CN116739417A - Gateway electric energy meter state evaluation method and device, storage medium and computer equipment - Google Patents

Gateway electric energy meter state evaluation method and device, storage medium and computer equipment Download PDF

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CN116739417A
CN116739417A CN202310591745.9A CN202310591745A CN116739417A CN 116739417 A CN116739417 A CN 116739417A CN 202310591745 A CN202310591745 A CN 202310591745A CN 116739417 A CN116739417 A CN 116739417A
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energy meter
index data
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洪元瑞
吴敏
袁志文
刘福斌
李晓刚
杨立兵
陈俊杰
冯茗俊
刘裕铖
张金丽
周永真
王丹
张路
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Beiming Software Co ltd
East China Branch Of State Grid Corp ltd
East China Power Test and Research Institute Co Ltd
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Beiming Software Co ltd
East China Branch Of State Grid Corp ltd
East China Power Test and Research Institute Co Ltd
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Abstract

The application discloses a gateway electric energy meter state evaluation method and device, a storage medium and computer equipment, wherein the method comprises the following steps: acquiring index data of preset evaluation dimensions of evaluation indexes corresponding to each gateway electric energy meter to be evaluated in a bus balance management system; calculating independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method, and calculating the sub-item score of each index data according to the index data and the good-bad solution distance method; and obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of each evaluation index corresponding to each gateway electric energy meter to be evaluated and the independent information weight of each evaluation index, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the state comprehensive score. The weight of each evaluation index is obtained by combining the self information and the independence degree of the measurement index data, and the interpretation of the evaluation is improved while the weight objectivity is achieved.

Description

Gateway electric energy meter state evaluation method and device, storage medium and computer equipment
Technical Field
The application relates to the technical field of power equipment state evaluation, in particular to a gateway electric energy meter state evaluation method and device, a storage medium and computer equipment.
Background
The multi-dimensional evaluation analysis of the bus balance system is constructed, and the method has important significance for evaluating the equipment state, particularly the real state of the electric energy meter, and improving the acquisition capacity of the terminal. The method is characterized in that a bus balance system state evaluation system is constructed and perfected, and the key points are the evaluation of metering points, electric energy meters and transformers in buses. The method is characterized in that the real state of the electric energy meter is accurately mastered aiming at the electric energy meter, the calculation accuracy of the running error of the electric energy meter is improved, and the trend evolution of the error of the electric energy meter is described; aiming at the terminal, comprehensive evaluation is carried out on the terminal acquisition capacity, the weak point of the acquisition capacity is determined, and the terminal acquisition capacity is improved.
In the prior art, the health status evaluation of power plant equipment is performed by comprehensively evaluating the weighting of each index. The conventional algorithms for index weighting include an entropy method, a discrete coefficient method, an expert scoring method and a neural network algorithm. The weighting method used by the entropy method and the discrete coefficient method in the algorithm is single, only provides statistical index data fluctuation information, and ignores the independence degree of the data information; expert scoring relies on the experience of external experts and may be somewhat subjective; although the neural network algorithm avoids the subjectivity problem, the model has higher requirements on data and has poor interpretability.
Disclosure of Invention
In view of the above, the application provides a method and a device for evaluating the state of a gateway electric energy meter, a storage medium and computer equipment, which combine the information of index data and the independent degree of the index data to obtain the weight of each evaluation index, and improve the interpretation of the evaluation while having the objectivity of the weight.
According to one aspect of the present application, there is provided a gateway electric energy meter state evaluation method, the method comprising:
acquiring index data of preset evaluation dimensions of evaluation indexes corresponding to each gateway electric energy meter to be evaluated in a bus balance management system;
calculating independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method, and calculating the sub-item score of each index data according to the index data and the good-bad solution distance method;
and obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of each evaluation index corresponding to each gateway electric energy meter to be evaluated and the independent information weight of each evaluation index, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the state comprehensive score.
Optionally, the calculating the independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method includes:
Selecting any one evaluation index, and calculating an index discrete coefficient of the selected evaluation index according to all index data corresponding to the selected evaluation index;
sequentially carrying out regression analysis by taking each index data in all index data corresponding to the selected evaluation index as a dependent variable and other index data as independent variables to obtain a fitting goodness, and obtaining independent information ratio according to the fitting goodness;
and obtaining the independent information weight corresponding to the selected evaluation index according to the index discrete coefficient and the independent information ratio.
Optionally, the obtaining the independent information weight corresponding to the selected evaluation index according to the index discrete coefficient and the independent information ratio includes:
respectively normalizing the index discrete coefficient and the independent information ratio, and fusing the normalized index discrete coefficient and the independent information ratio according to a multiplication model to obtain the pure information quantity of the selected evaluation index;
and calculating the percentage of the pure information quantity of the selected evaluation index in the sum of the pure information quantities corresponding to each evaluation index, and obtaining the independent information weight of the selected evaluation index.
Optionally, after any one of the evaluation indexes is selected, the method further includes:
If the index data of the selected evaluation index at each gateway electric energy meter to be evaluated is consistent, the independent information weight of the selected evaluation index is not calculated, and the selected evaluation index is determined to be a discarding amount evaluation index;
calculating the item score of the index data of each non-abandoned amount evaluation index according to the index data of the non-abandoned amount evaluation index and the good-bad solution distance method;
and obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of the non-abandoned amount evaluation indexes corresponding to each gateway electric energy meter to be evaluated and the independent information weights of each non-abandoned amount evaluation index.
Optionally, the calculating the score of each index data according to the index data and the better-worse solution distance method includes:
constructing an initial matrix according to all index data, determining an index type corresponding to each index data in the initial matrix, and converting all non-huge indexes in the initial matrix into huge indexes to obtain a forward matrix, wherein the index types comprise the huge indexes, the tiny indexes, the intermediate indexes and interval indexes;
and normalizing the forward matrix to obtain a normalized matrix, and obtaining the score of each index data according to the normalized matrix.
Optionally, the normalization matrix includes normalization index data; the obtaining the item score of each index data according to the standardized matrix comprises the following steps:
selecting any one evaluation index, and determining the worst solution and the optimal solution corresponding to the selected evaluation index according to all standardized index data corresponding to the selected evaluation index;
sequentially calculating the worst solution distance from each piece of standardized index data to the worst solution and the optimal solution distance from each piece of standardized index data to the optimal solution in all pieces of standardized index data corresponding to the selected evaluation indexes;
and calculating the optimal solution occupation ratio of each standardized index data according to the worst solution distance and the optimal solution distance, and obtaining the sub-item score of the index data corresponding to each standardized index data.
Optionally, the obtaining the comprehensive status score of each gateway electric energy meter to be evaluated according to the item scores of the index data of the corresponding evaluation indexes of each gateway electric energy meter to be evaluated and the independent information weights of each evaluation index includes:
selecting any gateway electric energy meter to be evaluated, and determining the sub-item scores of the index data of each evaluation index corresponding to the gateway electric energy meter to be evaluated and the independent information weight of the evaluation index corresponding to each sub-item score;
And summing the product of the independent information weights of the evaluation indexes corresponding to each item score to obtain the comprehensive state score of the selected gateway electric energy meter to be evaluated.
According to another aspect of the present application, there is provided a gateway electric energy meter state evaluation device, the device comprising:
the data acquisition module is used for acquiring index data of preset evaluation dimensions of evaluation indexes corresponding to the gateway electric energy meters to be evaluated in the bus balance management system;
the data calculation module is used for calculating the independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method and calculating the sub-item score of each index data according to the index data and the good-bad solution distance method;
the state evaluation module is used for obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of each evaluation index corresponding to each gateway electric energy meter to be evaluated and the independent information weight of each evaluation index, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the state comprehensive score.
Optionally, the data calculation module is further configured to:
selecting any one evaluation index, and calculating an index discrete coefficient of the selected evaluation index according to all index data corresponding to the selected evaluation index;
Sequentially carrying out regression analysis by taking each index data in all index data corresponding to the selected evaluation index as a dependent variable and other index data as independent variables to obtain a fitting goodness, and obtaining independent information ratio according to the fitting goodness;
and obtaining the independent information weight corresponding to the selected evaluation index according to the index discrete coefficient and the independent information ratio.
Optionally, the data calculation module is further configured to:
respectively normalizing the index discrete coefficient and the independent information ratio, and fusing the normalized index discrete coefficient and the independent information ratio according to a multiplication model to obtain the pure information quantity of the selected evaluation index;
and calculating the percentage of the pure information quantity of the selected evaluation index in the sum of the pure information quantities corresponding to each evaluation index, and obtaining the independent information weight of the selected evaluation index.
Optionally, the data calculation module is further configured to:
if the index data of the selected evaluation index at each gateway electric energy meter to be evaluated is consistent, the independent information weight of the selected evaluation index is not calculated, and the selected evaluation index is determined to be a discarding amount evaluation index;
calculating the item score of the index data of each non-abandoned amount evaluation index according to the index data of the non-abandoned amount evaluation index and the good-bad solution distance method;
And obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of the non-abandoned amount evaluation indexes corresponding to each gateway electric energy meter to be evaluated and the independent information weights of each non-abandoned amount evaluation index.
Optionally, the data calculation module is further configured to:
constructing an initial matrix according to all index data, determining an index type corresponding to each index data in the initial matrix, and converting all non-huge indexes in the initial matrix into huge indexes to obtain a forward matrix, wherein the index types comprise the huge indexes, the tiny indexes, the intermediate indexes and interval indexes;
and normalizing the forward matrix to obtain a normalized matrix, and obtaining the score of each index data according to the normalized matrix.
Optionally, the normalization matrix includes normalization index data; the data calculation module is further configured to:
selecting any one evaluation index, and determining the worst solution and the optimal solution corresponding to the selected evaluation index according to all standardized index data corresponding to the selected evaluation index;
sequentially calculating the worst solution distance from each piece of standardized index data to the worst solution and the optimal solution distance from each piece of standardized index data to the optimal solution in all pieces of standardized index data corresponding to the selected evaluation indexes;
And calculating the optimal solution occupation ratio of each standardized index data according to the worst solution distance and the optimal solution distance, and obtaining the sub-item score of the index data corresponding to each standardized index data.
Optionally, the state evaluation module is further configured to:
selecting any gateway electric energy meter to be evaluated, and determining the sub-item scores of the index data of each evaluation index corresponding to the gateway electric energy meter to be evaluated and the independent information weight of the evaluation index corresponding to each sub-item score;
and summing the product of the independent information weights of the evaluation indexes corresponding to each item score to obtain the comprehensive state score of the selected gateway electric energy meter to be evaluated.
According to still another aspect of the present application, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements the above-described gateway electric energy meter state evaluation method.
According to still another aspect of the present application, there is provided a computer device including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, the processor implementing the above-mentioned gateway electric energy meter state evaluation method when executing the program.
By means of the technical scheme, the state evaluation method and device for the gateway electric energy meter, the storage medium and the computer equipment provided by the application are used for acquiring index data of preset evaluation dimensions of evaluation indexes corresponding to the gateway electric energy meters to be evaluated in the bus balance management system, calculating independent information weight of each evaluation index according to the index data and an independent information data fluctuation weighting method, calculating sub-item scores of each index data according to the index data and a superior-inferior solution distance method, and obtaining comprehensive state scores of the gateway electric energy meters to be evaluated according to the sub-item scores of the index data of the evaluation indexes corresponding to the gateway electric energy meters to be evaluated and the independent information weight of each evaluation index, so that the state of the gateway electric energy meter to be evaluated is evaluated according to the comprehensive state scores. The weight of each evaluation index is obtained by combining and measuring the information of the index data and the independent degree of the index data, so that the evaluation interpretation is improved while the weight objectivity is achieved.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
fig. 1 shows a flow chart of a method for evaluating the state of a gateway electric energy meter according to an embodiment of the present application;
fig. 2 is a schematic flow chart of another method for evaluating the state of a gateway electric energy meter according to an embodiment of the present application;
fig. 3 is a schematic flow chart of another method for evaluating the state of a gateway electric energy meter according to an embodiment of the present application;
fig. 4 is a schematic flow chart of another method for evaluating the state of a gateway electric energy meter according to an embodiment of the present application;
fig. 5 shows a schematic diagram of a state evaluation method of a gateway electric energy meter according to an embodiment of the present application;
fig. 6 shows a schematic structural diagram of a state evaluation device for a gateway electric energy meter according to an embodiment of the present application.
Detailed Description
The application will be described in detail hereinafter with reference to the drawings in conjunction with embodiments. It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other.
In this embodiment, a method for evaluating a state of a gateway electric energy meter is provided, as shown in fig. 1, and the method includes:
step 101, acquiring index data of preset evaluation dimensions of evaluation indexes corresponding to each gateway electric energy meter to be evaluated in a bus balance management system.
In the above embodiment of the present application, index data of preset evaluation dimensions of each evaluation index corresponding to each gateway electric energy meter to be evaluated in the bus balance management system is obtained. Specifically, the evaluation index may include: the daily freezing acquisition success rate and the daily freezing acquisition integrity rate are used for evaluating the daily freezing data acquisition state of the gateway electric energy meter; the telemetry acquisition success rate and the telemetry acquisition integrity rate are used for evaluating telemetry data acquisition states of the gateway electric energy meter; the interval acquisition success rate and the interval acquisition integrity rate are used for evaluating the interval data acquisition state of the gateway electric energy meter; the accumulated acquisition success rate and the accumulated acquisition integrity rate are used for evaluating the accumulated data acquisition state of the gateway electric energy meter; the clock anomaly times, the counter-running times and the gateway flying times of the electric energy meter and the number of times of the gateway flying times are used for evaluating whether the metering of the gateway electric energy meter is abnormal or not; the current three-phase imbalance and the voltage three-phase imbalance are used for evaluating the abnormal operation of the gateway electric energy meter; and the equipment operation time (day) is used for evaluating the service life of the gateway electric energy meter. The data acquisition integrity rate and success rate of the gateway electric energy meter need to be comprehensively researched and judged by combining invalid data and data missing, and the gateway electric energy meter is free of missing data=missing data+invalid data.
The preset evaluation dimension includes a daily dimension or Zhou Weidu, and the acquired index data corresponds to daily dimension data or circumferential dimension data, for example: the daily freezing acquisition success rate and the equipment operation time (day) are daily dimension data, the weekly freezing acquisition success rate and the equipment operation time (week) are Zhou Weidu data, and therefore the evaluation dimension of the data can be adjusted at any time according to different application scenes.
In a specific embodiment, the obtained index data of the preset evaluation dimension of each evaluation index corresponding to the gateway electric energy meter 1 in the bus balance management system is, for example: "daily freezing acquisition success rate 100%, daily freezing acquisition integrity rate 98%, telemetry acquisition success rate 97%, telemetry acquisition integrity rate 100%, interval acquisition success rate 90%, interval acquisition integrity rate 100%, accumulated acquisition success rate 100%, accumulated acquisition integrity rate 87%, clock anomaly number of electric energy meter 2, electric energy meter backward travel number 0, gate meter fly away and overflow number 1, current three-phase imbalance 0, voltage three-phase imbalance 1, equipment operation time (day) 169"; index data of preset evaluation dimensions of each evaluation index corresponding to the gateway electric energy meter 2 are as follows: 90% of daily freezing acquisition success rate, 100% of daily freezing acquisition integrity rate, 90% of telemetry acquisition success rate, 80% of telemetry acquisition integrity rate, 100% of interval acquisition integrity rate, 87% of accumulated acquisition success rate, 95% of accumulated acquisition integrity rate, 4 clock anomaly times of an electric energy meter, 1 backward running times of the electric energy meter, 0 times of gate meter flying away and over running, 1 current three-phase imbalance, 1 voltage three-phase imbalance and 245 of equipment operation time (day).
And 102, calculating the independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method, and calculating the item score of each index data according to the index data and the good-bad solution distance method.
And then, calculating the independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method, and calculating the sub-term score of each index data according to the index data and the good-bad solution distance method, so that the state comprehensive score of each gateway electric energy meter to be evaluated can be calculated according to the independent information weight of each evaluation index and the sub-term score of each index data.
And step 103, obtaining a comprehensive state score of each gateway electric energy meter to be evaluated according to the item scores of the index data of the corresponding evaluation indexes of each gateway electric energy meter to be evaluated and the independent information weights of the evaluation indexes, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the comprehensive state score.
And obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of each evaluation index corresponding to each gateway electric energy meter to be evaluated and the independent information weight of each evaluation index, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the state comprehensive score. By combining the independent information data fluctuation weighting method with the good and bad solution distance method, the combination measurement of the data self information and the data independent degree is realized, the weight of each index is further obtained, and the evaluation interpretability is improved while the weight objectivity is achieved.
By applying the technical scheme of the embodiment, index data of preset evaluation dimensions of the evaluation indexes corresponding to each gateway electric energy meter to be evaluated in the bus balance management system are obtained; calculating independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method, and calculating the sub-item score of each index data according to the index data and the good-bad solution distance method; and obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of each evaluation index corresponding to each gateway electric energy meter to be evaluated and the independent information weight of each evaluation index, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the state comprehensive score. By combining the independent information data fluctuation weighting method with the good and bad solution distance method, the combination measurement of the data self information and the data independent degree is realized, the weight of each index is further obtained, and the evaluation interpretability is improved while the weight objectivity is achieved.
Further, as a refinement and extension of the specific implementation manner of the foregoing embodiment, in order to fully describe the specific implementation process of this embodiment, another method for evaluating the state of a gateway electric energy meter is provided, as shown in fig. 2, where the method includes:
Step 201, obtaining index data of preset evaluation dimensions of evaluation indexes corresponding to each gateway electric energy meter to be evaluated in a bus balance management system.
In the above embodiment of the present application, index data of preset evaluation dimensions of each evaluation index corresponding to each gateway electric energy meter to be evaluated in the bus balance management system is obtained, and the evaluation indexes include daily freezing acquisition success rate, daily freezing acquisition complete rate, telemetry acquisition success rate, telemetry acquisition complete rate and the like.
Step 202, selecting any one evaluation index, and calculating an index discrete coefficient of the selected evaluation index according to all index data corresponding to the selected evaluation index.
Then, any one evaluation index is selected, for example, an evaluation index of 'daily freezing acquisition success rate' is selected, and the acquisition of the evaluation index of 'daily freezing acquisition success rate' in the bus balance management system specifically comprises the following steps of: the method comprises the steps of calculating the ratio of standard deviation of all index data corresponding to a selected evaluation index to an arithmetic mean value to obtain an index discrete coefficient, namely calculating the ratio of standard deviation of all index data (' 100%, 97%, 88%) corresponding to the evaluation index ' daily freezing acquisition success rate ' to the arithmetic mean value to obtain the index discrete coefficient of the evaluation index ' daily freezing acquisition success rate '.
Specifically, if the evaluation index is assumed to be X j Evaluation index X j The standard deviation of all corresponding index data is delta j Evaluation index X j The arithmetic average value of all corresponding index data isWhere j represents the first and second..nth evaluation index, j=1, 2., n,
then index discrete coefficient V j The calculation formula of (2) is
Optionally, after any one of the evaluation indexes is selected, the method further includes:
step 202-1, if the index data of the selected evaluation index in each gateway electric energy meter to be evaluated is consistent, the independent information weight of the selected evaluation index is not calculated, and the selected evaluation index is determined as a discarding amount evaluation index.
Step 202-2, calculating the item scores of the index data of each non-abandoned amount evaluation index according to the index data of the non-abandoned amount evaluation index and the good-bad solution distance method.
And 203-3, obtaining the comprehensive state score of each gateway electric energy meter to be evaluated according to the item scores of the index data of the non-abandoned amount evaluation indexes corresponding to each gateway electric energy meter to be evaluated and the independent information weight of each non-abandoned amount evaluation index.
In the above embodiment of the present application, after the selection of the evaluation index is determined, in order to ensure the objectivity of the evaluation, the index weight is analyzed by adopting the independent information data fluctuation weighting method. Considering that the acquisition success rate and the integrity rate of all the gateway electric energy meters are 100% under the condition of normal operation of index data or the condition that a certain abnormality does not occur in all the gateway electric energy meters in the same day, the influence of the evaluation index on the whole health evaluation is small, the index data in the same day is required to be screened, and weight distribution analysis and comprehensive evaluation analysis are mainly carried out on the evaluation index with low occurrence data consistency.
For example, if the daily freezing acquisition success rate of the current day evaluation index is consistent in the bus balance management system, for example, the index data of each of the to-be-evaluated gate electric energy meters is 100%, then the evaluation index is not required to be scored, specifically, if the selected evaluation index is consistent in the index data of each of the to-be-evaluated gate electric energy meters, the independent information weight of the selected evaluation index is not calculated, the selected evaluation index is determined as the abandoned amount evaluation index, the sub-item score of the index data of each of the non-abandoned amount evaluation indexes is calculated according to the index data of the non-abandoned amount evaluation index and the superior-inferior solution distance method, and the state comprehensive score of each of the non-abandoned amount evaluation indexes is obtained according to the sub-item score of the index data of the non-abandoned amount evaluation index corresponding to each of the to-be-evaluated gate electric energy meters and the independent information weight of each of the non-abandoned amount evaluation index, so that the calculation of the evaluation index which is not required to be evaluated can be abandoned, thereby improving the calculation efficiency of the evaluation process.
And 203, carrying out regression analysis by taking each index data in all index data corresponding to the selected evaluation index as a dependent variable and other index data as independent variables to obtain a fitting goodness, and obtaining independent information ratio according to the fitting goodness.
Then, regression analysis is carried out by taking each index data in all index data corresponding to the selected evaluation index as a dependent variable and other index data as independent variables in turn to obtain a fitting goodness, and an independent information ratio is obtained according to the fitting goodness, specifically, if the fitting goodness is assumed to be R j The independent information ratio is D j ，
Then the independent information ratio is D j The calculation formula of (C) is D j ＝1-R j 。
And 204, respectively normalizing the index discrete coefficient and the independent information ratio, and fusing the normalized index discrete coefficient and the normalized independent information ratio according to a multiplication model to obtain the pure information quantity of the selected evaluation index.
Then, the index discrete coefficients V are normalized respectively j The independent information ratio D j Fusing the normalized index discrete coefficients V according to a multiplication model j The independent information ratio D j Obtaining the pure information quantity I of the selected evaluation index j Normalized index discrete coefficient V j Is V' j Normalized independent information ratio D j Is D' j ，V' j 、D' j Pure information quantity I j The calculation formulas of (a) are respectively as follows:
and 205, calculating the percentage of the pure information quantity of the selected evaluation index in the sum of the pure information quantities corresponding to each evaluation index, and obtaining the independent information weight of the selected evaluation index.
Then, calculating the percentage of the pure information quantity of the selected evaluation index in the sum of the pure information quantities corresponding to each evaluation index, and obtaining the independent information weight of the selected evaluation index, namely calculating the percentage of the pure information quantity of each evaluation index, and obtaining the independent information weight of each evaluation index.
And step 206, calculating the score of each index data according to the index data and the good-bad solution distance method.
Step 207, obtaining a comprehensive state score of each gateway electric energy meter to be evaluated according to the item scores of the index data of the corresponding evaluation indexes of each gateway electric energy meter to be evaluated and the independent information weights of the evaluation indexes, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the comprehensive state score.
And then, calculating the score of each index data according to the index data and the good-bad solution distance method. And obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of each evaluation index corresponding to each gateway electric energy meter to be evaluated and the independent information weight of each evaluation index, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the state comprehensive score. The independent information data fluctuation weighting method combines the information weighting methods such as a discrete coefficient method equidistant weighting method, a linear weighting method and the like, can evaluate the independent information provided by the data and the degree of change of the data, and can fully mine the characteristics of the existing index data.
By applying the technical scheme of the embodiment, index data of preset evaluation dimensions of the evaluation indexes corresponding to each gateway electric energy meter to be evaluated in the bus balance management system are obtained. Any one evaluation index is selected, and the index discrete coefficient of the selected evaluation index is calculated according to all index data corresponding to the selected evaluation index. And carrying out regression analysis by taking each index data in all index data corresponding to the selected evaluation index as a dependent variable and other index data as independent variables to obtain a fitting goodness, and obtaining independent information ratio according to the fitting goodness. And fusing the standardized index discrete coefficients and the independent information ratio according to a multiplication model to obtain the pure information quantity of the selected evaluation index. And calculating the percentage of the pure information quantity of the selected evaluation index in the sum of the pure information quantities corresponding to each evaluation index, and obtaining the independent information weight of the selected evaluation index. And calculating the score of each index data according to the index data and the good-bad solution distance method. And obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of each evaluation index corresponding to each gateway electric energy meter to be evaluated and the independent information weight of each evaluation index, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the state comprehensive score. The state evaluation is carried out on the gateway electric energy meter equipment of the bus balance system by adopting an independent information data fluctuation weighting method and a superior-inferior solution distance method, the information data weighting weight of an evaluation index and independent information of the index are fused by adopting a multiplication model, the available data are fully mined, the current day operation state of the equipment is comprehensively evaluated by acquiring more objective and reasonable weight, the health degree state and the past detection data are combined, the health degree and the life cycle of the equipment are predicted, and a user can be assisted to judge potential equipment deviation and faults in advance, so that the bus balance management system has the capacity of treating diseases.
Further, as a refinement and extension of the specific implementation manner of the foregoing embodiment, in order to fully describe the specific implementation process of the embodiment, another method for evaluating the state of a gateway electric energy meter is provided, as shown in fig. 3, where the method includes:
step 301, obtaining index data of preset evaluation dimensions of evaluation indexes corresponding to each gateway electric energy meter to be evaluated in a bus balance management system.
In the above embodiment of the present application, index data of preset evaluation dimensions of evaluation indexes corresponding to each gateway electric energy meter to be evaluated in the bus balance management system is obtained, so that each gateway electric energy meter to be evaluated is evaluated according to the index data.
And step 302, calculating the independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method.
And then, calculating the independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method, and combining the data self information and the data independent degree to obtain the independent information weight of each evaluation index, thereby improving the evaluation interpretability while having weight objectivity.
Step 303, constructing an initial matrix according to all index data, determining an index type corresponding to each index data in the initial matrix, and converting all non-huge indexes in the initial matrix into huge indexes to obtain a forward matrix, wherein the index types comprise the huge indexes, the tiny indexes, the intermediate indexes and the interval indexes.
And then, constructing an initial matrix according to all index data, determining an index type corresponding to each index data in the initial matrix, and converting all non-huge indexes in the initial matrix into huge indexes to obtain a forward matrix, wherein the index types comprise the huge indexes, the tiny indexes, the intermediate indexes and the interval indexes.
Specifically, for example, the bus balance management system includes m gateway electric energy meters, each gateway electric energy meter sets n evaluation indexes, m gateway electric energy meters are used as rows, n evaluation indexes are used as columns, and an initial matrix is constructed according to all index data, and is as follows:
wherein a is mn The n-th evaluation index of the m-th gateway electric energy meter is expressed, and more specifically, i is expressed as the first and second aspects.
Then, determining the index type corresponding to each index data in the initial matrix A, wherein the index type comprises a maximum index, a minimum index, an intermediate index and a section index. The larger the index value, i.e., the benefit index, the better, i.e., the index of forward direction, for example: the evaluation indexes comprise a daily freezing acquisition success rate, a daily freezing acquisition integrity rate, an interval acquisition integrity rate and the like; the smaller the index value, the better, for example: the evaluation indexes comprise the clock abnormality times of the electric energy meter, the reverse running times of the electric energy meter, the equipment operation time (day) of the evaluation indexes and the like; the intermediate index, i.e., the index value is better the closer the index value is to the preset value; the interval index, i.e. the index value is best within the range of the preset interval, and the value in the interval has no difference in the value.
In particular, if it is assumed that the index to be converted is x i The index after transformation is
The calculation formula for converting the minimum index into the maximum index is as follows:
or->
The calculation formula for converting the intermediate index into the very large index is as follows:
wherein the denominator is the value that deviates furthest from the best value, in this way converting the intermediate index into a very large index;
the calculation formula for converting the interval index into the extremely large index is as follows:
where m=max { a-min (X), max (X) -b }, a is the upper bound and b is the lower bound.
Step 304, normalizing the forward matrix to obtain a normalized matrix, selecting any one of the evaluation indexes, and determining the worst solution and the best solution corresponding to the selected evaluation index according to all the normalized index data corresponding to the selected evaluation index, wherein the normalized matrix comprises the normalized index data.
Then, since the dimensions of the respective indices may be different, it is necessary to perform normalization processing (normalization processing) on the original data, that is, normalize the forward matrix, to obtain a normalized matrix including normalized index data. Specifically, the obtained standardized matrix a' is:
wherein, likewise, a mn And the n-th evaluation index of the electric energy meter at the m-th gateway is shown. More specifically, the first and second aspects are denoted by i, the m-th aspect electric energy meter, i=1, 2, m, and the first and second aspects are denoted by j, the n-th evaluation index, j=1, 2, n.
Then, any one evaluation index is selected, and the worst solution and the optimal solution corresponding to the selected evaluation index are determined according to all standardized index data corresponding to the selected evaluation index.
Specifically, a method of a specific size can be adopted for all the standardized index data corresponding to the selected evaluation index, so as to obtain the worst solution and the best solution corresponding to the selected evaluation index. For example: the selected evaluation index is 'daily freezing acquisition success rate', the index data corresponding to the evaluation index 'daily freezing acquisition success rate' is 'gateway electric energy meter 1', the daily freezing acquisition success rate is 100 percent ',' gateway electric energy meter 2 ', the daily freezing acquisition success rate is 97 percent', 'gateway electric energy meter 3 and the daily freezing acquisition success rate is 88 percent', and the worst solution and the optimal solution corresponding to the evaluation index 'daily freezing acquisition success rate' are 88 percent and 100 percent respectively according to the information.
In step 305, the distance from each standardized index data to the worst solution and the optimal solution distance from each standardized index data to the optimal solution are sequentially calculated in all standardized index data corresponding to the selected evaluation index.
Then, each standard is calculated in turn in all the standardized index data corresponding to the selected evaluation indexThe index data is normalized to the worst solution distance of the worst solution and to the optimal solution distance of the optimal solution. Specifically, assume the worst solution is Optimal solution of->
The worst solution distance to the worst solution isThe calculation formula is +.>
The optimal solution distance to the optimal solution isThe calculation formula is +.>
And 306, calculating the optimal solution duty ratio of each standardized index according to the worst solution distance and the optimal solution distance, and obtaining the item scores of the index data corresponding to each standardized index data.
Then, calculating the ratio of the worst solution distance corresponding to each standardized index data to the sum of the worst solution distance and the best solution distance, namely
Wherein, the liquid crystal display device comprises a liquid crystal display device,for the evaluation index a ij To worst solution->Distance of->For the evaluation index a ij To optimal solution->When the index is far from the worst solution distance and is close to the best solution distance, the index is close to the best solution distance, and the score is high.
Step 307, obtaining a comprehensive state score of each gateway electric energy meter to be evaluated according to the item scores of the index data of each evaluation index corresponding to each gateway electric energy meter to be evaluated and the independent information weights of each evaluation index, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the comprehensive state score.
And obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of each evaluation index corresponding to each gateway electric energy meter to be evaluated and the independent information weight of each evaluation index, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the state comprehensive score. The forward matrix is obtained by unifying index types (forward processing) of the original data matrix, the effect of each index dimension is eliminated by performing standardized processing on the forward matrix, then index values of objects in each dimension are calculated, the index values are used as the basis for evaluating the quality, and the health condition of the gateway electric energy meter is obtained after all index values are accumulated together, so that the evaluation interpretability is improved while the weight objectivity is realized.
By applying the technical scheme of the embodiment, index data of preset evaluation dimensions of the evaluation indexes corresponding to each gateway electric energy meter to be evaluated in the bus balance management system are obtained. And calculating the independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method. Constructing an initial matrix according to all index data, determining the index type corresponding to each index data in the initial matrix, converting all non-huge indexes in the initial matrix into huge indexes, obtaining a forward standardized matrix, standardizing the forward standardized matrix, obtaining a standardized matrix, selecting any one evaluation index, determining the worst solution and the optimal solution corresponding to the selected evaluation index according to all standardized index data corresponding to the selected evaluation index, and sequentially calculating the worst solution distance from each standardized index data to the worst solution and the optimal solution distance to the optimal solution in all standardized index data corresponding to the selected evaluation index. And calculating the optimal solution occupation ratio of each standardized index data according to the worst solution distance and the optimal solution distance, and obtaining the sub-item score of the index data corresponding to each standardized index data. And obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of each evaluation index corresponding to each gateway electric energy meter to be evaluated and the independent information weight of each evaluation index, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the state comprehensive score. The forward matrix is obtained by unifying index types (forward processing) of the original data matrix, the effect of each index dimension is eliminated by performing standardized processing on the forward matrix, then index values of objects in each dimension are calculated, the index values are used as the basis for evaluating the quality, and the health condition of the gateway electric energy meter is obtained after all index values are accumulated together, so that the evaluation interpretability is improved while the weight objectivity is realized.
Further, as a refinement and extension of the specific implementation manner of the foregoing embodiment, in order to fully describe the specific implementation process of the embodiment, another method for evaluating the state of a gateway electric energy meter is provided, as shown in fig. 4, where the method includes:
step 401, obtaining index data of preset evaluation dimensions of evaluation indexes corresponding to each gateway electric energy meter to be evaluated in a bus balance management system.
In the above embodiment of the present application, index data of preset evaluation dimensions of evaluation indexes corresponding to each gateway electric energy meter to be evaluated in the bus balance management system is obtained, so that a status comprehensive score of each gateway electric energy meter to be evaluated can be obtained according to the index data.
And step 402, calculating the independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method, and calculating the item score of each index data according to the index data and the good-bad solution distance method.
And then, calculating the independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method, and calculating the item score of each index data according to the index data and the good and bad solution distance method. By combining the independent information data fluctuation weighting method with the good-bad solution distance method, the data self information and the data independent degree are combined and measured to further obtain the weight of each index, and the evaluation interpretability is improved while the weight objectivity is achieved.
Step 403, selecting any gateway electric energy meter to be evaluated, and determining the item scores of the index data of each evaluation index corresponding to the selected gateway electric energy meter to be evaluated and the independent information weights of the evaluation indexes corresponding to each item score.
And step 404, summing products of independent information weights of the evaluation indexes corresponding to each item score and each item score to obtain a comprehensive state score of the selected gateway electric energy meter to be evaluated, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the state comprehensive score.
Then, selecting any gateway electric energy meter to be evaluated, determining the item scores of index data of all evaluation indexes corresponding to the gateway electric energy meter to be evaluated and the independent information weights of the evaluation indexes corresponding to each item score, summing the products of the independent information weights of the evaluation indexes corresponding to each item score and each item score to obtain the comprehensive state score of the gateway electric energy meter to be evaluated, evaluating the state of the gateway electric energy meter to be evaluated according to the state comprehensive score, specifically, calculating the comprehensive state score of each gateway electric energy meter to be evaluated by constructing a weighted standardization matrix Z,
wherein w is j For the independent information weight of the j-th evaluation index, the higher the comprehensive state scoring result of the gateway electric energy meter to be evaluated is, the more the health degree of the gateway electric energy meter is illustratedHigh. Generally, the evaluation standard is that the ranking is low for several continuous days or several continuous weeks (adjusted at any time according to the preset evaluation dimension) as the bad state, and the specific situation can be specifically judged according to the production environment. And particularly, the transverse grading can be carried out according to the grading of each evaluation index of each gateway electric energy meter to be evaluated, the evaluation modes are various, and the basic data of the comprehensive evaluation modes are provided.
By applying the technical scheme of the embodiment, index data of preset evaluation dimensions of the evaluation indexes corresponding to each gateway electric energy meter to be evaluated in the bus balance management system are obtained. And calculating the independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method, and calculating the sub-item score of each index data according to the index data and the good-bad solution distance method. Selecting any gateway electric energy meter to be evaluated, and determining the item scores of the index data of all the evaluation indexes corresponding to the gateway electric energy meter to be evaluated and the independent information weights of the evaluation indexes corresponding to each item score. And summing the product of the independent information weights of the evaluation indexes corresponding to each item score and each item score to obtain the comprehensive state score of the selected gateway electric energy meter to be evaluated, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the state comprehensive score. As shown in fig. 5, by determining the gateway electric energy meters to be evaluated, obtaining index data of each gateway electric energy meter to be evaluated, screening the index data to determine non-abandoned amount evaluation indexes, calculating index discrete coefficients and independent information ratios by an independent information data fluctuation weighting method, obtaining independent information weights, calculating sub-item scores by a good-bad solution distance method, and finally obtaining a state comprehensive score according to the independent information weights and the sub-item scores, the method realizes that a measuring point daily dimension statistical database based on a bus balance system determines required evaluation dimensions and establishes a comprehensive evaluation index system, and simultaneously evaluates the operation state of the gateway electric energy meters by the independent information data fluctuation weighting method and the good-bad solution distance method, so that the comprehensive operation state of the gateway electric energy meters can be mastered in time.
Further, as a specific implementation of the method of fig. 1, an embodiment of the present application provides a gateway electric energy meter state evaluation device, as shown in fig. 6, where the device includes:
the data acquisition module 501 is configured to acquire index data of preset evaluation dimensions of each evaluation index corresponding to each gateway electric energy meter to be evaluated in the bus balance management system.
The data calculation module 502 is configured to calculate an independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method, and calculate a score of each index data according to the index data and the good-bad solution distance method.
The state evaluation module 503 is configured to obtain a state comprehensive score of each of the to-be-evaluated gateway electric energy meters according to the sub-item scores of the index data of the respective corresponding evaluation indexes of each of the to-be-evaluated gateway electric energy meters and the independent information weights of each of the evaluation indexes, so as to evaluate the state of the to-be-evaluated gateway electric energy meters according to the state comprehensive score.
Optionally, the data calculation module 502 is further configured to:
selecting any one evaluation index, and calculating an index discrete coefficient of the selected evaluation index according to all index data corresponding to the selected evaluation index;
Sequentially carrying out regression analysis by taking each index data in all index data corresponding to the selected evaluation index as a dependent variable and other index data as independent variables to obtain a fitting goodness, and obtaining independent information ratio according to the fitting goodness;
and obtaining the independent information weight corresponding to the selected evaluation index according to the index discrete coefficient and the independent information ratio.
Optionally, the data calculation module 502 is further configured to:
respectively normalizing the index discrete coefficient and the independent information ratio, and fusing the normalized index discrete coefficient and the independent information ratio according to a multiplication model to obtain the pure information quantity of the selected evaluation index;
and calculating the percentage of the pure information quantity of the selected evaluation index in the sum of the pure information quantities corresponding to each evaluation index, and obtaining the independent information weight of the selected evaluation index.
Optionally, the data calculation module 502 is further configured to:
if the index data of the selected evaluation index at each gateway electric energy meter to be evaluated is consistent, the independent information weight of the selected evaluation index is not calculated, and the selected evaluation index is determined to be a discarding amount evaluation index;
calculating the item score of the index data of each non-abandoned amount evaluation index according to the index data of the non-abandoned amount evaluation index and the good-bad solution distance method;
And obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of the non-abandoned amount evaluation indexes corresponding to each gateway electric energy meter to be evaluated and the independent information weights of each non-abandoned amount evaluation index.
Optionally, the data calculation module 502 is further configured to:
constructing an initial matrix according to all index data, determining an index type corresponding to each index data in the initial matrix, and converting all non-huge indexes in the initial matrix into huge indexes to obtain a forward matrix, wherein the index types comprise the huge indexes, the tiny indexes, the intermediate indexes and interval indexes;
and normalizing the forward matrix to obtain a normalized matrix, and obtaining the score of each index data according to the normalized matrix.
Optionally, the normalization matrix includes normalization index data; the data calculation module 602 is further configured to:
selecting any one evaluation index, and determining the worst solution and the optimal solution corresponding to the selected evaluation index according to all standardized index data corresponding to the selected evaluation index;
sequentially calculating the worst solution distance from each piece of standardized index data to the worst solution and the optimal solution distance from each piece of standardized index data to the optimal solution in all pieces of standardized index data corresponding to the selected evaluation indexes;
And calculating the optimal solution occupation ratio of each standardized index data according to the worst solution distance and the optimal solution distance, and obtaining the sub-item score of the index data corresponding to each standardized index data.
Optionally, the state evaluation module 503 is further configured to:
selecting any gateway electric energy meter to be evaluated, and determining the sub-item scores of the index data of each evaluation index corresponding to the gateway electric energy meter to be evaluated and the independent information weight of the evaluation index corresponding to each sub-item score;
and summing the product of the independent information weights of the evaluation indexes corresponding to each item score to obtain the comprehensive state score of the selected gateway electric energy meter to be evaluated.
It should be noted that, other corresponding descriptions of each functional unit related to the gateway electric energy meter state evaluation device provided by the embodiment of the present application may refer to corresponding descriptions in the methods of fig. 1 to fig. 4, and are not repeated herein.
Based on the method shown in fig. 1 to 4, correspondingly, the embodiment of the application further provides a storage medium, on which a computer program is stored, and the computer program realizes the method for evaluating the state of the gateway electric energy meter shown in fig. 1 to 4 when being executed by a processor.
Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.), and includes several instructions for causing a computer device (may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective implementation scenario of the present application.
Based on the method shown in fig. 1 to fig. 4 and the virtual device embodiment shown in fig. 6, in order to achieve the above object, the embodiment of the present application further provides a computer device, which may specifically be a personal computer, a server, a network device, etc., where the computer device includes a storage medium and a processor; a storage medium storing a computer program; and a processor for executing a computer program to implement the gateway electric energy meter state evaluation method as shown in fig. 1 to 4.
Optionally, the computer device may also include a user interface, a network interface, a camera, radio Frequency (RF) circuitry, sensors, audio circuitry, WI-FI modules, and the like. The user interface may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (e.g., bluetooth interface, WI-FI interface), etc.
It will be appreciated by those skilled in the art that the architecture of a computer device provided in the present embodiment is not limited to the computer device, and may include more or fewer components, or may combine certain components, or may be arranged in different components.
The storage medium may also include an operating system, a network communication module. An operating system is a program that manages and saves computer device hardware and software resources, supporting the execution of information handling programs and other software and/or programs. The network communication module is used for realizing communication among all components in the storage medium and communication with other hardware and software in the entity equipment.
Through the description of the above embodiments, it can be clearly understood by those skilled in the art that the present application can be implemented by means of software plus a necessary general hardware platform, or can be implemented by hardware, and index data of preset evaluation dimensions of each evaluation index corresponding to each gateway electric energy meter to be evaluated in the bus balance management system can be obtained; calculating independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method, and calculating the sub-item score of each index data according to the index data and the good-bad solution distance method; and obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of each evaluation index corresponding to each gateway electric energy meter to be evaluated and the independent information weight of each evaluation index, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the state comprehensive score. The weight of each evaluation index is obtained by combining the self information and the independence degree of the measurement index data, and the interpretation of the evaluation is improved while the weight objectivity is achieved.
Those skilled in the art will appreciate that the drawing is merely a schematic illustration of a preferred implementation scenario and that the modules or flows in the drawing are not necessarily required to practice the application. Those skilled in the art will appreciate that modules in an apparatus in an implementation scenario may be distributed in an apparatus in an implementation scenario according to an implementation scenario description, or that corresponding changes may be located in one or more apparatuses different from the implementation scenario. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.
The above-mentioned inventive sequence numbers are merely for description and do not represent advantages or disadvantages of the implementation scenario. The foregoing disclosure is merely illustrative of some embodiments of the application, and the application is not limited thereto, as modifications may be made by those skilled in the art without departing from the scope of the application.

Claims (10)

1. The method for evaluating the state of the gateway electric energy meter is characterized by comprising the following steps of:
acquiring index data of preset evaluation dimensions of evaluation indexes corresponding to each gateway electric energy meter to be evaluated in a bus balance management system;
calculating independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method, and calculating the sub-item score of each index data according to the index data and the good-bad solution distance method;
And obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of each evaluation index corresponding to each gateway electric energy meter to be evaluated and the independent information weight of each evaluation index, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the state comprehensive score.
2. The method according to claim 1, wherein calculating the independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method comprises:
selecting any one evaluation index, and calculating an index discrete coefficient of the selected evaluation index according to all index data corresponding to the selected evaluation index;
sequentially carrying out regression analysis by taking each index data in all index data corresponding to the selected evaluation index as a dependent variable and other index data as independent variables to obtain a fitting goodness, and obtaining independent information ratio according to the fitting goodness;
and obtaining the independent information weight corresponding to the selected evaluation index according to the index discrete coefficient and the independent information ratio.
3. The method according to claim 2, wherein obtaining the independent information weight corresponding to the selected evaluation index according to the index discrete coefficient and the independent information ratio comprises:
Respectively normalizing the index discrete coefficient and the independent information ratio, and fusing the normalized index discrete coefficient and the independent information ratio according to a multiplication model to obtain the pure information quantity of the selected evaluation index;
and calculating the percentage of the pure information quantity of the selected evaluation index in the sum of the pure information quantities corresponding to each evaluation index, and obtaining the independent information weight of the selected evaluation index.
4. A method according to claim 3, wherein after selecting any one of the evaluation criteria, the method further comprises:
if the index data of the selected evaluation index at each gateway electric energy meter to be evaluated is consistent, the independent information weight of the selected evaluation index is not calculated, and the selected evaluation index is determined to be a discarding amount evaluation index;
calculating the item score of the index data of each non-abandoned amount evaluation index according to the index data of the non-abandoned amount evaluation index and the good-bad solution distance method;
and obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of the non-abandoned amount evaluation indexes corresponding to each gateway electric energy meter to be evaluated and the independent information weights of each non-abandoned amount evaluation index.
5. The method of claim 1, wherein calculating a score for each index data based on the index data and a good-bad solution distance method comprises:
constructing an initial matrix according to all index data, determining an index type corresponding to each index data in the initial matrix, and converting all non-huge indexes in the initial matrix into huge indexes to obtain a forward matrix, wherein the index types comprise the huge indexes, the tiny indexes, the intermediate indexes and interval indexes;
and normalizing the forward matrix to obtain a normalized matrix, and obtaining the score of each index data according to the normalized matrix.
6. The method of claim 5, wherein the normalization matrix comprises normalization index data; the obtaining the item score of each index data according to the standardized matrix comprises the following steps:
selecting any one evaluation index, and determining the worst solution and the optimal solution corresponding to the selected evaluation index according to all standardized index data corresponding to the selected evaluation index;
sequentially calculating the worst solution distance from each piece of standardized index data to the worst solution and the optimal solution distance from each piece of standardized index data to the optimal solution in all pieces of standardized index data corresponding to the selected evaluation indexes;
And calculating the optimal solution occupation ratio of each standardized index data according to the worst solution distance and the optimal solution distance, and obtaining the sub-item score of the index data corresponding to each standardized index data.
7. The method according to any one of claims 1 to 6, wherein the obtaining the comprehensive status score of each gateway electric energy meter to be evaluated according to the sub-item score of the index data of each evaluation index corresponding to each gateway electric energy meter to be evaluated and the independent information weight of each evaluation index includes:
selecting any gateway electric energy meter to be evaluated, and determining the sub-item scores of the index data of each evaluation index corresponding to the gateway electric energy meter to be evaluated and the independent information weight of the evaluation index corresponding to each sub-item score;
and summing the product of the independent information weights of the evaluation indexes corresponding to each item score to obtain the comprehensive state score of the selected gateway electric energy meter to be evaluated.
8. A gateway electric energy meter state evaluation device, the device comprising:
the data acquisition module is used for acquiring index data of preset evaluation dimensions of evaluation indexes corresponding to the gateway electric energy meters to be evaluated in the bus balance management system;
The data calculation module is used for calculating the independent information weight of each evaluation index according to the index data and the independent information data fluctuation weighting method and calculating the sub-item score of each index data according to the index data and the good-bad solution distance method;
the state evaluation module is used for obtaining the state comprehensive score of each gateway electric energy meter to be evaluated according to the item scores of the index data of each evaluation index corresponding to each gateway electric energy meter to be evaluated and the independent information weight of each evaluation index, so as to evaluate the state of the gateway electric energy meter to be evaluated according to the state comprehensive score.
9. A storage medium having stored thereon a computer program, which when executed by a processor, implements the method of state evaluation of a gateway electric energy meter according to any one of claims 1 to 7.
10. A computer device comprising a storage medium, a processor and a computer program stored on the storage medium and executable on the processor, characterized in that the processor implements the method of gateway electric energy meter state evaluation according to any one of claims 1 to 7 when executing the computer program.
CN202310591745.9A 2023-05-24 2023-05-24 Gateway electric energy meter state evaluation method and device, storage medium and computer equipment Pending CN116739417A (en)

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