CN111563682A - Test evaluation method for distribution automation equipment - Google Patents

Test evaluation method for distribution automation equipment Download PDF

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CN111563682A
CN111563682A CN202010375473.5A CN202010375473A CN111563682A CN 111563682 A CN111563682 A CN 111563682A CN 202010375473 A CN202010375473 A CN 202010375473A CN 111563682 A CN111563682 A CN 111563682A
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郑友卓
付宇
张锐锋
肖小兵
何洪流
李前敏
吴鹏
刘安茳
郝树青
王卓月
柏毅辉
李忠
安波
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Guizhou Power Grid Co Ltd
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Abstract

The invention discloses a test evaluation method of distribution automation equipment, which comprises the steps of collecting test data of a distribution automation terminal and constructing a test evaluation index layering model; obtaining the scale of the index layer evaluation index to obtain a judgment matrix R; constructing a standard evaluation matrix X' through an index layer evaluation index test result; calculating subjective weight W of an index layer evaluation index by using an improved analytic hierarchy process; calculating an objective weight V of an index layer evaluation index; combining W and V to obtain an index layer evaluation index comprehensive weight vector A; performing composite operation, and outputting a criterion layer evaluation result B; obtaining the scale of the evaluation index of the criterion layer to obtain a judgment matrix R1; calculating subjective weight W1 of a criterion layer evaluation index by using an improved analytic hierarchy process; performing composite operation according to the subjective weight vector W1, and outputting a final evaluation result B1; the method solves the problems that the objectivity and the accuracy of an evaluation result existing in the test evaluation of the distribution automation equipment are easily influenced, so that the average accuracy is low and the like.

Description

Test evaluation method for distribution automation equipment
Technical Field
The invention belongs to a test evaluation technology of distribution automation equipment, and particularly relates to a test evaluation method of distribution automation equipment.
Background
Along with the continuous development of intelligent power distribution networks, distribution automation equipment has also obtained extensive popularization thereupon, and distribution automation equipment quantity also constantly increases, for distribution system's safe and reliable operation, must guarantee distribution automation equipment's high quality. Therefore, testing activities of the distribution automation equipment and construction of a test management platform need to be carried out, and intelligent data analysis and evaluation are carried out on test data results. At present, test evaluation work aiming at distribution automation equipment is mainly focused on projects, and has certain limitation, and evaluation methods for the distribution automation equipment test generally comprise an analytic hierarchy process, a fuzzy comprehensive evaluation method and the like. When the single analytic hierarchy process determines the weight, the factors of each layer are artificially weighted, the subjectivity of the weighting process is too strong, the consistency inspection needs to be carried out on the judgment matrix, if the consistency inspection needs to be carried out repeatedly, the calculated amount is too large, although the fuzzy comprehensive evaluation method has certain objectivity, the subjective factor can be influenced to a great extent when the membership function is selected, and the objectivity and the accuracy of the evaluation result are easily influenced.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method for testing and evaluating the distribution automation equipment is provided, and the problems that in the prior art, the objectivity and the accuracy of an evaluation result are easily influenced, so that the average accuracy is low and the like in the test and evaluation of the distribution automation equipment are solved.
The technical scheme of the invention is as follows:
a test evaluation method for distribution automation equipment comprises the following steps:
step A, collecting test data of a distribution automation terminal, and constructing a distribution automation terminal test evaluation index layered model, wherein the layered model comprises a target layer, a criterion layer and an index layer;
b, obtaining the scale of the evaluation index of the index layer, sequencing the importance degree, and solving a judgment matrix R;
step C, constructing a standard evaluation matrix X' through an index layer evaluation index test result;
step D, calculating subjective weight W of the index layer evaluation index by using an improved analytic hierarchy process;
step E, calculating objective weight V of evaluation indexes of the index layer by using a CRITIC method;
step F, combining the subjective weight W with the objective weight V to obtain an index layer evaluation index comprehensive weight vector A;
g, performing composite operation according to the comprehensive weight vector A, and outputting a criterion layer evaluation result B;
step H, obtaining the scale of the evaluation index of the criterion layer, sorting the importance degree, and obtaining a judgment matrix R1;
step I, calculating subjective weight W1 of a criterion layer evaluation index by using an improved analytic hierarchy process;
step J, performing composite operation according to the subjective weight vector W1, and outputting the final evaluationResult B1. The method for solving the judgment matrix R comprises the following steps: on the basis of all the evaluation indexes in the index layer in the step A, comparing every two evaluation indexes in the index layer, and sequencing the evaluation indexes according to the unreduced mode of the importance degree; for the index qiAnd q isi+1Comparing, and recording the corresponding scale value as tiThen, calculating other element values in the judgment matrix according to the transmissibility of the index importance degree, thereby obtaining a judgment matrix R;
Figure BDA0002479825450000021
the method for constructing the standard evaluation matrix X' comprises the following steps: b, based on the test results of all evaluation indexes in the index layer in the step A, carrying out index syntropy processing and index data dimensionless processing on the evaluation indexes of the index layer to construct a standard evaluation matrix X';
in the index homodromous treatment, the positive index refers to an index with better effect if the numerical value is larger, and the negative index refers to an index with better effect if the numerical value is smaller; converting the negative index into a positive index, wherein the conversion formula is as follows:
Figure BDA0002479825450000031
in the formula, xijIs a negative indicator; x'ijIs an index after the normalization; max | XiL is the maximum value of the ith index;
p is a coordination coefficient, and an evaluation matrix X' is obtained after the homodromous treatment;
in the non-dimensionalization processing of the index data, the formula for performing the non-dimensionalization processing on each index data is as follows:
Figure BDA0002479825450000032
in formula (II), x'ijThe elements in the evaluation matrix X' are obtained after the homodromous treatment, and m is the number of the distribution automation equipment to be evaluated and compared.
The method for calculating the subjective weight W in the step D comprises the following steps:
and B, based on the judgment matrix R obtained in the step B, calculating the subjective weight W of the evaluation index of the index layer by using an improved analytic hierarchy process, wherein the subjective weight calculation formula of each index is as follows:
Figure BDA0002479825450000033
in the formula, wiThe subjective weight value of the ith index;
Figure BDA0002479825450000034
the product of all elements in the ith row in the matrix R is determined.
Step E, the method for calculating the objective weight V of the evaluation index of the index layer by using the CRITIC method comprises the following steps:
establishing an objective weight calculation formula of each index as follows:
Figure BDA0002479825450000041
wherein v isiThe objective weight value of the ith index; n is the total index number of the layer; siIs the standard deviation of the i index; x ″)ijElements in matrix X' are evaluated for a standard; m is the number of the distribution automation equipment to be evaluated and compared; rhoijThe correlation coefficient of the ith index and the jth index is obtained; giThe information amount contained in the i-th index;
Figure BDA0002479825450000043
is the mean value of the ith index; cov (X ″)i,X″j) Is the covariance of the ith and jth rows of the normalized matrix X ". Note that, when the standard deviation of each index data is zero, the objective weight cannot be obtained.
The calculation method of the comprehensive weight vector A of the index layer evaluation index comprises the following steps:
Figure BDA0002479825450000042
wherein, aiIs the comprehensive weight value of the ith index.
The method for outputting the evaluation result B of the criterion layer comprises the following steps: and (4) multiplying the standard evaluation matrix X' obtained in the step (C) by the weight corresponding to the comprehensive weight A obtained in the step (F), and then summing to obtain an initial evaluation result of the criterion layer evaluation index, and outputting a criterion layer evaluation result B.
The method for establishing the judgment matrix R1 comprises the following steps: b, comparing the n evaluation indexes pairwise based on the evaluation indexes in the criterion layer in the step A, and sorting the evaluation indexes in a non-decreasing mode according to the importance degree; for the index siAnd si+1Comparing the two and marking the corresponding scale value as tiThen, calculating other element values in the judgment matrix according to the transmissibility of the index importance degree, thereby obtaining a judgment matrix R1;
Figure BDA0002479825450000051
the subjective weight W1 of the criterion layer evaluation index is calculated by the formula: a
Figure BDA0002479825450000052
In the formula: w is a1iThe subjective weight value of the ith index;
Figure BDA0002479825450000053
representing the product of all elements in row i of decision matrix R1.
And multiplying the criterion layer evaluation result B obtained in the step G by the corresponding weight in the subjective weight W1 obtained in the step I, adding the result to obtain a final evaluation result, and outputting the final evaluation result B1.
The invention has the beneficial effects that:
the improved analytic hierarchy process and the CRITIC process adopted by the invention have higher applicability and practicability in the aspects of determination of subjective and objective weights respectively, and the improved analytic hierarchy process has the advantages that consistency inspection is not needed, so that the calculated amount is greatly reduced; the CRITIC method has the advantages that when objective weighting is carried out, actual test data of each evaluation index is adopted for calculation, and weighting results are hardly influenced by subjective factors.
The improved analytic hierarchy process (subjective weighting method) and the CRITIC process (objective weighting method) are fused and applied to the test evaluation process of the distribution automation equipment, so that both subjective factors and objective factors are fully utilized, the weighting process is more reasonable, the evaluation method is more scientific and comprehensive, the operability is higher, the intelligent data processing, analysis and evaluation based on system test input data and an overall test result can be realized, and the technical support is provided for the power company to develop the construction of a distribution automation equipment test management platform.
The problem of the prior art to the objectivity and the accuracy of the assessment result that distribution automation equipment test evaluation exists easily receive the influence and lead to average accuracy low grade is solved.
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FIG. 1 is a flow chart of a test evaluation method of the present invention;
fig. 2 is a schematic diagram of a test evaluation hierarchy model of distribution automation equipment according to an embodiment of the present invention.
Detailed Description
The invention discloses a test evaluation method of distribution automation equipment, which comprises the following steps:
step A, collecting test data of the distribution automation terminal, and constructing a distribution automation terminal test evaluation index layering model which comprises a target layer, a standard layer and an index layer;
b, obtaining the scale of the evaluation index of the index layer, sequencing the importance degree, and solving a judgment matrix R;
step C, constructing a standard evaluation matrix X' through an index layer evaluation index test result;
step D, calculating subjective weight W of the index layer evaluation index by using an improved analytic hierarchy process;
step E, calculating objective weight V of evaluation indexes of the index layer by using a CRITIC method;
step F, combining the subjective weight W with the objective weight V to obtain an index layer evaluation index comprehensive weight vector A;
g, performing composite operation according to the comprehensive weight vector A, and outputting a criterion layer evaluation result B;
step H, obtaining the scale of the evaluation index of the criterion layer, sorting the importance degree, and obtaining a judgment matrix R1;
step I, calculating subjective weight W1 of a criterion layer evaluation index by using an improved analytic hierarchy process;
step J, performing composite operation according to the subjective weight vector W1, and outputting a final evaluation result B1;
in the step B, based on each evaluation index in the index layer in the step A, comparing n evaluation indexes in the index layer under the same evaluation index in the criterion layer pairwise according to expert opinions or user requirements, and sorting the evaluation indexes in an unreduced mode according to the importance degree; for the index qiAnd q isi+1Comparing the two and marking the corresponding scale value as tiThen, calculating other element values in the judgment matrix according to the transmissibility of the index importance degree, thereby obtaining a judgment matrix R;
Figure BDA0002479825450000071
in the step C, based on the test result of each evaluation index in the index layer in the step A, carrying out index syntropy processing and index data dimensionless processing on the evaluation index of the index layer to construct a standard evaluation matrix X';
in the index homodromous processing, a positive index refers to an index having a better effect when the numerical value is larger, and a negative index refers to an index having a better effect when the numerical value is smaller. Converting the negative indicator into a positive indicator, wherein the conversion formula is as follows:
Figure BDA0002479825450000072
wherein x isijIs a negative indicator; x'ijIs an index after the normalization; max | XiL is the maximum value of the ith index;
p is a coordination coefficient, and an evaluation matrix X' is obtained after the homodromous treatment;
in the non-dimensionalization processing of the index data, a non-dimensionalization processing formula for each index data is as follows:
Figure BDA0002479825450000073
in formula (II), x'ijThe elements in the evaluation matrix X' are obtained after the homodromous treatment, and m is the number of the distribution automation equipment to be evaluated and compared.
In the step D, based on the judgment matrix R obtained in the step B, the subjective weight W of the index layer evaluation index is calculated by using an improved analytic hierarchy process, and the calculation formula of the subjective weight of each index is as follows:
Figure BDA0002479825450000081
wherein, wiThe subjective weight value of the ith index;
Figure BDA0002479825450000082
representing the product of all elements in the ith row of the decision matrix R.
In step E, based on the standard evaluation matrix X ″ obtained in step C, an objective weight V of an index layer evaluation index is calculated by using the CRITIC method, and a calculation formula of the objective weight of each index is as follows:
Figure BDA0002479825450000083
wherein v isiThe objective weight value of the ith index; n is the total index number of the layer; siIs the standard deviation of the i index; x ″)ijElements in matrix X' are evaluated for a standard; m is the number of the distribution automation equipment to be evaluated and compared; rhoijThe correlation coefficient of the ith index and the jth index is obtained; giThe information amount contained in the i-th index;
Figure BDA0002479825450000084
is the mean value of the ith index; cov (X ″)i,X″j) Is the covariance of the ith and jth rows of the normalized matrix X ". Note that, when the standard deviation of each index data is zero, the objective weight cannot be obtained.
In step F, the calculation formula for obtaining the comprehensive weight vector a of the evaluation index of the index layer by combining the subjective weight W and the objective weight V is as follows:
Figure BDA0002479825450000091
wherein, aiIs the comprehensive weight value of the ith index. It should be noted that, when the standard deviation of each index data is zero, the comprehensive weight value is a subjective weight value.
In the step G, multiplying the standard evaluation matrix X' obtained in the step C by the weight corresponding to the comprehensive weight A obtained in the step F, and then adding the obtained product to obtain an initial evaluation result of the criterion layer evaluation index, and outputting a criterion layer evaluation result B;
in the step H, based on all the evaluation indexes in the criterion layer in the step A, comparing n evaluation indexes pairwise according to expert opinions or user requirements, and sorting the evaluation indexes in an unreduced mode of importance degree; for the index siAnd si+1Comparing the two and marking the corresponding scale value as tiThen, calculating other element values in the judgment matrix according to the transmissibility of the index importance degree, thereby obtaining a judgment matrix R1;
Figure BDA0002479825450000092
in step I, based on the judgment matrix R1 obtained in step H, a criterion layer evaluation index subjective weight W1 is calculated by using an improved analytic hierarchy process, and the calculation formula of the subjective weights of the indexes is as follows:
Figure BDA0002479825450000093
wherein, w1iThe subjective weight value of the ith index;
Figure BDA0002479825450000094
representing the product of all elements in row i of decision matrix R1.
In step J, the criterion layer evaluation result B obtained in step G is multiplied by the corresponding weight in the subjective weight W1 obtained in step I, and then summed up to obtain a final evaluation result, and a final evaluation result B1 is output.
The method for testing and evaluating distribution automation equipment based on the improved analytic hierarchy process and the CRITIC process provided by the present invention is further described with reference to the accompanying drawings and embodiments.
As shown in fig. 1, a flow chart of a power distribution automation equipment test evaluation method based on an improved analytic hierarchy process and a CRITIC method provided by the present invention includes the following steps:
and step A, collecting test data of the distribution automation terminal, and constructing a distribution automation terminal test evaluation index layering model which comprises a target layer, a standard layer and an index layer. In the present embodiment, a power distribution automation terminal test evaluation index hierarchical model is shown in fig. 2. The distribution automation device test data includes: high temperature influence, low temperature influence, damp heat influence, fault detection and processing, wave recording function, data transmission and storage, control function, time synchronization function, data acquisition and processing, maintenance and display, parameter retrieval and configuration, oscillatory wave immunity, power frequency magnetic field immunity, pulse magnetic field immunity, radio frequency electromagnetic field radiation immunity, damping oscillatory magnetic field immunity, voltage sag and short time interruption, electrostatic discharge immunity, electric fast transient pulse group immunity, surge immunity, state quantity, wave recording performance, continuous energization stability, basic error of AC input analog quantity, power frequency AC quantity allowable excessive input capacity, power supply load capacity, influence of AC analog quantity input, power consumption, insulation resistance, insulation strength, impact voltage resistance, protection level, mechanical vibration, structure inspection, appearance inspection, interface inspection, and classification into environmental influence, Main functions, electromagnetic compatibility, basic performance, insulation performance, structural and mechanical properties, general inspection.
In the step B, based on each evaluation index in the index layer in the step A, comparing n evaluation indexes in the index layer under the same evaluation index in the criterion layer pairwise according to expert opinions or user requirements, and sorting the evaluation indexes in an unreduced mode according to the importance degree; for the index qiAnd q isi+1Comparing the two and marking the corresponding scale value as tiAnd then, calculating other element values in the judgment matrix according to the transmissibility of the index importance degree, thereby obtaining the judgment matrix R.
Figure BDA0002479825450000111
In this example, the comparative scale used is as shown in Table 1. According to the expert opinion and the requirement of the user, the scale value between every two indexes of the index layer under the same index in the criterion layer is determined, so that the judgment matrix R is obtained1～R7. Wherein, for R1In other words, according to the expert opinion and the requirement of the user, the evaluation indexes are determined to establish the following sequence relation: high temperature effect-low temperature effect>The effect of damp heat; the relative importance between the indexes is determined as follows: t is t1＝1，t21.2; for R2In other words, according to the expert opinion and the requirement of the user, the evaluation indexes are determined to establish the following sequence relation: fault detection and processing as wave recording function>Data transmission and storage and time synchronization and control functions and data acquisition and processing functions>And (3) maintaining and displaying, namely parameter retrieval and configuration, and determining the relative importance degree between indexes as follows: t is t1＝1，t2＝1.2，t3＝1，t4＝1，t5＝1，t6＝1.4，t71 is ═ 1; for R3In other words, according to the expert opinion and the requirement of the user, the evaluation indexes are determined to establish the following sequence relation: oscillation wave immunity, power frequency magnetic field immunity, pulse magnetic field immunity, radio frequency electromagnetic field radiation immunity and damped oscillation magnetic field immunity>Electrostatic discharge immunity and fast transient for voltage sag and short interruptionAnd determining the relative importance degree between indexes as follows: t is t1＝1，t2＝1，t3＝1，t4＝1，t5＝1.2，t6＝1，t7＝1，t81 is ═ 1; for R4In other words, according to the expert opinion and the requirement of the user, the evaluation indexes are determined to establish the following sequence relation: recording performance>Continuous power-on stability, basic error of AC input analog quantity, allowable excess input capacity of power frequency AC quantity>Carrying capacity of power supply>The influence of the input of the alternating current analog quantity is power consumption, and the relative importance degree between indexes is determined as follows: t is t1＝1，t2＝1.2，t3＝1，t4＝1，t5＝1.2，t6＝1.2，t71 is ═ 1; for R5In other words, according to the expert opinion and the requirement of the user, the evaluation indexes are determined to establish the following sequence relation: the relative importance degree between the determined indexes is as follows: t is t1＝1，t21 is ═ 1; for R6In other words, according to the expert opinion and the requirement of the user, the evaluation indexes are determined to establish the following sequence relation: the protection grade is mechanical vibration, and the relative importance degree between the indexes is determined as follows: t is t11 is ═ 1; for R7In other words, according to the expert opinion and the requirement of the user, the evaluation indexes are determined to establish the following sequence relation: structural inspection>And (3) appearance inspection, namely interface inspection, and determining the relative importance degree between indexes as follows: t is t1＝1.2，t2＝1；
TABLE 1 definition of the respective scale values
Figure BDA0002479825450000121
Figure BDA0002479825450000122
Figure BDA0002479825450000123
Figure BDA0002479825450000131
Figure BDA0002479825450000132
Figure BDA0002479825450000133
Figure BDA0002479825450000134
Figure BDA0002479825450000135
In the step C, based on the test result of each evaluation index in the index layer in the step A, carrying out index syntropy processing and index data dimensionless processing on the evaluation index of the index layer to construct a standard evaluation matrix X';
in the index homodromous processing, a positive index refers to an index having a better effect when the numerical value is larger, and a negative index refers to an index having a better effect when the numerical value is smaller. Converting the negative indicator into a positive indicator, wherein the conversion formula is as follows:
Figure BDA0002479825450000136
wherein x isijIs a negative indicator; x'ijIs an index after the normalization; max | XiL is the maximum value of the ith index;
p is a coordination coefficient, and an evaluation matrix X' is obtained after the homodromous treatment;
in the non-dimensionalization processing of the index data, a non-dimensionalization processing formula for each index data is as follows:
Figure BDA0002479825450000141
in formula (II), x'ijThe elements in the evaluation matrix X' are obtained after the homodromous treatment, and m is the number of the distribution automation equipment to be evaluated and compared.
In this embodiment, two sets of the test results of the evaluation indexes of the power automation equipment are selected for calculation, and the standard evaluation matrix X is obtained through the index syntropy processing and the index data dimensionless processing1″～X7″。
Figure BDA0002479825450000142
Figure BDA0002479825450000143
Figure BDA0002479825450000144
Figure BDA0002479825450000145
Figure BDA0002479825450000146
Figure BDA0002479825450000151
Figure BDA0002479825450000152
In the step D, based on the judgment matrix R obtained in the step B, the subjective weight W of the index layer evaluation index is calculated by using an improved analytic hierarchy process, and the calculation formula of the subjective weight of each index is as follows:
Figure BDA0002479825450000153
wherein, wiThe subjective weight value of the ith index;
Figure BDA0002479825450000154
representing the product of all elements in the ith row of the decision matrix R.
In this embodiment, the determination matrix R is obtained based on the step B1～R7Calculating subjective weight W of index layer evaluation index by using improved analytic hierarchy process1～W7。W1＝[0.3529,0.3529,0.2941]T；W2＝[0.1533,0.1533,0.1277,0.1277,0.1277,0.1277,0.0912,0.0912]T；W3＝[0.1200,0.1200,0.1200,0.1200,0.1200,0.1000,0.1000,0.1000,0.1000]T；W4＝[0.1574,0.1574,0.1312,0.1312,0.1312,0.1093,0.0911,0.0911]T；W5＝[0.3333,0.3333,0.3333]T；W6＝[0.5000,0.5000]T；W7＝[0.3750,0.3125,0.3125]T。
In step E, based on the standard evaluation matrix X ″ obtained in step C, an objective weight V of an index layer evaluation index is calculated by using the CRITIC method, and a calculation formula of the objective weight of each index is as follows:
Figure BDA0002479825450000155
wherein v isiThe objective weight value of the ith index; n is the total index number of the layer; siIs the standard deviation of the i index; x ″)ijElements in matrix X' are evaluated for a standard; m is the number of the distribution automation equipment to be evaluated and compared; rhoijThe correlation coefficient of the ith index and the jth index is obtained; giThe information amount contained in the i-th index;
Figure BDA0002479825450000162
is the mean value of the ith index; cov (X ″)i,X″j) Is the covariance of the ith and jth rows of the normalized matrix X ". Note that, when the standard deviation of each index data is zero, the objective weight cannot be obtained.
In the present embodimentBased on the standard evaluation matrix X obtained in step C1″～X7″Calculating objective weight V of index layer evaluation index by CRITIC method1～V7Due to X2″,X6″,X7″The values of the medium elements are all consistent, so the standard deviation is zero, and the objective weight V cannot be obtained2,V6,V7。V1＝[0.5660,0.2740,0.1600]T；V3＝[0.2519,0.0550,0.0550,0.0550,0.0550,0.3329,0.1299,0.0217,0.0438]T；V4＝[0.0394,0.0394,0.0394,0.1705,0.0827,0.0808,0.1024,0.4453]T；V5＝[0.6865,0.2236,0.0900]T。
In step F, the calculation formula for obtaining the comprehensive weight vector a of the evaluation index of the index layer by combining the subjective weight W and the objective weight V is as follows:
Figure BDA0002479825450000161
wherein, aiIs the comprehensive weight value of the ith index. It should be noted that, when the standard deviation of each index data is zero, the comprehensive weight value is a subjective weight value.
In this embodiment, the subjective weight W and the objective weight V obtained by the respective calculations in step D and step E are combined to obtain the comprehensive weight a1～A7。A1＝[0.4585,0.3190,0.2225]T；A2＝[0.1533,0.1533,0.1277,0.1277,0.1277,0.1277,0.0912,0.0912]T；A3＝[0.1915,0.0895,0.0895,0.0895,0.0895,0.2010,0.1255,0.0513,0.0729]T；A4＝[0.0900,0.0900,0.0822,0.1709,0.1190,0.1074,0.1104,0.2302]T；A5＝[0.5174,0.2953,0.1873]T；A6＝[0.5000,0.5000]T；A7＝[0.3750,0.3125,0.3125]T。
In the step G, multiplying the standard evaluation matrix X' obtained in the step C by the weight corresponding to the comprehensive weight A obtained in the step F, and then adding the obtained product to obtain an initial evaluation result of the criterion layer evaluation index, and outputting a criterion layer evaluation result B;
in this embodiment, the standard evaluation matrix X obtained in step C1″～X7″And the comprehensive weight A obtained in the step F1～A7And multiplying the corresponding weights and then summing to obtain a criterion layer evaluation result B.
Figure BDA0002479825450000171
In the step H, based on all the evaluation indexes in the criterion layer in the step A, comparing n evaluation indexes pairwise according to expert opinions or user requirements, and sorting the evaluation indexes in an unreduced mode of importance degree; for the index siAnd si+1Comparing the two and marking the corresponding scale value as tiThen, calculating other element values in the judgment matrix according to the transmissibility of the index importance degree, thereby obtaining a judgment matrix R1;
Figure BDA0002479825450000172
in this example, the comparative scale used is as shown in Table 1. And determining the scale value between every two indexes in the criterion layer according to the expert opinion and the requirement of the user so as to obtain a judgment matrix R1. For R1, determining the evaluation index according to the expert opinion and the requirement of the user and establishing the following sequence relation: environmental impact, main function, electromagnetic compatibility, basic performance, and insulating performance>Structural and mechanical Properties>General inspection; the relative importance between the indexes is determined as follows: t is t1＝1，t2＝1，t3＝1，t4＝1，t5＝1.6，t6＝1.8。
Figure BDA0002479825450000181
In step I, based on the judgment matrix R1 obtained in step H, a criterion layer evaluation index subjective weight W1 is calculated by using an improved analytic hierarchy process, and the calculation formula of the subjective weights of the indexes is as follows:
Figure BDA0002479825450000182
wherein, w1iThe subjective weight value of the ith index;
Figure BDA0002479825450000183
representing the product of all elements in row i of decision matrix R1.
In the present embodiment, the index layer evaluation index subjective weight W1 is calculated by using the modified analytic hierarchy process based on the determination matrix R1 obtained in step H. W1 ═ 0.1674,0.1674,0.1674,0.1674,0.1674,0.1047,0.0581]T。
In step J, the criterion layer evaluation result B obtained in step G is multiplied by the corresponding weight in the subjective weight W1 obtained in step I, and then summed up to obtain a final evaluation result, and a final evaluation result B1 is output.
In the present embodiment, the criterion layer evaluation result B obtained in step G is multiplied by the corresponding weight of the subjective weight W1 obtained in step I, and then summed, so as to obtain a final evaluation result B1 ═ 0.69620.7157, where the test evaluation result of the distribution automation equipment 1 is 0.6962, the test evaluation result of the distribution automation equipment 2 is 0.7157, and the test evaluation result of the distribution automation equipment 2 is better than the evaluation result of the distribution automation equipment 1. The distribution automation equipment test evaluation method based on the improved analytic hierarchy process and the CRITIC method can more scientifically and comprehensively realize intelligent data processing, analysis and evaluation of system test input data, and the comparison with the test evaluation result based on the improved analytic hierarchy process is shown in Table 2.
TABLE 2 comparison of test and evaluation results
Figure BDA0002479825450000191

Claims (10)

1. A test evaluation method for distribution automation equipment comprises the following steps:
step A, collecting test data of a distribution automation terminal, and constructing a distribution automation terminal test evaluation index layered model, wherein the layered model comprises a target layer, a criterion layer and an index layer;
b, obtaining the scale of the evaluation index of the index layer, sequencing the importance degree, and solving a judgment matrix R;
step C, constructing a standard evaluation matrix X' through an index layer evaluation index test result;
step D, calculating subjective weight W of the index layer evaluation index by using an improved analytic hierarchy process;
step E, calculating objective weight V of evaluation indexes of the index layer by using a CRITIC method;
step F, combining the subjective weight W with the objective weight V to obtain an index layer evaluation index comprehensive weight vector A;
g, performing composite operation according to the comprehensive weight vector A, and outputting a criterion layer evaluation result B;
step H, obtaining the scale of the evaluation index of the criterion layer, sorting the importance degree, and obtaining a judgment matrix R1;
step I, calculating subjective weight W1 of a criterion layer evaluation index by using an improved analytic hierarchy process;
and step J, performing composite operation according to the subjective weight vector W1, and outputting a final evaluation result B1.
2. The distribution automation device test evaluation method according to claim 1, characterized in that: the method for solving the judgment matrix R comprises the following steps: on the basis of all the evaluation indexes in the index layer in the step A, comparing every two evaluation indexes in the index layer, and sequencing the evaluation indexes according to the unreduced mode of the importance degree; for the index qiAnd q isi+1Comparing, and recording the corresponding scale value as tiThen, calculating other element values in the judgment matrix according to the transmissibility of the index importance degree, thereby obtaining a judgment matrix R;
Figure FDA0002479825440000021
3. the distribution automation device test evaluation method according to claim 1, characterized in that: the method for constructing the standard evaluation matrix X' comprises the following steps: b, based on the test results of all evaluation indexes in the index layer in the step A, carrying out index syntropy processing and index data dimensionless processing on the evaluation indexes of the index layer to construct a standard evaluation matrix X';
in the index homodromous treatment, the positive index refers to an index with better effect if the numerical value is larger, and the negative index refers to an index with better effect if the numerical value is smaller; converting the negative index into a positive index, wherein the conversion formula is as follows:
Figure FDA0002479825440000022
in the formula, xijIs a negative indicator; x'ijIs an index after the normalization; max | XiL is the maximum value of the ith index; p is a coordination coefficient, and an evaluation matrix X' is obtained after the homodromous treatment;
in the non-dimensionalization processing of the index data, the formula for performing the non-dimensionalization processing on each index data is as follows:
Figure FDA0002479825440000023
in formula (II), x'ijThe elements in the evaluation matrix X' are obtained after the homodromous treatment, and m is the number of the distribution automation equipment to be evaluated and compared.
4. The distribution automation device test evaluation method according to claim 1, characterized in that:
the method for calculating the subjective weight W in the step D comprises the following steps:
and B, based on the judgment matrix R obtained in the step B, calculating the subjective weight W of the evaluation index of the index layer by using an improved analytic hierarchy process, wherein the subjective weight calculation formula of each index is as follows:
Figure FDA0002479825440000031
in the formula, wiThe subjective weight value of the ith index;
Figure FDA0002479825440000032
the product of all elements in the ith row in the matrix R is determined.
5. The distribution automation device test evaluation method according to claim 1, characterized in that: step E, the method for calculating the objective weight V of the evaluation index of the index layer by using the CRITIC method comprises the following steps: establishing an objective weight calculation formula of each index as follows:
Figure FDA0002479825440000033
wherein v isiThe objective weight value of the ith index; n is the total index number of the layer; siIs the standard deviation of the i index; x ″)ijElements in matrix X' are evaluated for a standard; m is the number of the distribution automation equipment to be evaluated and compared; rhoijThe correlation coefficient of the ith index and the jth index is obtained; giThe information amount contained in the i-th index;
Figure FDA0002479825440000034
is the mean value of the ith index; cov (X ″)i,X″j) Is the covariance of the ith and jth rows of the normalized matrix X ". Note that, when the standard deviation of each index data is zero, the objective weight cannot be obtained.
6. The distribution automation device test evaluation method according to claim 1, characterized in that: the calculation method of the comprehensive weight vector A of the index layer evaluation index comprises the following steps:
Figure FDA0002479825440000041
wherein, aiIs the comprehensive weight value of the ith index.
7. The distribution automation device test evaluation method according to claim 1, characterized in that: the method for outputting the evaluation result B of the criterion layer comprises the following steps: and (4) multiplying the standard evaluation matrix X' obtained in the step (C) by the weight corresponding to the comprehensive weight A obtained in the step (F), and then summing to obtain an initial evaluation result of the criterion layer evaluation index, and outputting a criterion layer evaluation result B.
8. The distribution automation device test evaluation method according to claim 1, characterized in that: the method for establishing the judgment matrix R1 comprises the following steps: b, comparing the n evaluation indexes pairwise based on the evaluation indexes in the criterion layer in the step A, and sorting the evaluation indexes in a non-decreasing mode according to the importance degree; for the index siAnd si+1Comparing the two and marking the corresponding scale value as tiThen, calculating other element values in the judgment matrix according to the transmissibility of the index importance degree, thereby obtaining a judgment matrix R1;
Figure FDA0002479825440000042
9. the distribution automation device test evaluation method according to claim 1, characterized in that: the subjective weight W1 of the criterion layer evaluation index is calculated by the formula: a
Figure FDA0002479825440000043
In the formula: w is a1iThe subjective weight value of the ith index;
Figure FDA0002479825440000044
representing the product of all elements in row i of decision matrix R1.
10. The distribution automation device test evaluation method according to claim 1, characterized in that: the method for outputting the final evaluation result B1 is as follows: and multiplying the criterion layer evaluation result B obtained in the step G by the corresponding weight in the subjective weight W1 obtained in the step I, adding the result to obtain a final evaluation result, and outputting the final evaluation result B1.
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