment in the previous day, since there is no previous sampling moment of the first sampling moment, 95 power outage judgment results can be determined.

[0062] S202: Determine a second quantity of each determination type in each time period according to the power outage determination result at each sampling moment in each time period.

[0063] Optionally, the judgment types may include false judgment, missed judgment and correct judgment.

[0064] In one embodiment, the actual power outage result at each sampling moment in each time period can be determined, and the actual power outage result at the same sampling moment can be compared with the power outage judgment result. If the actual power outage result is no power outage, and the power outage judgment result is power outage, then the judgment type at the sampling moment is determined to be a misjudgment; if the actual power outage result is a power outage, and the power outage judgment result is no power outage, then the judgment type at the sampling moment is determined to be a missed judgment; if the actual power outage result is a power outage, and the power outage judgment result is not a power outage, then the judgment type at the sampling moment is determined to be a missed judgment; if the actual power outage result is consistent with the power outage judgment result, then the judgment type at the sampling moment is determined to be a correct judgment.

[0065] Exemplarily, the second number of each analysis and judgment type in each time period can be initialized to 0, and then for each time period, the actual power outage results and the power outage analysis and judgment results at each sampling moment in the time period are compared in turn; if it is determined that the analysis and judgment type at the sampling moment is a misjudgment, the second number of the misjudgment types in the time period is increased by one; if it is determined that the analysis and judgment type at the sampling moment is a missed judgment, the second number of the missed judgment types in the time period is increased by one; if it is determined that the analysis and judgment type at the sampling moment is a correct judgment, the second number of the correct judgment types in the time period is increased by one, so that the second number of each analysis and judgment type in each time period can be determined.

[0066] S203, determining a basic step length of the same analysis type based on the second number of the same analysis type in each time period.

[0067] In an embodiment of the present application, taking the misjudgment type as an example, the basic step length of the misjudgment type can be determined based on the second number of misjudgment types in each time period in the following manner: determine the initial basic step length according to the second number of misjudgment types in the previous month and a preset threshold, and then determine the first coefficient (daily coefficient) corresponding to the initial basic step length according to the second number of misjudgment types in the previous day, the second number of misjudgment types in the previous week, and two different first preset coefficients; determine the second coefficient (weekly coefficient) corresponding to the initial basic step length according to the second number of misjudgment types in the previous week, the second number of misjudgment types in the previous month, and two different second preset coefficients; determine the third coefficient (monthly coefficient) corresponding to the initial basic step length according to the second number of misjudgment types in the previous month, the second number of misjudgment types in the previous three months, and two different third preset coefficients, and then determine the basic step length of the misjudgment type according to the initial basic step length, the first coefficient, the second coefficient, and the third coefficient.

[0068] Optionally, the basic step length of the missed judgment type and the basic step length of the correct judgment type may also be determined in a similar manner as described above.

[0069] S204, correcting the initial credibility according to the basic step length corresponding to each judgment type, the initial credibility of the power outage judgment result and the matching coefficient.

[0070] The matching coefficient is a coefficient determined according to the load of the most recent preset days.

[0071] Optionally, the comprehensive step length of the previous day can be determined based on the basic step length corresponding to each analysis type, and then the initial credibility can be corrected based on the comprehensive step length of the previous day, the initial credibility of the power outage analysis result and the matching coefficient.

[0072] For example, refer to Figure 3 , Figure 3 is a flow chart of a method for determining a matching coefficient provided in an embodiment of the present application. Figure 3 The matching coefficient is determined by the method: Set the preset number of days to 3 days, then the first load of each sampling time in the first day of the substation can be obtained ( ), the second load at each sampling time in the second day forward ( ) and the third load at each sampling time in the third day forward ( ), then determine the first load ( ) and the second load ( ) of the first load matching 、First load( ) and the third load ( ) of the second load matching degree , Second load ( ) and the third load ( ) of the third load matching degree , determine the load matching degree for the past three days based on the first load matching degree, the second load matching degree, and the third load matching degree Finally, the thresholds are set to 70% and 40%, which is the load matching degree for nearly three days. Compared with the thresholds 70% and 40%, if , then determine the matching coefficient ;like , then determine the matching coefficient , otherwise, determine the matching coefficient .

[0073] In the embodiment of the present application, the power outage judgment result at each sampling moment in each time period is determined according to the current value at each sampling moment in different time periods of the substation and the first number of sampling moments, the second number of each judgment type in each time period is determined according to the power outage judgment result at each sampling moment in each time period, the basic step length of the same judgment type is determined based on the second number of the same judgment type in each time period, and finally the initial credibility is corrected according to the basic step length corresponding to each judgment type, the initial credibility of the power outage judgment result and the matching coefficient. Since the matching coefficient in the embodiment of the present application is determined based on the load of the most recent preset number of days, the matching coefficient can reflect the recent changes in the load of the substation, so that the credibility of the power outage judgment result can be corrected according to the recent power outage judgment result and the load changes in the substation, thereby improving the accuracy of the credibility of the power outage judgment result.

[0074] Reference Figure 4 , Figure 4 It is a flow chart of a method for determining a power outage analysis result provided by an embodiment of the present application. This embodiment involves a possible implementation method of how to determine a power outage analysis result at each sampling moment in each time period according to the current value at each sampling moment in different time periods of the substation and the first number of sampling moments. On the basis of the above embodiment, the above S201 includes the following steps:

[0075] S401 , for each target sampling moment in each time period, determining a difference between a current value at the target sampling moment and a current value at a sampling moment before the target sampling moment.

[0076] The target sampling time is any sampling time except the first sampling time in each time period.

[0077] For example, taking the time period of the previous day as an example, starting from the second sampling time in the previous day, each sampling time is determined as the target sampling time in sequence. Then, the current difference between the current value at the target sampling time and the current value at the sampling time before the target sampling time can be determined.

[0078] S402, determining a power outage analysis result at a target sampling time according to the difference value and a preset current difference threshold.

[0079] In one embodiment, taking the time period of the previous day as an example, if the current difference is greater than the preset current difference threshold, the power outage determination result at the target sampling moment is determined to be no power outage; if the current difference is not greater than the preset current difference threshold, the power outage determination result at the target sampling moment is determined to be a power outage. When calculating the power outage determination results at each sampling moment in the previous day, since there is no sampling moment before the first sampling moment, 95 power outage determination results can be determined.

[0080] For example, refer to Figure 5 , Figure 5 FIG. 1 is a flow chart of another method for determining a power outage analysis result provided in an embodiment of the present application. Figure 5 As shown, the preset current difference threshold of the station area can be obtained ( ), the current value at each sampling moment in each time period ( ) and the first number of sampling moments in the time period ( ).make , that is, the second sampling time is determined as the target sampling time, and then the The sampling time and The current difference between the sampling times .like , then determine the The power outage analysis results at the sampling time , otherwise determine the The power outage analysis results at the sampling time . Afterwards, if , then let , which will be The sampling time is taken as the target sampling time, and the above steps are executed again. The power outage analysis result is that there is no power outage. The result of the power outage assessment is power outage.

[0081] In an embodiment of the present application, for each target sampling moment within each time period, the difference between the current value at the target sampling moment and the current value at the sampling moment before the target sampling moment is determined, and the power outage assessment result at the target sampling moment is determined based on the difference and the preset current difference threshold. Thus, the power outage assessment result at each sampling moment can be determined based on the current value at each sampling moment and the preset current difference threshold, which facilitates the subsequent correction of the credibility of the power outage assessment result.

[0082] Reference Figure 6 , Figure 61 is a flow chart of a second quantity determination method provided in an embodiment of the present application. This embodiment involves a possible implementation method of determining the second quantity of each judgment type in each time period based on the power outage judgment result at each sampling moment in each time period. Based on the above embodiment, the above S202 includes the following steps:

[0083] S601, obtaining actual power outage results at each sampling time in each time period.

[0084] Optionally, the actual power outage results at each sampling moment in each time period may be obtained from a local database, a cloud database of a cloud server, or the like.

[0085] S602: For each time period, determine a second quantity of each analysis type in the time period according to the actual power outage result at each sampling moment in the time period and the corresponding power outage analysis result.

[0086] In one embodiment, the actual power outage result at each sampling moment in each time period can be determined, and the actual power outage result at the same sampling moment can be compared with the power outage judgment result. If the actual power outage result is no power outage, and the power outage judgment result is power outage, then the judgment type at the sampling moment is determined to be a misjudgment; if the actual power outage result is a power outage, and the power outage judgment result is no power outage, then the judgment type at the sampling moment is determined to be a missed judgment; if the actual power outage result is a power outage, and the power outage judgment result is not a power outage, then the judgment type at the sampling moment is determined to be a missed judgment; if the actual power outage result is consistent with the power outage judgment result, then the judgment type at the sampling moment is determined to be a correct judgment.

[0087] Exemplarily, the second number of each analysis and judgment type in each time period can be initialized to 0, and then for each time period, the actual power outage results and the power outage analysis and judgment results at each sampling moment in the time period are compared in turn; if it is determined that the analysis and judgment type at the sampling moment is a misjudgment, the second number of the misjudgment types in the time period is increased by one; if it is determined that the analysis and judgment type at the sampling moment is a missed judgment, the second number of the missed judgment types in the time period is increased by one; if it is determined that the analysis and judgment type at the sampling moment is a correct judgment, the second number of the correct judgment types in the time period is increased by one, so that the second number of each analysis and judgment type in each time period can be determined.

[0088] For example, refer to Figure 7 , Figure 7 FIG. 1 is a flow chart of another second quantity determination method provided in an embodiment of the present application. Figure 7 As shown, for each time period, the power outage analysis results at each sampling time within the time period can be obtained ( )、Actual power outage results( ) and the first quantity ( ).make , that is, starting from the first sampling moment in the time period, if the The actual power outage result at the sampling time is a power outage, then The actual power outage results at the sampling time ,otherwise . Afterwards, if , then let , continue to repeat the above steps until all sampling moments are traversed.

[0089] like Figure 7 As shown, , that is, starting from the first sampling moment in the time period, if

[0090] , , then The type of analysis at each sampling moment , that is, The judgment type at the sampling moment is missed judgment; if ,and , then The type of judgment at each sampling moment , that is, The judgment type of the sampling moment is misjudgment; otherwise, determine the The type of judgment at each sampling moment , that is, The judgment type at the sampling moment is positive. , then let , continue to repeat the above steps until all sampling moments are traversed.

[0091] like Figure 7 As shown, the second number of misjudgment types can be initialized , the second number of missed types , the second number of positive judgment types .make , that is, starting from the first sampling moment in the time period, if the Sampling time ,but ; If Sampling time ,but ,otherwise . Afterwards, if , then let , continue to repeat the above steps until all sampling moments are traversed.

[0092] In an embodiment of the present application, the actual power outage results at each sampling moment in each time period are obtained. For each time period, the second number of each judgment type in the time period is determined based on the actual power outage results at each sampling moment in the time period and the corresponding power outage judgment results. Therefore, when determining the judgment type of the power outage judgment result, the second number of each judgment type can be determined, which is convenient for subsequent correction of the credibility of the power outage judgment result.

[0093] Reference Figure 8 , Figure 8 : is a flowchart of a basic step length determination method provided in an embodiment of the present application. This embodiment involves a possible implementation method of how to determine the basic step length of the same judgment type based on the second number of the same judgment type in each time period. Based on the above embodiment, the above S203 includes the following steps:

[0094] S801, determining an initial basic step length based on a second number of the same analysis type in each time period and a preset threshold.

[0095] The preset threshold includes a first threshold and a second threshold.

[0096] In the embodiment of the present application, taking the misjudgment type as an example, the initial basic step length can be determined according to the second number of misjudgment types in the previous month and a preset threshold.

[0097] For example, refer to Fig. 9 , Fig. 9 FIG. 1 is a flow chart of another basic step length determination method provided in an embodiment of the present application. Fig. 9 As shown, for each judgment type, the second quantity of the judgment type in the previous day can be obtained. , the second number of this type of judgment in the previous week , the second number of this type of judgment in the previous month , the second number of this type of judgment within the previous three months , then set the first threshold to 50 and the second threshold to 200. , then determine the initial basic step length ;like , then determine the initial basic step length , otherwise, determine the initial basic step length .

[0098] S802: Determine a first coefficient corresponding to an initial basic step length according to a second number corresponding to a first time period in each time period, a second number corresponding to a second time period, and two different first preset coefficients.

[0099] In this embodiment of the present application, taking the misjudgment type as an example, the first coefficient (daily coefficient) corresponding to the initial basic step size can be determined based on the second number of misjudgment types in the previous day, the second number of misjudgment types in the previous week and two different first preset coefficients.

[0100] For example, Fig. 9 As shown, two different first preset coefficients can be set to 3.5 and 14 respectively. , then determine the day coefficient ;like , then determine the day coefficient , otherwise, determine the day coefficient .

[0101] S803: Determine a second coefficient corresponding to the initial basic step length based on the second number corresponding to the second time period in each time period, the second number corresponding to the third time period, and two different second preset coefficients.

[0102] In this embodiment of the present application, taking the misjudgment type as an example, the second coefficient (weekly coefficient) corresponding to the initial basic step length can be determined based on the second number of misjudgment types in the previous week, the second number of misjudgment types in the previous month, and two different second preset coefficients.

[0103] For example, Fig. 9 As shown, two different second preset coefficients can be set to 2 and 8 respectively. , then determine the cycle coefficient ;like , then determine the cycle coefficient , otherwise, determine the cycle coefficient .

[0104] S804: Determine a third coefficient corresponding to the initial basic step length based on the second number corresponding to the third time period in each time period, the second number corresponding to the fourth time period, and two different third preset coefficients.

[0105] In this embodiment of the present application, taking the misjudgment type as an example, the third coefficient (monthly coefficient) corresponding to the initial basic step size can be determined based on the second number of misjudgment types in the previous month, the second number of misjudgment types in the previous three months, and two different third preset coefficients.

[0106] For example, Fig. 9 As shown, two different third preset coefficients can be set to 1.5 and 6 respectively. , then determine the monthly coefficient ;like , then determine the monthly coefficient , otherwise, determine the monthly coefficient .

[0107] S805, determining a first product of an initial basic step length, a first coefficient, a second coefficient, and a third coefficient, and determining a basic step length according to the first product.

[0108] Exemplarily, the first product of the initial basic step length, the first coefficient, the second coefficient, and the third coefficient may be determined as the basic step length. ,Right now .

[0109] In an embodiment of the present application, an initial basic step is determined based on the second number of the same analysis type in each time period and a preset threshold value; a first coefficient corresponding to the initial basic step is determined based on the second number corresponding to the first time period in each time period, the second number corresponding to the second time period, and two different first preset coefficients; a second coefficient corresponding to the initial basic step is determined based on the second number corresponding to the second time period in each time period, the second number corresponding to the third time period, and two different second preset coefficients; a third coefficient corresponding to the initial basic step is determined based on the second number corresponding to the third time period in each time period, the second number corresponding to the fourth time period, and two different third preset coefficients; and then the first product of the initial basic step, the first coefficient, the second coefficient, and the third coefficient is determined; the basic step is determined based on the first product, so that the initial credibility can be corrected based on the basic step, thereby improving the accuracy of the credibility of the power outage analysis result.

[0110] Reference Fig.10 , Fig.10 This is a flow chart of an initial credibility correction method provided by an embodiment of the present application. This embodiment involves a possible implementation method of how to correct the initial credibility according to the basic step size corresponding to each judgment type, the initial credibility of the power outage judgment result and the matching coefficient. Based on the above embodiment, the above S204 includes the following steps:

[0111] S1001, determining a second product of a second number of misjudgment types corresponding to a first time period and a basic step length corresponding to the misjudgment type.

[0112] For example, the first time period may be the previous day, and the second number of the corresponding misjudgment type in the previous day may be determined. The second product of the basic step length corresponding to the misjudgment type The second product between .

[0113] S1002, determining a third product of a second number of missed detection types corresponding to the first time period and a basic step length corresponding to the missed detection type.

[0114] For example, the second number of missed detection types corresponding to the previous day can be determined. Basic step length corresponding to missed judgment type The third product of .

[0115] S1003: Determine a fourth product of the second number of the positive judgment types corresponding to the first time period and the basic step length corresponding to the positive judgment type.

[0116] For example, the second number of corresponding positive judgment types in the previous day can be determined. Basic step length corresponding to the positive judgment type The fourth product of .

[0117] S1004, determining a comprehensive step length according to the second product, the third product, and the fourth product.

[0118] Exemplarily, the first summation result of the second product, the third product, and the fourth product can be determined as the comprehensive step length ,Right now .

[0119] S1005, correcting the initial credibility based on the comprehensive step length, the initial credibility of the power outage assessment result and the matching coefficient.

[0120] Optionally, the synthesis step size can be determined Matching coefficient The fifth product between them is then used to correct the initial credibility based on the fifth product, and the product result is combined with the initial credibility. The second summation result is determined as the target credibility ,Right now .

[0121] Alternatively, you can also determine the synthesis step size Matching coefficient The fifth product is then optimized, and the initial credibility is corrected based on the optimized fifth product.

[0122] In an embodiment of the present application, the second product of the second number of misjudgment types corresponding to the first time period and the basic step length corresponding to the misjudgment type is determined, the third product of the second number of missed judgment types corresponding to the first time period and the basic step length corresponding to the missed judgment type is determined, and the fourth product of the second number of correct judgment types corresponding to the first time period and the basic step length corresponding to the correct judgment type is determined. Based on the second product, the third product, and the fourth product, the comprehensive step length is determined, and then the initial credibility is corrected based on the comprehensive step length, the initial credibility of the power outage assessment result, and the matching coefficient. In this way, the credibility of the power outage assessment result can be corrected according to the recent power outage assessment situation and load changes in the substation, thereby improving the accuracy of the credibility of the power outage assessment result.

[0123] Reference Fig.11 , Fig.11 This is a flow chart of another method for correcting initial credibility provided by an embodiment of the present application. This embodiment involves a possible implementation method of how to correct the initial credibility based on the comprehensive step length, the initial credibility of the power outage judgment result and the matching coefficient. Based on the above embodiment, the above S1005 includes the following steps:

[0124] S1101, determine the fifth product between the matching coefficient and the comprehensive step length.

[0125] For example, the comprehensive step length can be determined Matching coefficient The fifth product between .

[0126] S1102, determining the sum of the fifth product and the initial credibility as the target credibility, so as to correct the initial credibility.

[0127] For example, the fifth product Initial credibility The sum of the results is determined as the target credibility ,Right now .

[0128] In an embodiment of the present application, the fifth product between the matching coefficient and the comprehensive step length is determined, and the sum of the fifth product and the initial credibility is determined as the target credibility to correct the initial credibility, so that the credibility of the power outage assessment result can be corrected according to the recent power outage assessment situation and load changes in the substation, thereby improving the accuracy of the credibility of the power outage assessment result.

[0129] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0130] Based on the same inventive concept, the embodiment of the present application also provides a credibility correction device for implementing the credibility correction method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more credibility correction device embodiments provided below can refer to the limitations of the credibility correction method above, and will not be repeated here.

[0131] In one embodiment, Fig.12 As shown, Fig.12 12 is a structural block diagram of a credibility correction device provided in an embodiment of the present application. The device 1200 includes:

[0132] The first determination module 1201 is used to determine the power outage analysis result at each sampling moment in each time period according to the current value at each sampling moment in different time periods of the substation and the first number of sampling moments.

[0133] The second determination module 1202 is used to determine the second quantity of each determination type in each time period according to the power outage determination result at each sampling moment in each time period.

[0134] The third determination module 1203 is used to determine the basic step length of the same analysis type based on the second number of the same analysis type in each time period.

[0135] Correction module 1204 is used to correct the initial credibility according to the basic step size corresponding to each judgment type, the initial credibility of the power outage judgment result and the matching coefficient; the matching coefficient is a coefficient determined according to the load of the most recent preset days.

[0136] In one embodiment, the first determining module 1201 includes:

[0137] The first determination unit is used to determine the difference between the current value at the target sampling moment and the current value at the sampling moment before the target sampling moment for each target sampling moment in each time period; the target sampling moment is any sampling moment except the first sampling moment in each time period.

[0138] The second determining unit is used to determine the power outage analysis result at the target sampling time according to the difference and a preset current difference threshold.

[0139] In one embodiment, the second determining module 1202 includes:

[0140] The acquisition unit is used to obtain the actual power outage result at each sampling moment in each time period.

[0141] The third determining unit is used to determine, for each time period, a second number of each analysis type in the time period according to the actual power outage result at each sampling moment in the time period and the corresponding power outage analysis result.

[0142] In one embodiment, the third determining module 1203 includes:

[0143] The fourth determination unit is used to determine the initial basic step size based on the second number of the same analysis type in each time period and a preset threshold; the preset threshold includes a first threshold and a second threshold.

[0144] The fifth determining unit is used to determine the first coefficient corresponding to the initial basic step size according to the second number corresponding to the first time period in each time period, the second number corresponding to the second time period, and two different first preset coefficients.

[0145] The sixth determining unit is used to determine the second coefficient corresponding to the initial basic step size based on the second number corresponding to the second time period in each time period, the second number corresponding to the third time period, and two different second preset coefficients.

[0146] The seventh determining unit is used to determine the third coefficient corresponding to the initial basic step size based on the second number corresponding to the third time period in each time period, the second number corresponding to the fourth time period, and two different third preset coefficients.

[0147] The eighth determination unit is used to determine a first product of an initial basic step length, a first coefficient, a second coefficient, and a third coefficient, and determine the basic step length according to the first product.

[0148] In one embodiment, the correction module 1204 includes:

[0149] The ninth determining unit is used to determine a second product of a second number of misjudgment types corresponding to the first time period and a basic step length corresponding to the misjudgment type.

[0150] The tenth determining unit is used to determine a third product of the second number of missed detection types corresponding to the first time period and the basic step length corresponding to the missed detection type.

[0151] The eleventh determining unit is used to determine a fourth product of the second number of the positive judgment types corresponding to the first time period and the basic step length corresponding to the positive judgment type.

[0152] The twelfth determining unit is used to determine the comprehensive step length according to the second product, the third product and the fourth product.

[0153] The correction unit is used to correct the initial credibility according to the comprehensive step length, the initial credibility and the matching coefficient of the power outage analysis result.

[0154] In one embodiment, the correction unit includes:

[0155] A determination subunit, used to determine the fifth product between the matching coefficient and the comprehensive step length;

[0156] The correction subunit is used to determine the sum of the fifth product and the initial credibility as the target credibility, so as to correct the initial credibility.

[0157] Each module in the above credibility correction device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.

[0158] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0159] Determine the power outage analysis result at each sampling moment in each time period according to the current value at each sampling moment in different time periods of the substation and the first number of sampling moments;

[0160] Determine the second quantity of each judgment type in each time period according to the power outage judgment result at each sampling moment in each time period;

[0161] Determining a basic step length of the same analysis type based on a second number of the same analysis type in each time period;

[0162] The initial credibility is corrected according to the basic step size corresponding to each judgment type, the initial credibility of the power outage judgment result and the matching coefficient; the matching coefficient is a coefficient determined according to the load of the most recent preset number of days.

[0163] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0164] For each target sampling moment in each time period, determine the difference between the current value at the target sampling moment and the current value at the sampling moment before the target sampling moment; the target sampling moment is any sampling moment in each time period except the first sampling moment;

[0165] The power outage analysis result at the target sampling time is determined based on the difference and the preset current difference threshold.

[0166] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0167] Obtain the actual power outage results at each sampling time in each time period;

[0168] For each time period, the second quantity of each analysis type in the time period is determined according to the actual power outage result at each sampling moment in the time period and the corresponding power outage analysis result.

[0169] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0170] Determine an initial basic step length based on a second number of the same judgment type in each time period and a preset threshold value; the preset threshold value includes a first threshold value and a second threshold value;

[0171] Determine a first coefficient corresponding to the initial basic step length according to a second number corresponding to a first time period in each time period, a second number corresponding to a second time period, and two different first preset coefficients;

[0172] Determine a second coefficient corresponding to the initial basic step length based on a second number corresponding to the second time period in each time period, a second number corresponding to the third time period, and two different second preset coefficients;

[0173] Determine a third coefficient corresponding to the initial basic step length based on the second number corresponding to the third time period in each time period, the second number corresponding to the fourth time period, and two different third preset coefficients;

[0174] An initial basic step size, a first coefficient, a second coefficient, and a first product of a third coefficient are determined, and a basic step size is determined according to the first product.

[0175] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0176] Determine a second product of a second number of misjudgment types corresponding to the first time period and a basic step length corresponding to the misjudgment type;

[0177] Determine a third product of a second number of missed detection types corresponding to the first time period and a basic step length corresponding to the missed detection type;

[0178] Determine a fourth product of the second number of positive judgment types corresponding to the first time period and the basic step length corresponding to the positive judgment type;

[0179] Determine the comprehensive step length according to the second product, the third product and the fourth product;

[0180] According to the comprehensive step length, the initial credibility and the matching coefficient of the power outage analysis result, the initial credibility is corrected.

[0181] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0182] Determine the fifth product between the matching coefficient and the integrated step length;

[0183] The sum of the fifth product and the initial credibility is determined as the target credibility to correct the initial credibility.

[0184] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0185] Determine the power outage analysis result at each sampling moment in each time period according to the current value at each sampling moment in different time periods of the substation and the first number of sampling moments;

[0186] Determine the second quantity of each judgment type in each time period according to the power outage judgment result at each sampling moment in each time period;

[0187] Determining a basic step length of the same analysis type based on a second number of the same analysis type in each time period;

[0188] The initial credibility is corrected according to the basic step size corresponding to each judgment type, the initial credibility of the power outage judgment result and the matching coefficient; the matching coefficient is a coefficient determined according to the load of the most recent preset number of days.

[0189] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0190] For each target sampling moment in each time period, determine the difference between the current value at the target sampling moment and the current value at the sampling moment before the target sampling moment; the target sampling moment is any sampling moment in each time period except the first sampling moment;

[0191] The power outage analysis result at the target sampling time is determined based on the difference and the preset current difference threshold.

[0192] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0193] Obtain the actual power outage results at each sampling time in each time period;

[0194] For each time period, the second quantity of each analysis type in the time period is determined according to the actual power outage result at each sampling moment in the time period and the corresponding power outage analysis result.

[0195] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0196] Determine an initial basic step length based on a second number of the same judgment type in each time period and a preset threshold value; the preset threshold value includes a first threshold value and a second threshold value;

[0197] Determine a first coefficient corresponding to the initial basic step length according to a second number corresponding to a first time period in each time period, a second number corresponding to a second time period, and two different first preset coefficients;

[0198] Determine a second coefficient corresponding to the initial basic step length based on a second number corresponding to the second time period in each time period, a second number corresponding to the third time period, and two different second preset coefficients;

[0199] Determine a third coefficient corresponding to the initial basic step length based on the second number corresponding to the third time period in each time period, the second number corresponding to the fourth time period, and two different third preset coefficients;

[0200] An initial basic step size, a first coefficient, a second coefficient, and a first product of a third coefficient are determined, and a basic step size is determined according to the first product.

[0201] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0202] Determine a second product of a second number of misjudgment types corresponding to the first time period and a basic step length corresponding to the misjudgment type;

[0203] Determine a third product of a second number of missed detection types corresponding to the first time period and a basic step length corresponding to the missed detection type;

[0204] Determine a fourth product of the second number of positive judgment types corresponding to the first time period and the basic step length corresponding to the positive judgment type;

[0205] Determine the comprehensive step length according to the second product, the third product and the fourth product;

[0206] According to the comprehensive step length, the initial credibility and the matching coefficient of the power outage analysis result, the initial credibility is corrected.

[0207] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0208] Determine the fifth product between the matching coefficient and the integrated step length;

[0209] The sum of the fifth product and the initial credibility is determined as the target credibility to correct the initial credibility.

[0210] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0211] Determine the power outage analysis result at each sampling moment in each time period according to the current value at each sampling moment in different time periods of the substation and the first number of sampling moments;

[0212] Determine the second quantity of each judgment type in each time period according to the power outage judgment result at each sampling moment in each time period;

[0213] Determining a basic step length of the same analysis type based on a second number of the same analysis type in each time period;

[0214] The initial credibility is corrected according to the basic step size corresponding to each judgment type, the initial credibility of the power outage judgment result and the matching coefficient; the matching coefficient is a coefficient determined according to the load of the most recent preset number of days.

[0215] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0216] For each target sampling moment in each time period, determine the difference between the current value at the target sampling moment and the current value at the sampling moment before the target sampling moment; the target sampling moment is any sampling moment in each time period except the first sampling moment;

[0217] The power outage analysis result at the target sampling time is determined based on the difference and the preset current difference threshold.

[0218] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0219] Obtain the actual power outage results at each sampling time in each time period;

[0220] For each time period, the second quantity of each analysis type in the time period is determined according to the actual power outage result at each sampling moment in the time period and the corresponding power outage analysis result.

[0221] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0222] Determine an initial basic step length based on a second number of the same judgment type in each time period and a preset threshold value; the preset threshold value includes a first threshold value and a second threshold value;

[0223] Determine a first coefficient corresponding to the initial basic step length according to a second number corresponding to a first time period in each time period, a second number corresponding to a second time period, and two different first preset coefficients;

[0224] Determine a second coefficient corresponding to the initial basic step length based on a second number corresponding to the second time period in each time period, a second number corresponding to the third time period, and two different second preset coefficients;

[0225] Determine a third coefficient corresponding to the initial basic step length based on the second number corresponding to the third time period in each time period, the second number corresponding to the fourth time period, and two different third preset coefficients;

[0226] An initial basic step size, a first coefficient, a second coefficient, and a first product of a third coefficient are determined, and a basic step size is determined according to the first product.

[0227] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0228] Determine a second product of a second number of misjudgment types corresponding to the first time period and a basic step length corresponding to the misjudgment type;

[0229] Determine a third product of a second number of missed detection types corresponding to the first time period and a basic step length corresponding to the missed detection type;

[0230] Determine a fourth product of the second number of positive judgment types corresponding to the first time period and the basic step length corresponding to the positive judgment type;

[0231] Determine the comprehensive step length according to the second product, the third product and the fourth product;

[0232] According to the comprehensive step length, the initial credibility and the matching coefficient of the power outage analysis result, the initial credibility is corrected.

[0233] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0234] Determine the fifth product between the matching coefficient and the integrated step length;

[0235] The sum of the fifth product and the initial credibility is determined as the target credibility to correct the initial credibility.

[0236] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0237] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0238] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A credibility correction method, characterized in that: The method comprises: Determine the power outage analysis result at each sampling moment in each time period according to the current value at each sampling moment in different time periods of the substation and the first number of the sampling moments; Determine the second quantity of each determination type in each of the time periods according to the power outage determination results at each of the sampling moments in each of the time periods; Determining a basic step length of the same type of analysis based on a second number of the same type of analysis in each of the time periods; According to the basic step size corresponding to each of the analysis types, the initial credibility and the matching coefficient of the power outage analysis result, the initial credibility is corrected; the matching coefficient is a coefficient determined according to the load of the most recent preset number of days.

2. The method according to claim 1, characterized in that The method of determining the power outage analysis result at each sampling moment in each time period according to the current value at each sampling moment in different time periods of the substation and the first number of the sampling moments includes: For each target sampling moment in each of the time periods, determine the difference between the current value at the target sampling moment and the current value at a sampling moment before the target sampling moment; the target sampling moment is any sampling moment in each of the time periods except the first sampling moment; The power outage analysis result at the target sampling time is determined according to the difference and a preset current difference threshold.

3. The method according to claim 1, characterized in that Determining the second quantity of each determination type in each time period according to the power outage determination result at each sampling moment in each time period includes: Obtaining actual power outage results at each sampling time within each time period; For each of the time periods, the second quantity of each analysis type in the time period is determined according to the actual power outage result at each of the sampling moments in the time period and the corresponding power outage analysis result.

4. The method according to claim 1, characterized in that: The determining of the basic step length of the same judgment type based on the second number of the same judgment type in each of the time periods comprises: Determining an initial basic step length based on a second number of the same judgment type in each of the time periods and a preset threshold; the preset threshold includes a first threshold and a second threshold; Determine a first coefficient corresponding to the initial basic step length according to the second number corresponding to the first time period in each of the time periods, the second number corresponding to the second time period, and two different first preset coefficients; Determine a second coefficient corresponding to the initial basic step length based on the second number corresponding to the second time period in each of the time periods, the second number corresponding to the third time period, and two different second preset coefficients; Determine a third coefficient corresponding to the initial basic step length based on the second number corresponding to the third time period in each of the time periods, the second number corresponding to the fourth time period, and two different third preset coefficients; A first product of the initial basic step size, the first coefficient, the second coefficient, and the third coefficient is determined, and the basic step size is determined according to the first product.

5. The method according to claim 4, characterized in that The initial credibility is corrected according to the basic step length corresponding to each of the judgment types, the initial credibility and the matching coefficient of the power outage judgment result, including: Determine a second product of a second number of misjudgment types corresponding to the first time period and a basic step length corresponding to the misjudgment type; Determine a third product of a second number of missed detection types corresponding to the first time period and a basic step length corresponding to the missed detection type; Determine a fourth product of a second number of positive judgment types corresponding to the first time period and a basic step length corresponding to the positive judgment type; Determine a comprehensive step length according to the second product, the third product, and the fourth product; The initial credibility is corrected according to the comprehensive step length, the initial credibility of the power outage analysis result and the matching coefficient.

6. The method according to claim 5, characterized in that The step of correcting the initial credibility according to the comprehensive step length, the initial credibility of the power outage analysis result and the matching coefficient includes: determining a fifth product between the matching coefficient and the integrated step length; The sum of the fifth product and the initial credibility is determined as the target credibility to correct the initial credibility.

7. A credibility correction device, characterized in that: The device comprises: A first determination module is used to determine the power outage analysis result at each sampling moment in each time period according to the current value at each sampling moment in different time periods of the substation and the first number of the sampling moments; A second determination module is used to determine the second number of each determination type in each of the time periods according to the power outage determination results at each of the sampling moments in each of the time periods; A third determination module is used to determine a basic step length of the same analysis type based on the second number of the same analysis type in each of the time periods; The correction module is used to correct the initial credibility according to the basic step size corresponding to each judgment type, the initial credibility and the matching coefficient of the power outage judgment result; the matching coefficient is a coefficient determined according to the load of the last preset number of days.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

Images