CN113537763A - Method for evaluating response capability of intelligent distribution transformer terminal of power distribution internet of things - Google Patents
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Abstract
The invention provides a method for evaluating the response capability of an intelligent distribution transformer terminal of a power distribution internet of things, and belongs to the field of power distribution internet of things. Firstly, constructing a response capability evaluation index system of the intelligent distribution transformer terminal of the power distribution internet of things, taking each function of the intelligent distribution transformer terminal of the power distribution internet of things as an evaluation index of the index system, and evaluating the response capability of the intelligent distribution transformer terminal of the power distribution internet of things; secondly, analyzing and calculating the index weight in the index system by adopting an analytic hierarchy process; finally, constructing an evaluation model by adopting a comprehensive index method; the invention solves the problem that the function detection response capability of the intelligent distribution transformer terminal of the distribution internet of things cannot be reasonably and comprehensively evaluated in the prior art. The invention provides corresponding function detection and evaluation indexes, thereby objectively evaluating the service functions of the intelligent distribution transformer terminals of different manufacturers and realizing comprehensive detection and comprehensive evaluation of the service functions of the intelligent distribution transformer terminals.
Description
Technical Field
The invention relates to an evaluation method, in particular to an evaluation method for response capability of an intelligent distribution transformer terminal of a power distribution internet of things, and belongs to the field of power distribution internet of things.
Background
The intelligent distribution transformer terminal is used as a core device of a distribution internet of things and has the service data analysis functions of low-voltage distribution network distribution transformer monitoring, power quality management, low-voltage fault rapid prejudgment and reporting, distribution area topology analysis, distribution area shunt subsection line loss analysis, diversified load management, distributed energy management and the like. Whether the response capability and the service function of the intelligent distribution transformer terminal are good or not is directly related to the normal operation of the distribution internet of things, and a standard means and a system for detecting the data analysis function of the intelligent distribution transformer terminal and testing the response capability of the intelligent distribution transformer terminal are lacked at present.
At present, no relevant research or less relevant research content exists in the evaluation field of the intelligent distribution transformer terminal of the distribution internet of things, and reasonable comprehensive evaluation on the function detection response capability of the intelligent distribution transformer terminal of the distribution internet of things cannot be carried out.
Therefore, it is urgently needed to establish a method for evaluating the response capability of the intelligent distribution transformer terminal of the power distribution internet of things, and provide corresponding function detection evaluation indexes, so that the service functions of the intelligent distribution transformer terminals of different manufacturers can be objectively evaluated, and comprehensive detection and comprehensive evaluation of the service functions of the intelligent distribution transformer terminals can be realized.
Disclosure of Invention
The following presents a simplified summary of the invention in order to provide a basic understanding of some aspects of the invention. It should be understood that this summary is not an exhaustive overview of the invention. It is not intended to determine the key or critical elements of the present invention, nor is it intended to limit the scope of the present invention. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is discussed later.
The invention provides a method for evaluating the response capability of an intelligent distribution transformer terminal of a distribution Internet of things, which comprises the following steps:
s1, establishing a response capability index system of the intelligent distribution transformer terminal of the power distribution Internet of things;
s2, analyzing and calculating the index weight in the index system;
s3 constructs an evaluation model.
Preferably, in step S1, a response capability index system of the power distribution internet of things intelligent distribution transformer terminal is established, and specifically, each function of the power distribution internet of things intelligent distribution transformer terminal is used as an evaluation index to evaluate the response capability of the power distribution internet of things intelligent distribution transformer terminal.
Preferably, in step S2, the index weight in the index system is analyzed and calculated, and an analytic hierarchy process is mainly used to analyze and calculate the index weight in the index system.
Preferably, in the step S3, the evaluation model is constructed mainly by using a comprehensive index method.
Preferably, the basic function and the service function in step S1 specifically include,
basic functions are as follows: data acquisition, electric energy metering, data recording, data statistics, terminal event recording, data processing, parameter setting and query and terminal maintenance;
and (4) service functions: distribution transformer monitoring, power quality management, station area topology identification, equipment state monitoring, low-voltage fault rapid study and report and station area shunt subsection line loss analysis.
Preferably, in step S2, the analyzing and calculating the index weight in the index system by using an analytic hierarchy process specifically includes the following steps:
s21, constructing a judgment matrix A;
s22, calculating the maximum eigenvalue lambda max of the judgment matrix A;
s23, consistency check is carried out; if the consistency check is passed, executing the step S24, otherwise executing the step S21;
s24, calculating index weight w of each layer index in evaluation indexesi。
Preferably, in the step S3, the specific method for constructing the evaluation model mainly using the comprehensive index method is:
calculating each qualitative index score of specific evaluation object
Calculating a final score of the evaluation object
Wherein n is the index number; w is aiIs the weight of each index; x is the number ofjFor each fingerA target evaluation score; i is 1,2, …, n.
Preferably, the specific method for constructing the judgment matrix a in S21 is as follows:
judging the data in the matrix to be the importance contrast coefficient between indexes in each layer, judging the ratio of matrix elements, and carrying out pairwise comparison and scoring on each related element in each layer by using a 1-9 ratio scaling method, wherein the matrix adopts the numbers 1-9 and the reciprocal thereof as importance scales, and the number 1 indicates that the importance of the two indexes is the same; 3, 5, 7, 9 respectively indicate that one element is slightly, significantly, strongly, and absolutely more important than another element; even numbers represent intermediate values of adjacent odd scales;
the specific method for calculating the maximum eigenvalue λ max of the judgment matrix a by S22 is as follows:
wherein n is the index number, aijJudging the data in the matrix A; w is ai、wjIs the weight of each index;
the specific method for performing consistency check in the step S23 is as follows:
wherein n is the index number; lambda [ alpha ]maxIs the maximum eigenvalue; RI is an average random consistency index, CI is a consistency index, and CR is a check coefficient;
s24, calculating index weight w of each layer index in evaluation indexesiThe specific method comprises the following steps:
wherein i is 1,2, …, n, wiFor each index weight value, judging the eigenvector corresponding to the maximum eigenvalue of the matrix A as
n is the index number. The invention has the following beneficial effects: according to the standardized evaluation method for the service functions of the intelligent distribution transformer terminal of the power distribution Internet of things, the corresponding function detection evaluation indexes are provided, so that the service functions of the intelligent distribution transformer terminals of different manufacturers can be objectively evaluated, and comprehensive detection and comprehensive evaluation of the service functions of the intelligent distribution transformer terminals are realized.
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The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flow chart of a method according to a first embodiment of the present invention.
Detailed Description
In order to make the technical solutions and advantages of the embodiments of the present application more apparent, the following further detailed description of the exemplary embodiments of the present application with reference to the accompanying drawings makes it clear that the described embodiments are only a part of the embodiments of the present application, and are not exhaustive of all embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
First embodiment, the embodiment is described with reference to fig. 1, and the method for evaluating the response capability of the intelligent distribution transformer terminal of the power distribution internet of things includes the following steps:
s1, establishing a response capability index system of the intelligent distribution transformer terminal of the power distribution Internet of things; the specific power distribution internet of things intelligent distribution transformer terminal response capability index system is shown in table 1:
table 1 power distribution internet of things intelligent distribution transformer terminal response capability index system
Specifically, according to an index system construction theory and a basic principle, each function of the intelligent distribution transformer terminal of the power distribution internet of things is used as an evaluation index, and the response capability of the intelligent distribution transformer terminal of the power distribution internet of things is evaluated.
When various functions of the intelligent terminal of the power distribution internet of things are detected, the response capability of the intelligent terminal is judged according to the function detection condition, and the evaluation index of the response capability of the intelligent terminal of the power distribution internet of things is established. And carrying out layer-by-layer statistical analysis on each function of the response capability of the intelligent terminal of the power distribution internet of things and the specific function corresponding to the function. The method comprises the following steps of firstly, dividing the functions into basic functions and business functions according to the functional types of the intelligent terminals of the power distribution internet of things.
Specifically, the basic function and the service function in step S1 specifically include,
basic functions are as follows: data acquisition, electric energy metering, data recording, data statistics, terminal event recording, data processing, parameter setting and query and terminal maintenance;
and (4) service functions: distribution transformer monitoring, power quality management, station area topology identification, equipment state monitoring, low-voltage fault rapid study and report and station area shunt subsection line loss analysis.
In particular, the basic functions are, among others,
the data acquisition function mainly comprises alternating current analog quantity acquisition, state quantity acquisition, residual current action protector acquisition, transformer state acquisition, environment state acquisition, electric energy quality equipment acquisition, ammeter data acquisition and monitoring, electric energy meter running state monitoring and other low-voltage sensing equipment acquisition.
The parameter setting and inquiring functions mainly comprise terminal parameter setting and inquiring, meter reading parameter setting and inquiring, freezing parameter setting and inquiring, statistical parameter setting and inquiring, event and reporting.
The terminal maintenance is mainly divided into three items of self-checking and abnormal recording, initialization and module information.
Specifically, in the service function,
the power quality management is mainly divided into voltage monitoring out-of-limit statistics, power factor out-of-limit statistics, voltage and current imbalance statistics, frequency monitoring statistics and harmonic monitoring statistics.
And according to a construction framework and a construction principle of an evaluation system, combining all basic functions and business functions of the intelligent terminal of the distribution transformer Internet of things to construct an evaluation index of the response capability of the intelligent terminal of the distribution transformer Internet of things. The evaluation index is mainly used for evaluating the response capability of the intelligent terminal of the power distribution internet of things.
S2, analyzing and calculating the index weight in the index system;
specifically, an analytic hierarchy process is mainly adopted to analyze and calculate the index weight in the index system.
The evaluation object is regarded as a system, the research object is decomposed into different elements according to the property and the general target of the system, and the elements are arranged into a plurality of layers from high to low according to the membership and the correlation degree between the elements, so that a multi-layer analysis system is established. The AHP is thought to decompose complex problems by establishing a clear hierarchical structure, introduce a measure theory, quantize human judgment scales by using relative scales through pairwise comparison, establish judgment matrixes layer by layer, solve the weights of the judgment matrixes and finally calculate the comprehensive weight of a scheme. The clear hierarchical structure is the key of the AHP decomposition and simplification comprehensive complex problem, and the attribute weight determined on the basis reflects the importance degree among indexes on the same layer.
Specifically, the method specifically comprises the following steps:
s21, constructing a judgment matrix A; the specific method comprises the following steps:
and constructing a judgment matrix on the basis of establishing a system level evaluation model. Judging the data in the matrix to be the importance contrast coefficient between indexes in each layer, judging the ratio of matrix elements, and carrying out pairwise comparison and scoring on each related element in each layer by using a 1-9 ratio scaling method, wherein the matrix adopts the numbers 1-9 and the reciprocal thereof as importance scales, and the number 1 indicates that the importance of the two indexes is the same; 3, 5, 7, 9 respectively indicate that one element is slightly, significantly, strongly, and absolutely more important than another element; even numbers represent intermediate values of adjacent odd scales;
s22, calculating the maximum eigenvalue lambda max of the judgment matrix A; the specific method comprises the following steps:
wherein n is the index number, aijJudging the data in the matrix A; w is ai、wjIs the weight of each index;
s23, consistency check is carried out; because of the complexity of multi-order judgment, some numerical values in the judgment matrix may have a front-to-back contradiction condition, so that consistency check is required to be performed on the judgment matrix by using the formula (5) and the formula (6); the specific method comprises the following steps:
wherein n is the order of the judgment matrix; lambda [ alpha ]maxIs the maximum eigenvalue; RI is an average random consistency index, CI is a consistency index, and CR is a check coefficient;
the larger the CI value is, the worse the consistency of the judgment matrix is. When CR <0.1, the matrix is judged to have satisfactory consistency. If the judgment matrix does not pass the consistency check, the mutual importance degree among the indexes needs to be assigned again until the judgment matrix passes the consistency check.
S24, calculating index weight w of each layer index in evaluation indexesiThe specific method comprises the following steps:
wherein i is 1,2, …, n, wiFor each index weight value, judging the eigenvector corresponding to the maximum eigenvalue of the matrix A as
n is the index number.
S3, constructing an evaluation model;
specifically, the evaluation model is constructed mainly by using a comprehensive index method.
The constructed evaluation model has large index quantity and all indexes of each layer are qualitative indexes, so that how to select a proper evaluation method to evaluate the response capability of the distribution transformer terminal is very critical. The invention combines the evaluation index and each index characteristic, and comprehensively considers and adopts a comprehensive index method to evaluate. The comprehensive index method is a method of analyzing and researching the quantitative relationship of things or phenomena by using various comprehensive indexes to comprehensively show the general characteristics of the things or phenomena. For the qualitative index, the highest value (corresponding score of 100 points) and the lowest value (corresponding score of 0 points) are determined according to the scoring standard values of the indexes. Then, each qualitative index score of the specific evaluation object is calculated. Since the system evaluation index is in a direct proportional relationship, a proportional method is adopted in the data processing process, and the following formula is used for calculation.
Calculating each qualitative index score of specific evaluation object
Weighting and summing each single evaluation index of the system layer by using a comprehensive index method, and finally calculating to obtain a final score of the evaluation object; the specific calculation formula is as follows:
wherein n is the index number; w is aiIs the weight of each index; x is the number ofjThe evaluation score of each index; i is 1,2, …, n.
While the invention has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of this description, will appreciate that other embodiments can be devised which do not depart from the scope of the invention as described herein. Furthermore, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and may not have been selected to delineate or circumscribe the inventive subject matter. Accordingly, many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the appended claims. The present invention has been disclosed in an illustrative rather than a restrictive sense, and the scope of the present invention is defined by the appended claims.
Claims (8)
1. A method for evaluating the response capability of an intelligent distribution transformer terminal of a power distribution Internet of things is characterized by comprising the following steps:
s1, establishing a response capability index system of the intelligent distribution transformer terminal of the power distribution Internet of things;
s2, analyzing and calculating the index weight in the index system;
s3 constructs an evaluation model.
2. The method according to claim 1, wherein in step S1, a power distribution internet of things intelligent distribution transformer terminal response capability index system is established, and in particular, each function of the power distribution internet of things intelligent distribution transformer terminal is used as an evaluation index to evaluate the response capability of the power distribution internet of things intelligent distribution transformer terminal.
3. The method of claim 2, wherein the step S2 is to analyze and calculate the index weight in the index system, and the index weight in the index system is mainly analyzed and calculated by using an analytic hierarchy process.
4. The method according to claim 3, wherein the step S3 is to construct the evaluation model by mainly using a comprehensive index method.
5. The method according to claim 4, wherein the basic functions and business functions of step S1 specifically include,
basic functions are as follows: data acquisition, electric energy metering, data recording, data statistics, terminal event recording, data processing, parameter setting and query and terminal maintenance;
and (4) service functions: distribution transformer monitoring, power quality management, station area topology identification, equipment state monitoring, low-voltage fault rapid study and report and station area shunt subsection line loss analysis.
6. The method as claimed in claim 5, wherein the step S2 of analyzing and calculating the index weight in the index system by using an analytic hierarchy process specifically includes the following steps:
s21, constructing a judgment matrix A;
s22, calculating the maximum eigenvalue lambda max of the judgment matrix A;
s23, consistency check is carried out; if the consistency check is passed, executing the step S24, otherwise executing the step S21;
s24, calculating index weight w of each layer index in evaluation indexesi。
7. The method according to claim 6, wherein the step S3 of constructing the evaluation model mainly adopts a comprehensive index method to construct the evaluation model by the specific method comprising the following steps:
calculating each qualitative index score of specific evaluation object
Calculating a final score of the evaluation object
Wherein n is the index number; w is aiIs the weight of each index; x is the number ofjThe evaluation score of each index; i is 1,2, …, n.
8. The method of claim 7,
s21 the specific method for constructing the judgment matrix A is as follows:
judging the data in the matrix to be the importance contrast coefficient between indexes in each layer, judging the ratio of matrix elements, and carrying out pairwise comparison and scoring on each related element in each layer by using a 1-9 ratio scaling method, wherein the matrix adopts the numbers 1-9 and the reciprocal thereof as importance scales, and the number 1 indicates that the importance of the two indexes is the same; 3, 5, 7, 9 respectively indicate that one element is slightly, significantly, strongly, and absolutely more important than another element; even numbers represent intermediate values of adjacent odd scales;
the specific method for calculating the maximum eigenvalue λ max of the judgment matrix a by S22 is as follows:
wherein n is the index number, aijJudging the data in the matrix A; w is ai、wjIs the weight of each index;
the specific method for performing consistency check in the step S23 is as follows:
wherein n is the order of the judgment matrix; lambda [ alpha ]maxIs the maximum eigenvalue; RI is an average random consistency index, CI is a consistency index, and CR is a check coefficient;
s24, calculating index weight w of each layer index in evaluation indexesiThe specific method comprises the following steps:
wherein i is 1,2, …, n, wiFor each index weight value, judging the eigenvector corresponding to the maximum eigenvalue of the matrix A as
n is the index number.
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