A reliability evaluation method and system for electric energy meters based on comprehensive evaluation and analysis

Abstract

A method and system for evaluating the reliability of electricity meters based on comprehensive evaluation analysis includes: calculating the failure rate and reliability of the electricity meters in multiple preset operating periods based on the number of electricity meters installed at each installation time and the number of failures in each preset operating period provided by each supplier to each region; processing the failure rate and reliability using forward normalization methods, and constructing an evaluation index value matrix using the processed failure rate, reliability, and the number of failures of electricity meters installed at each installation time and in each preset operating period provided by each supplier to each region as evaluation index values; determining the score of the electricity meters provided by each supplier to each region in each preset operating period using the Topsis evaluation method according to the pre-determined weights of each evaluation index based on the entropy weight method, and determining the reliability of the electricity meters provided by each supplier to each region in each preset operating period based on the score. This invention can more accurately evaluate the reliability of electricity meters.

Description

Technical Field

[0001] The present invention relates to the field of reliability analysis of electric energy meters, and in particular to a reliability evaluation method and system for electric energy meters based on comprehensive evaluation and analysis. Background Art

[0002] The existing electricity meter reliability evaluation and analysis method has simple rules and quick results, and can quickly evaluate the reliability of electricity meters in each year. However, the failure rate of electricity meters is calculated only by relying on the number of installed electricity meters in a period of time and the number of failures in a period of time. The index results are easily affected by extreme values, resulting in insufficient analysis accuracy. For the evaluation of the reliability of electricity meters, the failure rate of electricity meters is calculated only by relying on the number of installed electricity meters in a period of time and the number of failures in a period of time after installation. The index results are easily affected by extreme values, resulting in insufficient analysis accuracy; affected by factors such as electricity meter technology updates and business changes, different suppliers may provide electricity meters installed in a certain period of time to different regions. In another period of time, the electricity meters installed may have a higher failure rate. Only using the failure rate cannot reflect the reliability of electricity meters provided by each supplier to each region as a whole; there is no distinction between the failure conditions of electricity meters installed in different years in different operating years after installation. Summary of the invention

[0003] Aiming at the problem that the evaluation index in the reliability evaluation method of electric energy meters in the prior art is easily disturbed by extreme values, resulting in low accuracy of the evaluation result of the reliability of the electric energy meters, the present invention provides an electric energy meter reliability evaluation method based on comprehensive evaluation analysis, comprising:

[0004] Calculate the failure rate and reliability of the electric energy meters provided by each supplier to each region in multiple preset operating time periods based on the number of electric energy meters installed at each installation time and the number of failures in each preset operating time period provided by each supplier to each region;

[0005] The failure rate and reliability are processed by using a forward method and a normalization method, and an evaluation index value matrix is ​​constructed by using the processed failure rate, reliability, and the number of failures of the electric energy meters installed at each installation time in each region provided by each supplier in all preset operating time periods as evaluation index values;

[0006] The Topsis evaluation method is used to determine the scores of the electric energy meters provided by each supplier to each region in each preset operating period according to the weights of each evaluation indicator predetermined based on the entropy weight method for the evaluation index value matrix, and the reliability of the electric energy meters provided by each supplier to each region in each preset operating period is determined based on the scores.

[0007] Preferably, the calculation of the failure rate and reliability of the electric energy meters provided by each supplier to each region in multiple preset operating time periods based on the number of installations of the electric energy meters provided by each supplier to each region at each installation time and the number of failures in each preset operating time period includes:

[0008] The failure rate of the electric energy meters installed at each installation time and provided by each supplier to each region in each preset operating period is calculated as follows:

[0009]

[0010] In the formula, is the failure rate of the electric energy meter installed at time x in the yth operating period provided by supplier F to region E, is the number of failures of the electric energy meters installed at time x and provided by supplier F to region E in the yth operating period, is the total number of electric energy meters installed at time x provided by supplier F to area E, m is the number of installation times of electric energy meters provided by supplier F to area E, and n is the number of operating time periods of electric energy meters provided by supplier F to area E;

[0011] The failure rate of the electric energy meters provided by each supplier to each region in multiple preset operating periods is calculated as follows:

[0012]

[0013] In the formula, is the failure rate of the electric energy meters provided by supplier F to area E in the yth preset operating period;

[0014] The reliability of the electric energy meters provided by each supplier to each region in multiple preset operating periods is calculated as follows:

[0015]

[0016] In the formula, The reliability of the electric energy meter provided by supplier F to area E in the yth operating period.

[0017] Preferably, the Topsis evaluation method is used to determine the scores of the electric energy meters provided by each supplier to each region in each preset operating period according to the weights of each evaluation indicator predetermined based on the entropy weight method for the evaluation index value matrix, and the reliability of the electric energy meters provided by each supplier to each region in each preset operating period is determined according to the scores, including:

[0018] The evaluation index values ​​in the evaluation index value matrix are screened out using the topsis evaluation method to find the best evaluation index value and the worst evaluation index value under each evaluation index, and the distance between each evaluation index value corresponding to the electric energy meter provided by each supplier to each region in each preset operating period and the corresponding best evaluation index and worst evaluation index value is calculated respectively;

[0019] Input the distance between each evaluation index value corresponding to the electric energy meter provided by each supplier to each region in each preset operation period and the corresponding optimal evaluation index and the worst evaluation index value and the predetermined weight of each evaluation index into the comprehensive evaluation analysis calculation formula to obtain the score of the electric energy meter provided by each supplier to each region in each preset operation period;

[0020] The scores of the electric energy meters provided by the suppliers to the respective regions in the preset operating time periods are used to represent the reliability of the electric energy meters provided by the suppliers to the respective regions in the preset operating time periods.

[0021] Preferably, the comprehensive evaluation analysis calculation formula is as follows:

[0022]

[0023] In the formula, is the score corresponding to the electric energy meter provided by the supplier F to the area E in the yth operating period, is the distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding worst evaluation index value, is the distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding optimal evaluation index value;

[0024] The distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding optimal evaluation index value is Calculate as follows:

[0025]

[0026] In the formula, is the optimal evaluation index value of the evaluation index value matrix under the jth evaluation index, is the evaluation index value of the electric energy meter provided by supplier F to area E in the yth operating period under the jth evaluation index, w j is the weight of the jth evaluation index, and h is the number of evaluation indicators;

[0027] The distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding worst evaluation index value Calculate as follows:

[0028]

[0029] In the formula, is the worst evaluation index value of the evaluation index value matrix under the jth evaluation index.

[0030] Preferably, the determination of the weights of the evaluation indicators includes:

[0031] Substituting the ratio of each evaluation index value under each evaluation index to all evaluation index values ​​under the corresponding evaluation index into the entropy value calculation formula in the entropy weight method, the entropy value of each evaluation index is calculated;

[0032] The information entropy redundancy calculation formula is used to calculate the information entropy redundancy of each evaluation indicator according to the entropy value of each evaluation indicator;

[0033] The ratio of the information entropy redundancy of each evaluation indicator to all information entropy redundancies is used as the indicator weight of each evaluation indicator.

[0034] Preferably, the weight of each evaluation index is calculated as follows:

[0035]

[0036] In the formula, w j is the weight of the jth evaluation index, d j is the information entropy redundancy of the j-th evaluation index;

[0037] Among them, the information entropy redundancy of the j-th evaluation index d j , calculated as follows:

[0038] d j =1-e j

[0039] In the formula, e j is the entropy value of the jth evaluation index.

[0040] Based on the same inventive concept, the present invention also provides an electric energy meter reliability evaluation system based on comprehensive evaluation and analysis, comprising:

[0041] A calculation module, which calculates the failure rate and reliability of the electric energy meters provided by each supplier to each region in multiple preset operating time periods based on the number of electric energy meters installed at each installation time and the number of failures in each preset operating time period provided by each supplier to each region;

[0042] A processing module, used to process the failure rate and reliability by using a forward method and a normalization method, and to construct an evaluation index value matrix using the processed failure rate, reliability, and the number of failures of the electric energy meters installed at each installation time in each region provided by each supplier in all preset operating time periods as evaluation index values;

[0043] An evaluation module is used to determine the scores of the electric energy meters provided by each supplier to each region in each preset operating period according to the weights of each evaluation indicator predetermined based on the entropy weight method using the Topsis evaluation method for the evaluation index value matrix, and to determine the reliability of the electric energy meters provided by each supplier to each region in each preset operating period based on the scores.

[0044] Preferably, the calculation module includes:

[0045] The failure rate calculation submodule is used to calculate the failure rate of the electric energy meters installed at each installation time and provided by each supplier to each region in each preset operation period according to the following formula:

[0046]

[0047] In the formula, is the failure rate of the electric energy meter installed at time x in the yth operating period provided by supplier F to region E, is the number of failures of the electric energy meters installed at time x and provided by supplier F to region E in the yth operating period, is the total number of electric energy meters installed at time x provided by supplier F to area E, m is the number of installation times of electric energy meters provided by supplier F to area E, and n is the number of operating time periods of electric energy meters provided by supplier F to area E;

[0048] The failure rate of the electric energy meters provided by each supplier to each region in multiple preset operating periods is calculated as follows:

[0049]

[0050] In the formula, is the failure rate of the electric energy meters provided by supplier F to area E in the yth preset operating period;

[0051] The reliability calculation submodule is used to calculate the reliability of the electric energy meters provided by each supplier to each region in multiple preset operating periods according to the following formula:

[0052]

[0053] In the formula, The reliability of the electric energy meter provided by supplier F to area E in the yth operating period.

[0054] Preferably, the evaluation module includes:

[0055] A distance calculation submodule is used to screen out the optimal evaluation index value and the worst evaluation index value under each evaluation index by using the evaluation index value in the evaluation index value matrix by the topsis evaluation method, and respectively calculate the distance between each evaluation index value corresponding to the electric energy meter provided by each supplier to each region in each preset operating period and the corresponding optimal evaluation index and the worst evaluation index value;

[0056] A score calculation submodule, for inputting the distance between each evaluation index value corresponding to the electric energy meter provided by each supplier to each region in each preset operation period and the corresponding optimal evaluation index and the worst evaluation index value and the predetermined weight of each evaluation index into a comprehensive evaluation analysis calculation formula, to obtain the score of the electric energy meter provided by each supplier to each region in each preset operation period;

[0057] The reliability determination submodule is used to use the scores of the electric energy meters provided by the suppliers to the respective regions in the preset operating time periods to represent the reliability of the electric energy meters provided by the suppliers to the respective regions in the preset operating time periods.

[0058] Preferably, the comprehensive evaluation analysis calculation formula is as follows:

[0059]

[0060] In the formula, is the score corresponding to the electric energy meter provided by the supplier F to the area E in the yth operating period, is the distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding worst evaluation index value, is the distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding optimal evaluation index value;

[0061] The distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding optimal evaluation index value is Calculate as follows:

[0062]

[0063] In the formula, is the optimal evaluation index value of the evaluation index value matrix under the jth evaluation index, is the evaluation index value of the electric energy meter provided by supplier F to area E in the yth operating period under the jth evaluation index, w jis the weight of the jth evaluation index, and h is the number of evaluation indicators;

[0064] The distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding worst evaluation index value Calculate as follows:

[0065]

[0066] In the formula, is the worst evaluation index value of the evaluation index value matrix under the jth evaluation index.

[0067] Compared with the prior art, the present invention has the following beneficial effects:

[0068] The present invention provides a method and system for evaluating the reliability of electric energy meters based on comprehensive evaluation and analysis, including: calculating the failure rate and reliability of electric energy meters provided by each supplier to each region in multiple preset operating periods based on the number of electric energy meters installed at each installation time and the number of failures in each preset operating period provided by each supplier to each region; processing the failure rate and reliability by using a forward method and a normalization method, and using the processed failure rate, reliability, and the number of failures of electric energy meters provided by each supplier to each region at each installation time in all preset operating periods as evaluation index values ​​to construct an evaluation index value matrix; using a Topsis evaluation method to determine the scores of electric energy meters provided by each supplier to each region in each preset operating period according to the weights of each evaluation index predetermined based on an entropy weight method, and determining the reliability of the electric energy meters provided by each supplier to each region in each preset operating period according to the scores. Based on the topsis evaluation method, the present invention uses the number of failures of electric energy meters installed in a set period and the failure rate and reliability of electric energy meters running to the set period as evaluation indicators to evaluate the reliability of electric energy meters, thereby improving the accuracy of reliability evaluation of electric energy meters. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 This is a flow chart of a method for evaluating the reliability of an electric energy meter based on comprehensive evaluation and analysis according to the present invention;

[0070] Figure 2 The present invention is a schematic diagram of an electric energy meter reliability evaluation system based on comprehensive evaluation and analysis. DETAILED DESCRIPTION

[0071] Example 1

[0072] Aiming at the problem that the evaluation index in the reliability evaluation method of electric energy meter in the prior art is easily disturbed by extreme values, resulting in low accuracy of the evaluation result of the reliability of the electric energy meter, the present invention provides an electric energy meter reliability evaluation method based on comprehensive evaluation analysis, such as Figure 1 As shown, including:

[0073] Step 1, calculating the failure rate and reliability of the electric energy meters provided by each supplier to each region in multiple preset operating time periods based on the number of electric energy meters installed at each installation time and the number of failures in each preset operating time period provided by each supplier to each region;

[0074] Step 2, using a forward method and a normalization method to process the failure rate and reliability, and using the processed failure rate, reliability, and the number of failures of the electric energy meters installed at each installation time in each region provided by each supplier in all preset operating time periods as evaluation index values ​​to construct an evaluation index value matrix;

[0075] Step 3, using the Topsis evaluation method to determine the scores of the electric energy meters provided by each supplier to each region in each preset operating period according to the weights of each evaluation indicator predetermined based on the entropy weight method for the evaluation index value matrix, and determine the reliability of the electric energy meters provided by each supplier to each region in each preset operating period based on the scores.

[0076] In this embodiment, the installation time, in-operation data, and operating time period of historical fault data of the electric energy meters corresponding to each region, single-phase supplier, and three-phase supplier are obtained in advance, and the data is pre-processed.

[0077] For each single-phase electricity meter supplier, the data of electricity meters installed in each region where the number of electricity meters installed each year is less than 10,000 electricity meters are eliminated. For each three-phase electricity meter supplier, the data of electricity meters installed in each region where the number of electricity meters installed each year is less than 1,000 electricity meters are eliminated to ensure that the calculated failure rate and reliability are not affected by extreme data.

[0078] In step 1, for the electric energy meters provided by each supplier to each region and installed at each installation time, the failure rates of the electric energy meters provided by each supplier to each region and installed at each installation time in each preset operating time period are first calculated, and then the average value of the failure rates of the electric energy meters provided by each supplier to each region and installed at each installation time in each preset operating time period is taken as the failure rate of the electric energy meters provided by each supplier to each region in multiple preset operating time periods, and finally the reliability of the electric energy meters provided by each supplier to each region in multiple preset operating time periods is calculated based on the failure rates of the electric energy meters provided by each supplier to each region in multiple preset operating time periods.

[0079] The failure rate of the electric energy meters installed at each installation time and provided by each supplier to each region in each preset operation period is calculated as follows:

[0080]

[0081] In the formula, is the failure rate of the electric energy meter installed at time x in the yth operating period provided by supplier F to region E, is the number of failures of the electric energy meters installed at time x and provided by supplier F to region E in the yth operating period, is the total number of electric energy meters installed at time x provided by supplier F to area E, m is the number of installation times of electric energy meters provided by supplier F to area E, and n is the number of operating time periods of electric energy meters provided by supplier F to area E;

[0082] The failure rate of the electric energy meters provided by each supplier to each region in each preset operating period is calculated as follows:

[0083]

[0084] In the formula, is the failure rate of the electric energy meters provided by supplier F to area E in the yth preset operating period;

[0085] The reliability of the electric energy meters provided by each supplier to each region in each preset operating period is calculated as follows:

[0086]

[0087] In the formula, The reliability of the electric energy meter provided by supplier F to area E in the yth operating period.

[0088] In step 2, since the reliability evaluation index of each preset operation period is an extremely large index, and the fault quantity and the failure rate of each preset operation period are extremely small indexes, the different directions of the data will make the comprehensive evaluation analysis confusing. In order to simplify the analysis, the corresponding evaluation index value under each evaluation index is processed positively, and the data is uniformly made as large as possible;

[0089] The corresponding evaluation value under each evaluation indicator is positively processed according to the following formula:

[0090]

[0091] In the formula, is the value of the ith evaluation index under the jth evaluation index after positive processing, x i，jis the i-th evaluation index value under the j-th evaluation index, f is the number of evaluation index values ​​under each evaluation index, and h is the number of evaluation indicators;

[0092] Each evaluation index value under each evaluation index after the positive processing is normalized according to the following formula:

[0093]

[0094] In the formula, Z i，j is the value of the i-th evaluation index under the j-th evaluation index after normalization and positive processing;

[0095] After the data is forward processed, the forward matrix Z is constructed by combining the reliability data of the electric energy meters provided by each supplier to each region in each preset operating period, as shown in the following formula:

[0096]

[0097] Before step 3, since each indicator has different effects on the comprehensive evaluation, the weight of the indicator should be selectively biased towards the indicator with greater effect. In order to be more objective and accurate, the present invention uses the entropy weight method to calculate the weight of the fault volume of the electric energy meter provided by each supplier to each region and the failure rate and reliability in each set operating period, and predetermines the indicator weight according to the difference in the degree of order of the information contained. The specific process is as follows:

[0098] The proportion of the i-th evaluation index value under the j-th index is calculated as follows:

[0099]

[0100] In the formula, A i，j The proportion of the i-th evaluation index value under the j-th evaluation index to the evaluation index;

[0101] The entropy value of the jth evaluation index is calculated as follows:

[0102]

[0103] In the formula, e j The entropy value of the jth evaluation index;

[0104] The information entropy redundancy of the jth evaluation index is calculated as follows:

[0105] d j =1-e j

[0106] Where, d j The information entropy redundancy of the jth evaluation index;

[0107] The weight of the jth evaluation index is calculated as follows:

[0108]

[0109] In the formula, w j is the weight of the jth evaluation index.

[0110] In step 3, the evaluation index values ​​in the evaluation index value matrix are screened out using the topsis evaluation method to find the best evaluation index value and the worst evaluation index value under each evaluation index, and the distance between each evaluation index value corresponding to the electric energy meter provided by each supplier to each region in each preset operating period and the corresponding best evaluation index and worst evaluation index value is calculated respectively;

[0111] First, the optimal solution and the worst solution are determined based on the maximum and minimum values ​​of all evaluation index values ​​contained under each evaluation index in the evaluation index value matrix;

[0112] The optimal solution consisting of the maximum value of all evaluation index values ​​contained under each evaluation index in the evaluation index value matrix is:

[0113]

[0114] In the formula, Z + The optimal solution is the maximum value of all evaluation index values ​​contained in each evaluation index in the evaluation index value matrix. is the maximum value of all evaluation index values ​​under the hth evaluation index in the evaluation index matrix;

[0115] The worst solution consisting of the minimum value of all evaluation index values ​​contained under each evaluation index in the evaluation index value matrix is:

[0116]

[0117] In the formula, Z - The optimal solution is the minimum value of all evaluation index values ​​contained in each evaluation index in the evaluation index value matrix. It is the minimum value of all evaluation index values ​​under the hth evaluation index in the evaluation index matrix.

[0118] Based on the calculated weight of each evaluation index, the optimal evaluation index value and the worst evaluation index value contained in the optimal solution and the worst solution, respectively calculate the amount of failures of the electric energy meters provided by each supplier to each region in all preset operating time periods, and the distance between each evaluation index value and the optimal evaluation index value and the worst evaluation index value under the reliability and failure rate evaluation index of each preset operating time period;

[0119] The distance between each evaluation index value and the corresponding optimal evaluation index value under all evaluation indicators is calculated as follows:

[0120]

[0121] In the formula, is the distance between each evaluation index value of the electric energy meter provided by supplier F to area E in the yth operating period and the corresponding optimal evaluation index value, is the optimal evaluation index value of the evaluation index value matrix under the jth evaluation index, is the evaluation index value of the electric energy meter provided by supplier F to area E in the yth operating period under the jth evaluation index, w j is the weight of the jth evaluation index, and h is the number of evaluation indicators;

[0122] The distance between each evaluation index value and the corresponding worst evaluation index value under all evaluation indicators is calculated as follows:

[0123]

[0124] In the formula, is the distance between each evaluation index value of the electric energy meter provided by supplier F to area E in the yth operating period and the corresponding worst evaluation index value, is the worst evaluation index value of the evaluation index value matrix under the jth evaluation index.

[0125] Input the distance between each evaluation index value corresponding to the electric energy meter provided by each supplier to each region in each preset operation period and the corresponding optimal evaluation index and the worst evaluation index value and the predetermined weight of each evaluation index into the comprehensive evaluation analysis calculation formula to obtain the score of the electric energy meter provided by each supplier to each region in each preset operation period;

[0126] Based on the calculated distances from the optimal and superior solutions, the comprehensive scores of the electric energy meters provided by each supplier to each region in each preset operating period are calculated as follows:

[0127]

[0128] In the formula, is the score corresponding to the electric energy meter provided by the supplier F to the area E in the yth operating period;

[0129] in, The larger the value, the better the evaluation object.

[0130] In this embodiment, since there are many schemes involved in the evaluation, after the evaluation, the value of each comprehensive evaluation score is small, which is not convenient for viewing. Therefore, all scores are converted by multiplying them by 10000, and finally sorted and compared.

[0131] The score corresponding to the electric energy meter provided by supplier F to area E in the yth operating period is converted as follows:

[0132]

[0133] In the formula, is the converted score corresponding to the electric energy meter provided by the supplier F to the area E in the yth operating period;

[0134] The scores of the electric energy meters provided by the suppliers to the respective regions in the preset operating time periods are used to represent the reliability of the electric energy meters provided by the suppliers to the respective regions in the preset operating time periods.

[0135] The present invention proposes a method for evaluating the reliability of electric energy meters based on comprehensive evaluation and analysis, which can calculate the failure rate of electric energy meters according to the number of failures in each operating year or a set period of time based on the number of electric energy meters installed in any period in the past, and can solve the problems that the evaluation index results are easily affected by extreme values ​​and the accuracy of the analysis is insufficient; at the same time, an overall evaluation and analysis of the reliability of the electric energy meters is performed, which can reflect the failure conditions of the installed electric energy meters in different operating years after installation, and reflect the reliability of the electric energy meters in various regions and suppliers in different operating periods as a whole.

[0136] Example 2

[0137] Based on the same inventive concept, the present invention also provides an electric energy meter reliability evaluation system based on comprehensive evaluation and analysis, such as Figure 2 As shown, including:

[0138] A calculation module, which calculates the failure rate and reliability of the electric energy meters provided by each supplier to each region in multiple preset operating time periods based on the number of electric energy meters installed at each installation time and the number of failures in each preset operating time period provided by each supplier to each region;

[0139] A processing module, used to process the failure rate and reliability by using a forward method and a normalization method, and to construct an evaluation index value matrix using the processed failure rate, reliability, and the number of failures of the electric energy meters installed at each installation time in each region provided by each supplier in all preset operating time periods as evaluation index values;

[0140] An evaluation module is used to determine the scores of the electric energy meters provided by each supplier to each region in each preset operating period according to the weights of each evaluation indicator predetermined based on the entropy weight method using the Topsis evaluation method for the evaluation index value matrix, and to determine the reliability of the electric energy meters provided by each supplier to each region in each preset operating period based on the scores.

[0141] In this embodiment, the installation time, in-operation data, and operating time period of historical fault data of the electric energy meters corresponding to each region, single-phase supplier, and three-phase supplier are obtained in advance, and the data is pre-processed.

[0142] For each single-phase electricity meter supplier, the data of electricity meters installed in each region where the number of electricity meters installed each year is less than 10,000 electricity meters are eliminated. For each three-phase electricity meter supplier, the data of electricity meters installed in each region where the number of electricity meters installed each year is less than 1,000 electricity meters are eliminated to ensure that the calculated failure rate and reliability are not affected by extreme data.

[0143] The calculation module includes: a failure rate calculation submodule and a reliability calculation submodule;

[0144] The failure rate calculation submodule is used to calculate the failure rate of the electric energy meters installed at each installation time provided by each supplier to each region in each preset operation period, and then use the average of the failure rates of the electric energy meters installed at each installation time provided by each supplier to each region in each preset operation period as the failure rate of the electric energy meters provided by each supplier to each region in multiple preset operation periods;

[0145] The failure rate of the electric energy meters installed at each installation time and provided by each supplier to each region in each preset operation period is calculated as follows:

[0146]

[0147] In the formula, is the failure rate of the electric energy meter installed at time x in the yth operating period provided by supplier F to region E, is the number of failures of the electric energy meters installed at time x and provided by supplier F to region E in the yth operating period, is the total number of electric energy meters installed at time x provided by supplier F to area E, m is the number of installation times of electric energy meters provided by supplier F to area E, and n is the number of operating time periods of electric energy meters provided by supplier F to area E;

[0148] The failure rate of the electric energy meters provided by each supplier to each region in each preset operating period is calculated as follows:

[0149]

[0150] In the formula, is the failure rate of the electric energy meters provided by supplier F to area E in the yth preset operating period;

[0151] The reliability calculation submodule is used to calculate the reliability of the electric energy meters provided by each supplier to each region in multiple preset operating time periods according to the failure rate of the electric energy meters provided by each supplier to each region in multiple preset operating time periods.

[0152] The reliability of the electric energy meters provided by each supplier to each region in each preset operating period is calculated as follows:

[0153]

[0154] In the formula, The reliability of the electric energy meter provided by supplier F to area E in the yth operating period.

[0155] In this embodiment, since the reliability evaluation index of each operating period is an extremely large index, and the fault quantity and the failure rate of each operating period are extremely small indexes, the different directions of the data will make the comprehensive evaluation analysis confusing, and the processing module is used to process and analyze the data;

[0156] The processing module is used to process the failure rate and reliability by using a forward method and a normalization method, and use the processed failure rate, reliability, and the number of failures of the electric energy meters installed at each installation time in each region provided by each supplier in all preset operating time periods as evaluation index values ​​to construct an evaluation index value matrix;

[0157] The corresponding evaluation value under each evaluation indicator is positively processed according to the following formula:

[0158]

[0159] In the formula, is the value of the ith evaluation index under the jth evaluation index after positive processing, x i，j is the i-th evaluation index value under the j-th evaluation index, f is the number of evaluation index values ​​under each evaluation index, and h is the number of evaluation indicators;

[0160] Each evaluation index value under each evaluation index after the positive processing is normalized according to the following formula:

[0161]

[0162] In the formula, Z i，j is the value of the i-th evaluation index under the j-th evaluation index after normalization and positive processing;

[0163] After the data is forward processed, the forward matrix Z is constructed by combining the reliability data of the electric energy meters provided by each supplier to each region in each preset operating period, as shown in the following formula:

[0164]

[0165] In this embodiment, since each indicator has a different effect on the comprehensive evaluation, the weight of the indicator should be selectively biased towards the indicator with a greater effect. In order to be more objective and accurate, the present invention uses the entropy weight method to calculate the weight of the fault volume of the electric energy meter provided by each supplier to each region and the failure rate and reliability in each set operating period, and predetermines the indicator weight according to the difference in the degree of order of the information contained. The specific process is as follows:

[0166] The proportion of the i-th evaluation index value under the j-th index is calculated as follows:

[0167]

[0168] In the formula, A i，j The proportion of the i-th evaluation index value under the j-th evaluation index to the evaluation index;

[0169] The entropy value of the jth evaluation index is calculated as follows:

[0170]

[0171] In the formula, e j The entropy value of the jth evaluation index;

[0172] The information entropy redundancy of the jth evaluation index is calculated as follows:

[0173] d j =1-e j

[0174] Where, d j The information entropy redundancy of the jth evaluation index;

[0175] The weight of the jth evaluation index is calculated as follows:

[0176]

[0177] In the formula, w j is the weight of the jth evaluation index.

[0178] The evaluation module includes: a distance calculation submodule, a score calculation submodule and a reliability determination submodule;

[0179] The distance calculation submodule is used to screen out the optimal evaluation index value and the worst evaluation index value under each evaluation index by using the evaluation index value in the evaluation index value matrix by the topsis evaluation method, and respectively calculate the distance between each evaluation index value corresponding to the electric energy meter provided by each supplier to each region in each preset operating time period and the corresponding optimal evaluation index and the worst evaluation index value;

[0180] Firstly, the optimal solution and the worst solution are determined based on the maximum value and the minimum value of all evaluation index values ​​contained under each evaluation index in the evaluation index value matrix;

[0181] The optimal solution consisting of the maximum value of all evaluation index values ​​contained under each evaluation index in the evaluation index value matrix is:

[0182]

[0183] In the formula, Z + The optimal solution is the maximum value of all evaluation index values ​​contained in each evaluation index in the evaluation index value matrix. It is the maximum value of all evaluation index values ​​under the hth evaluation index in the evaluation index matrix;

[0184] The worst solution consisting of the minimum value of all evaluation index values ​​contained under each evaluation index in the evaluation index value matrix is:

[0185]

[0186] In the formula, Z - It is the optimal solution consisting of the minimum value of all evaluation index values ​​contained in each evaluation index in the evaluation index value matrix. It is the minimum value of all evaluation index values ​​under the hth evaluation index in the evaluation index matrix.

[0187] Based on the calculated weight of each evaluation index, the optimal evaluation index value and the worst evaluation index value contained in the optimal solution and the worst solution, respectively calculate the amount of failures of the electric energy meters provided by each supplier to each region in all preset operating time periods, and the distance between each evaluation index value and the optimal evaluation index value and the worst evaluation index value under the reliability and failure rate evaluation index of each preset operating time period;

[0188] The distance between each evaluation index value and the corresponding optimal evaluation index value under all evaluation indicators is calculated as follows:

[0189]

[0190] In the formula, is the distance between each evaluation index value of the electric energy meter provided by supplier F to area E in the yth operating period and the corresponding optimal evaluation index value, is the optimal evaluation index value of the evaluation index value matrix under the jth evaluation index, is the evaluation index value of the electric energy meter provided by supplier F to area E in the yth operating period under the jth evaluation index, w j is the weight of the jth evaluation index, and h is the number of evaluation indicators;

[0191] The distance between each evaluation index value and the corresponding worst evaluation index value under all evaluation indicators is calculated as follows:

[0192]

[0193] In the formula, is the distance between each evaluation index value of the electric energy meter provided by supplier F to area E in the yth operating period and the corresponding worst evaluation index value, is the worst evaluation index value of the evaluation index value matrix under the jth evaluation index.

[0194] The score calculation submodule is used to input the distance between each evaluation index value corresponding to the electric energy meter provided by each supplier to each region in each preset operating period and the corresponding optimal evaluation index and the worst evaluation index value and the predetermined weight of each evaluation index into the comprehensive evaluation analysis calculation formula to obtain the score of the electric energy meter provided by each supplier to each region in each preset operating period;

[0195] Based on the calculated distances from the optimal and superior solutions, the comprehensive scores of the electric energy meters provided by each supplier to each region in each preset operating period are calculated as follows:

[0196]

[0197] In the formula, is the score corresponding to the electric energy meter provided by the supplier F to the area E in the yth operating period;

[0198] in, The larger the value, the better the evaluation object.

[0199] In this embodiment, since there are many schemes involved in the evaluation, after the evaluation, the value of each comprehensive evaluation score is small, which is not convenient for viewing. Therefore, all scores are converted by multiplying them by 10000, and finally sorted and compared.

[0200] The score corresponding to the electric energy meter provided by supplier F to area E in the yth operating period is converted as follows:

[0201]

[0202] In the formula, is the converted score corresponding to the electric energy meter provided by the supplier F to the area E in the yth operating period;

[0203] The reliability determination submodule is used to use the scores of the electric energy meters provided by each supplier to each region in each preset operating period to represent the reliability of the electric energy meters provided by each supplier to each region in each preset operating period.

[0204] Obviously, the described embodiments are only some embodiments of the present invention, but not all 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.

[0205] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0206] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0207] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0208] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0209] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are included in the scope of the claims of the present invention to be approved.

Claims

1. A reliability evaluation method for electric energy meters based on comprehensive evaluation and analysis, characterized in that: include: Calculate the failure rate and reliability of the electric energy meters provided by each supplier to each region in multiple preset operating time periods based on the number of electric energy meters installed at each installation time and the number of failures in each preset operating time period provided by each supplier to each region; The failure rate and reliability are processed by using a forward method and a normalization method, and an evaluation index value matrix is ​​constructed by using the processed failure rate, reliability, and the number of failures of the electric energy meters installed at each installation time in each region provided by each supplier in all preset operating time periods as evaluation index values; Using the Topsis evaluation method, the scores of the electric energy meters provided by each supplier to each region in each preset operating period are determined according to the weights of each evaluation indicator predetermined based on the entropy weight method for the evaluation index value matrix, and the reliability of the electric energy meters provided by each supplier to each region in each preset operating period is determined according to the scores; The calculation of the failure rate and reliability of the electric energy meters provided by each supplier to each region in multiple preset operating time periods based on the number of electric energy meters installed at each installation time and the number of failures in each preset operating time period provided by each supplier to each region includes: The failure rate of the electric energy meters installed at each installation time and provided by each supplier to each region in each preset operating period is calculated as follows: In the formula, is the failure rate of the electric energy meter installed at time x in the yth operating period provided by supplier F to region E, is the number of failures of the electric energy meters installed at time x and provided by supplier F to region E in the yth operating period, is the total number of electric energy meters installed at time x provided by supplier F to area E, m is the number of installation times of electric energy meters provided by supplier F to area E, and n is the number of operating time periods of electric energy meters provided by supplier F to area E; The failure rate of the electric energy meters provided by each supplier to each region in multiple preset operating periods is calculated as follows: In the formula, is the failure rate of the electric energy meters provided by supplier F to area E in the yth preset operating period; The reliability of the electric energy meters provided by each supplier to each region in multiple preset operating periods is calculated as follows: In the formula, The reliability of the electric energy meter provided by supplier F to area E in the yth operating period; The Topsis evaluation method is used to determine the scores of the electric energy meters provided by each supplier to each region in each preset operating period according to the weights of each evaluation indicator predetermined based on the entropy weight method for the evaluation index value matrix, and the reliability of the electric energy meters provided by each supplier to each region in each preset operating period is determined according to the scores, including: The evaluation index values ​​in the evaluation index value matrix are screened out using the topsis evaluation method to find the best evaluation index value and the worst evaluation index value under each evaluation index, and the distance between each evaluation index value corresponding to the electric energy meter provided by each supplier to each region in each preset operating period and the corresponding best evaluation index and worst evaluation index value is calculated respectively; Input the distance between each evaluation index value corresponding to the electric energy meter provided by each supplier to each region in each preset operation period and the corresponding optimal evaluation index and the worst evaluation index value and the predetermined weight of each evaluation index into the comprehensive evaluation analysis calculation formula to obtain the score of the electric energy meter provided by each supplier to each region in each preset operation period; The scores of the electric energy meters provided by the suppliers to the respective regions in the preset operating time periods are used to represent the reliability of the electric energy meters provided by the suppliers to the respective regions in the preset operating time periods.

2. The method according to claim 1, characterized in that: The comprehensive evaluation analysis calculation formula is as follows: In the formula, is the score corresponding to the electric energy meter provided by the supplier F to the area E in the yth operating period, is the distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding worst evaluation index value, is the distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding optimal evaluation index value; The distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding optimal evaluation index value is Calculate as follows: In the formula, is the optimal evaluation index value of the evaluation index value matrix under the jth evaluation index, is the evaluation index value of the electric energy meter provided by supplier F to area E in the yth operating period under the jth evaluation index, w j is the weight of the jth evaluation index, and h is the number of evaluation indicators; The distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding worst evaluation index value Calculate as follows: In the formula, is the worst evaluation index value of the evaluation index value matrix under the jth evaluation index.

3. The method according to claim 1, characterized in that: The determination of the weights of the evaluation indicators includes: Substituting the ratio of each evaluation index value under each evaluation index to all evaluation index values ​​under the corresponding evaluation index into the entropy value calculation formula in the entropy weight method, the entropy value of each evaluation index is calculated; The information entropy redundancy calculation formula is used to calculate the information entropy redundancy of each evaluation indicator according to the entropy value of each evaluation indicator; The ratio of the information entropy redundancy of each evaluation indicator to all information entropy redundancies is used as the indicator weight of each evaluation indicator.

4. The method according to claim 3, characterized in that: The weight of each evaluation index is calculated as follows: In the formula, w j is the weight of the jth evaluation index, d j is the information entropy redundancy of the j-th evaluation index; Among them, the information entropy redundancy of the j-th evaluation index d j , calculated as follows: d j =1-e j In the formula, e j is the entropy value of the jth evaluation index.

5. An electric energy meter reliability evaluation system based on comprehensive evaluation and analysis, characterized in that: include: A calculation module, which calculates the failure rate and reliability of the electric energy meters provided by each supplier to each region in multiple preset operating time periods based on the number of electric energy meters installed at each installation time and the number of failures in each preset operating time period provided by each supplier to each region; A processing module, used to process the failure rate and reliability by using a forward method and a normalization method, and to construct an evaluation index value matrix using the processed failure rate, reliability, and the number of failures of the electric energy meters installed at each installation time in each region provided by each supplier in all preset operating time periods as evaluation index values; An evaluation module, for determining the scores of the electric energy meters provided by each supplier to each region in each preset operating period according to the weights of each evaluation indicator predetermined based on the entropy weight method using the Topsis evaluation method for the evaluation indicator value matrix, and determining the reliability of the electric energy meters provided by each supplier to each region in each preset operating period according to the scores; The computing module comprises: The failure rate calculation submodule is used to calculate the failure rate of the electric energy meters installed at each installation time and provided by each supplier to each region in each preset operation period according to the following formula: In the formula, is the failure rate of the electric energy meter installed at time x in the yth operating period provided by supplier F to region E, is the number of failures of the electric energy meters installed at time x and provided by supplier F to region E in the yth operating period, is the total number of electric energy meters installed at time x provided by supplier F to area E, m is the number of installation times of electric energy meters provided by supplier F to area E, and n is the number of operating time periods of electric energy meters provided by supplier F to area E; The failure rate of the electric energy meters provided by each supplier to each region in multiple preset operating periods is calculated as follows: In the formula, is the failure rate of the electric energy meters provided by supplier F to area E in the yth preset operating period; The reliability calculation submodule is used to calculate the reliability of the electric energy meters provided by each supplier to each region in multiple preset operating periods according to the following formula: In the formula, The reliability of the electric energy meter provided by supplier F to area E in the yth operating period; The evaluation module comprises: A distance calculation submodule is used to screen out the optimal evaluation index value and the worst evaluation index value under each evaluation index by using the evaluation index value in the evaluation index value matrix by the topsis evaluation method, and respectively calculate the distance between each evaluation index value corresponding to the electric energy meter provided by each supplier to each region in each preset operating period and the corresponding optimal evaluation index and the worst evaluation index value; A score calculation submodule, for inputting the distance between each evaluation index value corresponding to the electric energy meter provided by each supplier to each region in each preset operation period and the corresponding optimal evaluation index and the worst evaluation index value and the predetermined weight of each evaluation index into a comprehensive evaluation analysis calculation formula, to obtain the score of the electric energy meter provided by each supplier to each region in each preset operation period; The reliability determination submodule is used to use the scores of the electric energy meters provided by the suppliers to the respective regions in the preset operating time periods to represent the reliability of the electric energy meters provided by the suppliers to the respective regions in the preset operating time periods.

6. The system according to claim 5, characterized in that: The comprehensive evaluation analysis calculation formula is as follows: In the formula, is the score corresponding to the electric energy meter provided by the supplier F to the area E in the yth operating period, is the distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding worst evaluation index value, is the distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding optimal evaluation index value; The distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding optimal evaluation index value is Calculate as follows: In the formula, is the optimal evaluation index value of the evaluation index value matrix under the jth evaluation index, is the evaluation index value of the electric energy meter provided by supplier F to area E in the yth operating period under the jth evaluation index, w j is the weight of the jth evaluation index, and h is the number of evaluation indicators; The distance between each evaluation index value of the electric energy meter provided by the supplier F to the area E in the yth operating period and the corresponding worst evaluation index value Calculate as follows: In the formula, is the worst evaluation index value of the evaluation index value matrix under the jth evaluation index.

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