CN114399135A - Power grid operation abnormity index cause correlation determination method based on analytic hierarchy process - Google Patents

Power grid operation abnormity index cause correlation determination method based on analytic hierarchy process Download PDF

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CN114399135A
CN114399135A CN202111428366.5A CN202111428366A CN114399135A CN 114399135 A CN114399135 A CN 114399135A CN 202111428366 A CN202111428366 A CN 202111428366A CN 114399135 A CN114399135 A CN 114399135A
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闫朝阳
仇晨光
熊浩
张振华
崔占飞
戴上
赵玉林
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State Grid Jiangsu Electric Power Co Ltd
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Abstract

The invention discloses a power grid operation abnormity index cause correlation determination method based on an analytic hierarchy process, wherein a target layer and a criterion layer to be verified or the criterion layer and an index layer are input into a constructed judgment matrix; calculating a weight coefficient of the judgment matrix; performing consistency check according to the weight coefficient, if the consistency check is smaller than a set threshold value, judging that the judgment matrix passes the consistency check, otherwise, failing to pass the consistency check and ending the operation; and carrying out priority arrangement on the target layer, the criterion layer and the index layer, and screening to obtain the layer with the maximum correlation degree of the cause of the abnormal operation index of the power grid. The method helps the scheduling personnel to quickly locate the abnormal factors which have the largest influence on the power grid at present, is convenient for preferentially processing key problems, and improves the response speed and the efficiency of troubleshooting.

Description

Power grid operation abnormity index cause correlation determination method based on analytic hierarchy process
Technical Field
The invention relates to a power grid operation abnormity index cause correlation determination method based on an analytic hierarchy process, and belongs to the technical field of power system operation and power transmission networks.
Background
With the rapid scale expansion of an extra-high voltage alternating current-direct current hybrid power grid, the new energy grid connection is rapidly developed, and the complexity of a power system is increased due to the rapid increase of novel load proportions such as a distributed power supply and energy storage. Aiming at the new requirements of a new generation of power system on scheduling operation control, comprehensive evaluation application is needed, various regulation and control service data are converged and fused based on a big data technology, and the internal rules among various data are analyzed and mined. An evaluation system based on the power grid operation indexes needs to provide guidance or auxiliary decision for scheduling operation services as much as possible, so that quick and corresponding and efficient operation is achieved, the problem of influencing abnormal operation of the power grid is solved, and the lean and intelligent levels of the power grid operation are improved.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a power grid operation abnormal index cause correlation degree determination method based on an analytic hierarchy process, and aims to help a dispatcher to quickly locate the abnormal factors which have the largest influence on a power grid at present, preferentially process key problems and improve response speed and fault removal efficiency.
In order to achieve the above object, the present invention provides a method for determining a cause correlation of an abnormal index of power grid operation based on an analytic hierarchy process, comprising:
inputting a target layer to be verified and a criterion layer, or the criterion layer and an index layer into a constructed judgment matrix;
calculating a weight coefficient of the judgment matrix;
performing consistency check according to the weight coefficient, if the consistency check is smaller than a set threshold value, judging that the judgment matrix passes the consistency check, otherwise, failing to pass the consistency check and ending the operation;
and carrying out priority arrangement on the target layer, the criterion layer and the index layer, and screening to obtain the layer with the maximum correlation degree of the cause of the abnormal operation index of the power grid.
Preferentially, obtaining a relation table between a target layer and a criterion layer according to an existing hierarchical structure model I;
and establishing a new hierarchical structure model II, and establishing a relation table between the index layer and the criterion layer.
Preferably, constructing a decision matrix comprises:
constructing a judgment matrix between a target layer and a criterion layer:
Figure BDA0003379290980000021
in the formula: a isijTo measure the importance of the ith index of the target layer/criterion layer to the jth index of the target layer/criterion layer, i is the [1, n ]]，j∈[1,n]N is the sum of the number of indexes in the target layer and the number of indexes in the criterion layer;
aijfollowing a positive reciprocal matrix:
Figure BDA0003379290980000022
in the formula, ajiIs a value for measuring the importance of the jth index of the target layer/criterion layer to the ith index of the target layer/criterion layer.
Preferably, constructing a decision matrix comprises:
constructing a judgment matrix between the index layer and the criterion layer:
Figure BDA0003379290980000023
in the formula: a isefTo measure the importance of the e index of index layer/criterion layer to the f index of index layer/criterion layer, e belongs to [1, h]，f∈[1,h]H is the sum of the number of indexes in the index layer and the number of indexes in the criterion layer；
aefFollowing a positive reciprocal matrix:
Figure BDA0003379290980000024
in the formula, aefThe importance of the e index of the index layer/criterion layer to the f index of the index layer/criterion layer is measured.
Preferentially, calculating the weight coefficient of the judgment matrix comprises:
calculating the jth index weight w according to a square root methodjComprises the following steps:
Figure BDA0003379290980000025
preferentially, calculating the weight coefficient of the judgment matrix comprises:
calculating the f index weight w according to the square root methodfComprises the following steps:
Figure BDA0003379290980000031
preferably, the consistency check is performed according to the weight coefficients, including:
calculating CI and CR:
Figure BDA0003379290980000032
wherein CI is the general consistency index of the judgment matrix of the target layer and the criterion layer, RI is the random consistency index of the judgment matrix of the target layer and the criterion layer, and lambdamaxThe maximum characteristic root of a judgment matrix of a target layer and a criterion layer is obtained, and x is n;
calculating lambdamax：
Figure BDA0003379290980000033
If CR is less than the set threshold, the judgment matrix passes the consistency check.
Preferably, the consistency check is performed according to the weight coefficients, including:
calculating CI and CR:
Figure BDA0003379290980000034
wherein, CI is the general consistency index of the judgment matrix of the index layer and the criterion layer, RI is the random consistency index of the judgment matrix of the index layer and the criterion layer, and lambdamaxThe judgment matrix is the maximum characteristic root of the judgment matrix of the index layer and the criterion layer, and x is h;
calculating lambdamax：
Figure BDA0003379290980000035
If CR is less than the set threshold, the judgment matrix passes the consistency check.
Preferably, the RI takes the values:
determining the order of the matrix 1 2 3 4 5 6 7 8 9 10
RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49
；
The value of CR is 0.1.
Preferentially, the target layer, the criterion layer and the index layer are subjected to priority ranking, and the highest correlation degree of the cause of the abnormal operation index of the power grid is obtained by screening, wherein the priority ranking comprises the following steps:
sorting the priority in descending order: a target layer, a criterion layer and an index layer;
sequentially obtaining the sum of the weights of all indexes in the target layer, the sum of the weights of all indexes in the criterion layer and the sum of the weights of all indexes in the index layer;
and screening the maximum value among the sum of the weights of all the indexes in the target layer, the sum of the weights of all the indexes in the criterion layer and the sum of the weights of all the indexes in the index layer to obtain the level with the maximum correlation degree of the cause of the abnormal operation index of the power grid.
Preferentially, the index of the target layer comprises the cause correlation degree of the abnormal index of the power grid operation;
the indexes of the criterion layer comprise adjusting capacity and steady-state operation capacity;
indexes of the index layer comprise primary frequency modulation capacity, AGC (automatic gain control) regulation capacity, voltage regulation capacity, section active power, line overload, main transformer overload, short-circuit current, bus voltage and power grid system frequency.
The invention achieves the following beneficial effects:
inputting a target layer to be verified and a criterion layer or the criterion layer and an index layer into a constructed judgment matrix; calculating a weight coefficient of the judgment matrix; performing consistency check according to the weight coefficient, if the consistency check is smaller than a set threshold value, judging that the judgment matrix passes the consistency check, otherwise, failing to pass the consistency check and ending the operation; carrying out priority arrangement on the target layer, the criterion layer and the index layer, screening to obtain a layer with the maximum correlation degree of the summary factor of the abnormal operation index of the power grid, realizing the evaluation of the correlation degree of the summary factor of the abnormal operation index of the power grid, and providing a reference basis for the priority of subsequent operation;
the invention aims to help a dispatcher to quickly locate the abnormal factors which have the largest influence on the power grid at present, so that the priority processing of key problems is facilitated, and the response speed and the efficiency of troubleshooting are improved.
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FIG. 1 is a flow chart of the present invention.
Detailed Description
The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
The method for determining the correlation degree of the cause of the abnormal index of the power grid operation based on the analytic hierarchy process aims to capture index factors influencing the power grid abnormality, and carries out cause attribution and weight sequencing on the influence factors based on the analytic hierarchy process so as to provide reference for subsequent scheduling operation. In the analysis process, the power grid can be regarded as a complex system which is formed by a plurality of factors which are mutually related and restricted and often lacks quantitative data, and the analytic hierarchy process provides a new, simple and practical modeling method for the decision and the sequencing of the multi-factor problems.
When the hierarchical analysis is applied to the decision-making of the problem, the problem is firstly organized and layered to construct a hierarchical structure model. Under this hierarchical model, the complex problem is decomposed into components of elements that, in turn, form several levels according to their attributes and relationships. The elements of the previous level are used as the criteria to dominate the elements of the next level. These hierarchies can be divided into three categories:
(i) the highest layer: there is only one element in this hierarchy, which is typically the intended target or desired result of the analysis problem, and is therefore also referred to as the target layer.
(ii) An intermediate layer: this level, which contains the intermediate links involved in achieving the goal, may consist of several levels, including criteria and sub-criteria to be considered, and is therefore also referred to as a criteria level.
(iii) The bottom layer: this level includes specific criteria that may be selected to achieve the goal and is therefore also referred to as an index layer or a solution layer.
Firstly, defining the category of the power grid operation indexes, and then carrying out hierarchical construction on the indexes, for example, selecting the regulation capacity and the steady-state operation capacity as models, wherein the hierarchical structure model mainly comprises a target layer, a criterion layer and an index layer. After the index system is constructed, the weight value of the post-evaluation index system of the power grid index needs to be calculated. The basic calculation principle is that various elements of the evaluation system scheme are decomposed into a plurality of layers to form a hierarchical structure model with ordered hierarchical order, and then every two comparison judgment is carried out on each element of each layer of the hierarchical structure model relative to a certain element of the previous layer, so as to calculate the weight of each element; and arranging according to the comprehensive weight coefficient, and positioning the optimal scheme according to the maximum weight principle.
1.1 building a hierarchical model
The step of S1 includes: and establishing a required hierarchical structure model, and taking the table 1 as an internal structure of the hierarchical structure model.
TABLE 1
Figure BDA0003379290980000051
1.2 construction of the decision matrix
The step of S2 includes: determining the judgment matrix of the target layer and the criterion layer and the judgment matrix of the criterion layer and the index layer, and aiming at each index a in the systemijComparing every two of the two parts respectively to form a judgment matrix A comprehensively:
establishing a judgment matrix between a target layer and a criterion layer:
Figure BDA0003379290980000061
in the formula: a isijTo measure the importance of the ith index of the target layer/criterion layer to the jth index of the target layer/criterion layer, i is the [1, n ]]，j∈[1,n]N is the sum of the number of indexes in the target layer and the number of indexes in the criterion layer;
aijfollowing a positive reciprocal matrix:
Figure BDA0003379290980000062
in the formula, ajiIs a value for measuring the importance of the jth index of the target layer/criterion layer to the ith index of the target layer/criterion layer.
aijAnd aefThe calculation mode adopts an AHP calculation rule formula in the prior art, and the embodiment is not described in detail.
Constructing a judgment matrix between the index layer and the criterion layer:
Figure BDA0003379290980000063
in the formula: a isefTo measure the importance of the e index of index layer/criterion layer to the f index of index layer/criterion layer, e belongs to [1, h]，f∈[1,h]H is the sum of the number of indexes in the index layer and the number of indexes in the criterion layer;
aeffollowing a positive reciprocal matrix:
Figure BDA0003379290980000064
in the formula, aefThe importance of the e index of the index layer/criterion layer to the f index of the index layer/criterion layer is measured.
1.3 weight calculation
According to the evaluation method for correlation degree of cause of abnormal operation index of power grid based on analytic hierarchy process in 1.2, the step S3 includes calculating a weight coefficient corresponding to the judgment matrix, specifically, calculating a weight w of an index j according to a root methodjComprises the following steps:
Figure BDA0003379290980000071
calculating the weight w of the index f according to the square root methodfComprises the following steps:
Figure BDA0003379290980000072
1.4 consistency test
According to the analytic hierarchy process-based power grid operation anomaly index cause correlation evaluation method in 1.3, the step S4 includes performing consistency check on the weight coefficients corresponding to the judgment matrix, and the calculation formula of the check result CR is as follows:
Figure BDA0003379290980000073
in the formula: CI is the general consistency index of the judgment matrix, RI is the random consistency index of the judgment matrix, lambdamaxTo judge the maximum characteristic root of the matrix, the calculation formula is as follows:
Figure BDA0003379290980000074
the RI value is an average random consistency index RI standard value in the AHP method, which is specifically shown in table 2:
TABLE 2 average random consistency index RI standard value
Order of matrix 1 2 3 4 5 6 7 8 9 10
RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49
According to the calculation result of CR, if CR is less than 0.1, the judgment matrix is judged to pass the consistency check, otherwise, the judgment matrix does not have satisfactory consistency.
1.5 weight permutation
Sorting the priority in descending order: a target layer, a criterion layer and an index layer;
according to 1.4, the step S5 includes integrating the arrangement of the weight coefficients, and calculating the weight of the relative importance of all the factors at a certain level, which is called total rank ordering, and this process is performed sequentially from the highest level to the lowest level. And positioning the index priority which has the largest influence on the power grid according to the arrangement result, namely the index with the largest cause correlation.
2. Analytic method result analysis of power grid operation index evaluation state hierarchy
According to the method for determining the cause correlation of the abnormal power grid operation index based on the analytic hierarchy process in 1.5, the weight arrangement sequence is known, and when the consistency test result is smaller, the cause correlation of the index to the abnormal power grid operation is larger. Therefore, in the process of scheduling, operating and operating the power grid, in order to accelerate the processing efficiency and shorten the corresponding time, the priority can be given to solving the abnormal index with large cause correlation according to the result.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.

Claims (10)

1. A power grid operation abnormity index cause correlation determination method based on an analytic hierarchy process is characterized by comprising the following steps:
inputting a target layer to be verified and a criterion layer, or the criterion layer and an index layer into a constructed judgment matrix;
calculating a weight coefficient of the judgment matrix;
performing consistency check according to the weight coefficient, if the consistency check is smaller than a set threshold value, judging that the judgment matrix passes the consistency check, otherwise, failing to pass the consistency check and ending the operation;
and carrying out priority arrangement on the target layer, the criterion layer and the index layer, and screening to obtain the layer with the maximum correlation degree of the cause of the abnormal operation index of the power grid.
2. The analytic hierarchy process-based power grid operation abnormity index cause correlation determination method according to claim 1, characterized in that a relation table between a target layer and a criterion layer is obtained according to an existing hierarchical structure model I;
and establishing a new hierarchical structure model II, and establishing a relation table between the index layer and the criterion layer.
3. The analytic hierarchy process-based power grid operation anomaly index cause correlation determination method according to claim 1, wherein constructing a judgment matrix comprises:
constructing a judgment matrix between a target layer and a criterion layer:
Figure FDA0003379290970000011
in the formula: a isijTo measure the importance of the ith index of the target layer/criterion layer to the jth index of the target layer/criterion layer, i is the [1, n ]]，j∈[1,n]N is the sum of the number of indexes in the target layer and the number of indexes in the criterion layer;
aijfollowing a positive reciprocal matrix:
Figure FDA0003379290970000012
in the formula, ajiFor measuring j index of target layer/criterion layer to target layer/criterion layerThe value of the importance of the i-th index.
4. The analytic hierarchy process-based power grid operation anomaly index cause correlation determination method according to claim 1, wherein constructing a judgment matrix comprises:
constructing a judgment matrix between the index layer and the criterion layer:
Figure FDA0003379290970000021
in the formula: a isefTo measure the importance of the e index of index layer/criterion layer to the f index of index layer/criterion layer, e belongs to [1, h]，f∈[1,h]H is the sum of the number of indexes in the index layer and the number of indexes in the criterion layer;
aeffollowing a positive reciprocal matrix:
Figure FDA0003379290970000022
in the formula, aefThe importance of the e index of the index layer/criterion layer to the f index of the index layer/criterion layer is measured.
5. The analytic hierarchy process-based power grid operation abnormality index cause correlation determination method according to claim 3, wherein calculating the weight coefficient of the determination matrix comprises:
calculating the jth index weight w according to a square root methodjComprises the following steps:
Figure FDA0003379290970000023
6. the analytic hierarchy process-based power grid operation anomaly index cause correlation determination method according to claim 4, wherein calculating the weight coefficient of the judgment matrix comprises:
calculating the f index weight w according to the square root methodfComprises the following steps:
Figure FDA0003379290970000024
7. the analytic hierarchy process-based power grid operation anomaly index cause correlation determination method according to claim 5, wherein the consistency check is performed according to a weight coefficient, and comprises:
calculating CI and CR:
Figure FDA0003379290970000025
wherein CI is the general consistency index of the judgment matrix of the target layer and the criterion layer, RI is the random consistency index of the judgment matrix of the target layer and the criterion layer, and lambdamaxThe maximum characteristic root of a judgment matrix of a target layer and a criterion layer is obtained, and x is n;
calculating lambdamax：
Figure FDA0003379290970000031
If CR is less than the set threshold, the judgment matrix passes the consistency check.
8. The analytic hierarchy process-based power grid operation abnormality index cause correlation determination method according to claim 1, wherein the cause correlation determination method comprises the following steps,
and performing consistency check according to the weight coefficient, wherein the consistency check comprises the following steps:
calculating CI and CR:
Figure FDA0003379290970000032
wherein, CI is the general consistency index of the judgment matrix of the index layer and the criterion layer, RI is the random consistency index of the judgment matrix of the index layer and the criterion layer, and lambdamaxThe judgment matrix is the maximum characteristic root of the judgment matrix of the index layer and the criterion layer, and x is h;
calculating lambdamax：
Figure FDA0003379290970000033
If CR is less than the set threshold, the judgment matrix passes the consistency check.
9. The analytic hierarchy process-based power grid operation anomaly index cause correlation determination method according to claim 6 or 7, wherein the RI takes values of:
determining the order of the matrix 1 2 3 4 5 6 7 8 9 10 RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49
；
The value of CR is 0.1.
10. The analytic hierarchy process-based power grid operation abnormality index cause correlation determination method according to claim 1, wherein the step of prioritizing the target layer, the criterion layer and the index layer and screening to obtain the maximum cause correlation of the power grid operation abnormality index includes:
sorting the priority in descending order: a target layer, a criterion layer and an index layer;
sequentially obtaining the sum of the weights of all indexes in the target layer, the sum of the weights of all indexes in the criterion layer and the sum of the weights of all indexes in the index layer;
and screening the maximum value among the sum of the weights of all the indexes in the target layer, the sum of the weights of all the indexes in the criterion layer and the sum of the weights of all the indexes in the index layer to obtain the level with the maximum correlation degree of the cause of the abnormal operation index of the power grid.
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Cited By (3)

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CN115061815A (en) * 2022-06-20 2022-09-16 北京计算机技术及应用研究所 Optimal scheduling decision method and system based on AHP
CN117150388A (en) * 2023-11-01 2023-12-01 江西现代职业技术学院 Abnormal state detection method and system for automobile chassis
CN117748596A (en) * 2024-02-20 2024-03-22 国网山西省电力公司晋中供电公司 Power grid dispatching method and device, storage medium and computer equipment

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115061815A (en) * 2022-06-20 2022-09-16 北京计算机技术及应用研究所 Optimal scheduling decision method and system based on AHP
CN115061815B (en) * 2022-06-20 2024-03-26 北京计算机技术及应用研究所 AHP-based optimal scheduling decision method and system
CN117150388A (en) * 2023-11-01 2023-12-01 江西现代职业技术学院 Abnormal state detection method and system for automobile chassis
CN117150388B (en) * 2023-11-01 2024-01-26 江西现代职业技术学院 Abnormal state detection method and system for automobile chassis
CN117748596A (en) * 2024-02-20 2024-03-22 国网山西省电力公司晋中供电公司 Power grid dispatching method and device, storage medium and computer equipment

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