CN111724071A - TOPSIS method-based intelligent box-type substation operation state evaluation method - Google Patents
TOPSIS method-based intelligent box-type substation operation state evaluation method Download PDFInfo
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Abstract
The application discloses intelligent box-type substation operation state evaluation method based on TOPSIS method includes: constructing a decision matrix according to each evaluation index of the intelligent box-type substation; constructing a weighted decision matrix by using an analytic hierarchy process according to the decision matrix; analyzing the weighted decision matrix by adopting a TOPSIS method to obtain the health state estimation value of the intelligent box-type substation; and comparing the health state estimated value of the intelligent box-type substation with the health state grade classification table of the intelligent box-type substation to obtain the health state of the intelligent box-type substation. The method can efficiently and reliably evaluate the overall health state of the intelligent box-type substation, and is convenient for operation and maintenance personnel to know the condition of the intelligent box-type substation in operation. The application also discloses a TOPSIS method-based intelligent box-type substation operation state evaluation device, equipment and a computer-readable storage medium, and the device and the equipment have the technical effects.
Description
Technical Field
The application relates to the technical field of intelligent box-type substations, in particular to a TOPSIS method-based intelligent box-type substation operation state evaluation method; the TOPSIS method-based intelligent box-type substation operation state evaluation device, equipment and computer readable storage medium are also provided.
Background
With the continuous development of human society, the power industry enters the information-based era, and the intelligent box-type substation plays an important role therein. The intelligent transmission node is used as an important transmission node deep into a load center in a power distribution network, and is particularly critical for intelligent and informationized operation and maintenance management of an intelligent box-type substation.
At present, most of research on state evaluation of the intelligent box-type substation focuses on single equipment or a certain state of the intelligent box-type substation, and the research on the state evaluation of the whole box-type substation is less. However, in view of the distribution of the current intelligent box-type substations, operation and maintenance personnel need to more comprehensively grasp the operation conditions of the intelligent box-type substations in different regions. By combining the characteristics of intellectualization and informatization of the current intelligent box-type substation, operation and maintenance personnel can master various state data of the intelligent box-type substation in real time through an operation and maintenance system of the intelligent box-type substation, and abundant intelligent box-type substation data are favorable for realizing the overall health state assessment of the intelligent box-type substation. In order to make full use of various state data of the intelligent box-type substation and enable operation and maintenance personnel to master the health state of the intelligent box-type substation more comprehensively, an evaluation method of the intelligent box-type substation with high efficiency and reliable evaluation results is needed.
Therefore, providing an evaluation method for an intelligent box-type substation with high implementation efficiency and reliable evaluation results has become a technical problem to be solved by those skilled in the art.
Disclosure of Invention
The application aims to provide an intelligent box-type substation operation state assessment method based on the TOPSIS method, which can efficiently and reliably assess the overall health state of the intelligent box-type substation, and is convenient for operation and maintenance personnel to know the condition of the intelligent box-type substation in operation so as to timely process health problems occurring in the intelligent box-type substation. Another object of the present application is to provide an intelligent substation operation state evaluation device, equipment and computer readable storage medium based on the TOPSIS method, all of which have the above technical effects.
In order to solve the technical problem, the application provides an intelligent box-type substation operation state evaluation method based on a TOPSIS method, which comprises the following steps:
constructing a decision matrix according to each evaluation index of the intelligent box-type substation;
constructing a weighted decision matrix by using an analytic hierarchy process according to the decision matrix;
analyzing the weighted decision matrix by adopting a TOPSIS method to obtain the health state estimation value of the intelligent box-type substation;
and comparing the health state estimated value of the intelligent box-type substation with the health state grade classification table of the intelligent box-type substation to obtain the health state of the intelligent box-type substation.
Optionally, the evaluation index includes an operating parameter and an environmental parameter of electrical equipment in a high-voltage chamber, a low-voltage chamber and a transformer chamber of the intelligent box-type substation.
Optionally, before constructing the weighted decision matrix by using an analytic hierarchy process according to the decision matrix, the method further includes:
carrying out dimensionless processing on the decision matrix to obtain a normalized decision matrix;
correspondingly, the constructing a weighted decision matrix by using an analytic hierarchy process according to the decision matrix comprises:
and constructing the weighting decision matrix by using an analytic hierarchy process according to the normalized decision matrix.
Optionally, the performing dimensionless processing on the decision matrix to obtain a normalized decision matrix includes:
according to the formula
Performing non-dimensionalization on the decision matrix, or according to a formula
Carrying out dimensionless processing on the decision matrix;
wherein v isijProcessing value, x, of the jth evaluation index for the ith evaluation objectijThe original value of the j-th evaluation index as the ith evaluation object. min (x)j) Is the minimum value of the jth evaluation index, max (x)j) Is the maximum value of the j-th evaluation index.
Optionally, the constructing the weighted decision matrix according to the normalized decision matrix by using an analytic hierarchy process includes:
taking an intelligent box-type substation as a target layer, taking a high-voltage chamber, a transformer chamber and a low-voltage chamber as a criterion layer, taking the operation parameters and the environmental parameters of electrical equipment as index layers, and establishing a comparison matrix for pairwise comparison of the evaluation indexes in the same layer;
solving to obtain a maximum characteristic root of the comparison matrix, and calculating to obtain a characteristic vector corresponding to the maximum characteristic root;
normalizing the feature vector to obtain a weight vector;
calculating the weight of the importance of each evaluation index in the index layer relative to the target layer;
and multiplying the weight by the normalized decision matrix to obtain the weighted decision matrix.
Optionally, the analyzing the weighted decision matrix by using a TOPSIS method to obtain the health status estimation value of the intelligent box-type substation includes:
searching an optimal value of each row and a worst value of each row in the weighting decision matrix, obtaining an optimal solution vector according to the optimal value, and obtaining a worst solution vector according to the worst value;
and respectively calculating Euclidean distances between each intelligent box-type substation and the optimal vector and between each intelligent box-type substation and the worst vector, and obtaining the health state estimated value of the intelligent box-type substation according to the Euclidean distances.
In order to solve the technical problem, the application further provides an intelligent box-type substation operation state evaluation device based on the TOPSIS method, which comprises:
the first construction module is used for constructing a decision matrix according to each evaluation index of the intelligent box-type substation;
the second construction module is used for constructing a weighted decision matrix by using an analytic hierarchy process according to the decision matrix;
the analysis module is used for analyzing the weighted decision matrix by adopting a TOPSIS method to obtain the health state estimation value of the intelligent box-type substation;
and the comparison module is used for comparing the health state estimated value of the intelligent box-type substation with the health state grade classification table of the intelligent box-type substation to obtain the health state of the intelligent box-type substation.
Optionally, the method further includes:
the non-dimensionalization processing module is used for carrying out non-dimensionalization processing on the decision matrix to obtain a normalized decision matrix;
correspondingly, the second construction module is specifically configured to construct the weighted decision matrix by using an analytic hierarchy process according to the normalized decision matrix.
In order to solve the technical problem, the application further provides an intelligent box-type substation operation state evaluation device based on the TOPSIS method, which comprises:
a memory for storing a computer program;
and the processor is used for realizing the steps of the intelligent box-type substation operation state evaluation method based on the TOPSIS method when executing the computer program.
In order to solve the technical problem, the present application further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the steps of the method for evaluating the operating state of the intelligent box-type substation based on the TOPSIS method are implemented.
The application provides a TOPSIS method-based intelligent box-type substation operation state evaluation method, including: constructing a decision matrix according to each evaluation index of the intelligent box-type substation; constructing a weighted decision matrix by using an analytic hierarchy process according to the decision matrix; analyzing the weighted decision matrix by adopting a TOPSIS method to obtain the health state estimation value of the intelligent box-type substation; and comparing the health state estimated value of the intelligent box-type substation with the health state grade classification table of the intelligent box-type substation to obtain the health state of the intelligent box-type substation.
Therefore, the TOPSIS method-based intelligent box-type substation operation state evaluation method is based on the TOPSIS method, the decision matrix is constructed according to each evaluation index of the intelligent box-type substation, the TOPSIS method is adopted for analysis, and the health state of the intelligent box-type substation is obtained, so that operation and maintenance personnel can know the state of the whole intelligent box-type substation and the state of each part in operation in real time, and the overhaul, maintenance and arrangement of the intelligent box-type substation and the establishment of a health report are conveniently completed.
The intelligent box-type substation operation state evaluation device based on the TOPSIS method, equipment and computer readable storage medium have the technical effects.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the prior art and the embodiments are briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic flow chart of an intelligent box-type substation operation state evaluation method based on the TOPSIS method according to an embodiment of the present application;
fig. 2 is a schematic diagram of an intelligent substation operating state evaluation device based on the TOPSIS method according to an embodiment of the present application;
fig. 3 is a schematic diagram of an intelligent substation operating state evaluation device based on the TOPSIS method according to an embodiment of the present application.
Detailed Description
The core of the application is to provide an intelligent box-type substation operation state assessment method based on the TOPSIS method, which can efficiently and reliably assess the overall health state of the intelligent box-type substation, and is convenient for operation and maintenance personnel to know the condition of the intelligent box-type substation in operation so as to timely process the health problems occurring in the intelligent box-type substation. The other core of the application is to provide the intelligent box-type substation operation state evaluation device, equipment and computer readable storage medium based on the TOPSIS method, which have the technical effects.
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Referring to fig. 1, fig. 1 is a schematic flow chart of a method for evaluating an operating state of an intelligent box-type substation based on a TOPSIS method according to an embodiment of the present application, and referring to fig. 1, the method includes:
s101: constructing a decision matrix according to each evaluation index of the intelligent box-type substation;
specifically, the method aims to construct a decision matrix according to the multi-type evaluation indexes of the intelligent box-type substation. The evaluation indexes of the intelligent box-type substation comprise operating parameters and environmental parameters of electrical equipment of a high-voltage chamber, a low-voltage chamber and a transformer chamber of the intelligent box-type substation. Specifically, the operating parameters and environmental parameters of the electrical equipment in the high-voltage chamber may include environmental temperature and humidity, temperature of key parts, partial discharge, and power factors; the operation parameters and environmental parameters of the electrical equipment in the low-voltage chamber can comprise environmental temperature and humidity, three-phase voltage, three-phase current and harmful gas; the operating and environmental parameters of the electrical equipment of the transformer room may include the temperature of the underlying oil, the insulating oil medium, vibration harmonics, and the temperature rise of the partial discharge winding.
The decision matrix X constructed is as follows:
wherein M isiIs a specific intelligent box-type substation in the area, namely an evaluation object DjFor the evaluation index of the intelligent box-type substation, for a specific intelligent box-type substation MiEvaluation index D thereofjIs denoted as xij(i＝1,2…,m；j＝1,2…,n)。
S102: constructing a weighted decision matrix by using an analytic hierarchy process according to the decision matrix;
specifically, this step is intended to construct a weighted decision matrix based on the decision matrix.
In a specific embodiment, before constructing the weighted decision matrix by using the analytic hierarchy process according to the decision matrix, the method further comprises: carrying out dimensionless processing on the decision matrix to obtain a normalized decision matrix; correspondingly, according to the decision matrix, constructing the weighted decision matrix by using an analytic hierarchy process comprises the following steps: and constructing a weighted decision matrix by using an analytic hierarchy process according to the normalized decision matrix.
Wherein, the performing dimensionless processing on the decision matrix to obtain a normalized decision matrix includes: according to the formula
Performing non-dimensionalization on the decision matrix, or according to a formula
Carrying out dimensionless processing on the decision matrix; wherein v isijThe processing value, x, of the j index of the i evaluation objectijIs the original value of the j index of the ith evaluation object. min (x)j) Is the minimum value of the j-th index, max (x)j) Is the maximum value of the j index.
Specifically, the more preferable index is larger and more preferable, the formula is followed
Performing dimensionless treatment, and optimizing the index according to formula
And carrying out dimensionless treatment.
In addition, the constructing the weighted decision matrix according to the normalized decision matrix by using an analytic hierarchy process includes: taking an intelligent box-type substation as a target layer, taking a high-voltage chamber, a transformer chamber and a low-voltage chamber as a criterion layer, taking the operation parameters and the environmental parameters of electrical equipment as index layers, and establishing a comparison matrix for pairwise comparison of the evaluation indexes in the same layer; solving to obtain a maximum characteristic root of the comparison matrix, and calculating to obtain a characteristic vector corresponding to the maximum characteristic root; normalizing the feature vector to obtain a weight vector; calculating the weight of the importance of each evaluation index in the index layer relative to the target layer; and multiplying the weight by the normalized decision matrix to obtain the weighted decision matrix.
Specifically, the final purpose of the method is to determine the operation state of the intelligent box-type substation, so that the whole intelligent box-type substation is used as a target layer; since a box substation generally comprises three parts: high-voltage chamber, low-voltage chamber and transformer chamber, so the high-voltage chamber, low-voltage chamber and transformer chamber are used as the standard layers; and the operating parameters and the environmental parameters of the electrical equipment in the criterion layer are used as an index layer. Establishing an n x n comparison matrix A for pairwise comparison of evaluation indexes in the same level (including index level and criterion level):
in the formula: a represents a comparison matrix formed by integrating the T expert opinions, AkFor comparison matrices formed on the basis of the k-th expert opinion, aijRepresenting the importance degree of the ith index relative to the jth index; the value on the main diagonal is constant at 1.
Further, solving the characteristic root | λ E-A | ═ 0 of each comparison matrix, and solving to obtain the maximum characteristic root λ of the comparison matrixmax；|A-λmaxObtaining a corresponding characteristic vector after E | x is 0, and obtaining a weight vector of the index after normalization processing;
further, calculating the weight of the relative importance of all evaluation indexes of the index layer to the target layer:
wj＝wi0wij；
the operation parameters and the environmental parameters of the electrical equipment of the high-voltage chamber comprise environment temperature and humidity, temperature of key parts, partial discharge and power factors, the operation parameters and the environmental parameters of the electrical equipment of the low-voltage chamber can comprise environment temperature and humidity, three-phase voltage, three-phase current and harmful gas, the operation parameters and the environmental parameters of the electrical equipment of the transformer chamber can comprise the conditions of bottom layer oil temperature, insulating oil medium, vibration harmonic wave and partial discharge winding temperature rise, wherein in the formula, i ∈ {1,2,3}, j ∈ {1,2, …,12}, w < w > is defined asjWeight of each index of the layer to the target layer, wi0Weight, w, representing the criterion layer calculated in the preceding stepijRepresenting a preceding step calculationAnd obtaining the weight of the index layer.
Further, the weights are multiplied by the matrix subjected to the dimensionless process to obtain a weighted decision matrix R ═ R (R)ij)m×n，rij＝wj·vij(i＝1,2,…,m；j＝1,2,…,n)。
S103: analyzing the weighted decision matrix by adopting a TOPSIS method to obtain the health state estimation value of the intelligent box-type substation;
specifically, after the construction of the weighted decision matrix is completed, the weighted decision matrix is further analyzed by adopting a TOPSIS method to obtain the health state estimation value of the intelligent box-type substation.
Wherein, the above-mentioned adoption TOPSIS method analysis weighting decision matrix obtains intelligent box-type substation's health status valuation, includes: searching the optimal value of each row and the worst value of each row in the weighting decision matrix, obtaining an optimal solution vector according to the optimal value, and obtaining a worst solution vector according to the worst value; and respectively calculating Euclidean distances between each intelligent box-type substation and the optimal vector and between each intelligent box-type substation and the worst vector, and obtaining a health state estimated value of the intelligent box-type substation according to the Euclidean distances.
Specifically, find the optimal value for each column as ri *The worst value of each column is recorded as ri -Then, then
In order to obtain the optimal solution vector, the method comprises the following steps of,
is the worst solution vector; calculating Euclidean distances between each intelligent box-type substation, namely an evaluation object, and the optimal vector and the worst vector;
in the formula (I), the compound is shown in the specification,
the Euclidean distance between the ith evaluation object and the optimal solution,
the Euclidean distance between the ith evaluation object and the worst solution;
further, calculating the relative closeness of each evaluation object to the optimal solution and the worst solution;
according to relative closeness ciRanking the evaluation objects, ciThe larger the evaluation target, the more preferable the evaluation target. c. CiNamely the health state estimation of the intelligent box-type substation.
S104: and comparing the health state estimated value of the intelligent box-type substation with the health state grade classification table of the intelligent box-type substation to obtain the health state of the intelligent box-type substation.
Specifically, the health state estimation value of the intelligent box-type substation is compared with the health state grade classification table of the intelligent box-type substation, so that the health state of the intelligent box-type substation is obtained. As shown in table 1:
TABLE 1 Intelligent box type substation Normal State class Classification Table
If the health state estimation value of the intelligent box-type substation is between 0.9 and 1.0, outputting the result that the intelligent box-type substation is in a normal state; if the health state of the intelligent box-type substation is between 0.8 and 0.9, informing operation and maintenance personnel of the result that the intelligent box-type substation is in the attention state so that the operation and maintenance personnel can carry out enhanced inspection on the intelligent box-type substation; if the health state of the intelligent box-type substation is between 0.6 and 0.8, informing operation and maintenance personnel to carry out maintenance as soon as possible; and if the health state of the intelligent box-type substation is between 0 and 0.6, informing operation and maintenance personnel to maintain the intelligent box-type substation immediately.
In summary, the method for evaluating the operating state of the intelligent box-type substation based on the TOPSIS method provided by the application comprises the following steps: constructing a decision matrix according to each evaluation index of the intelligent box-type substation; constructing a weighted decision matrix by using an analytic hierarchy process according to the decision matrix; analyzing the weighted decision matrix by adopting a TOPSIS method to obtain the health state estimation value of the intelligent box-type substation; and comparing the health state estimated value of the intelligent box-type substation with the health state grade classification table of the intelligent box-type substation to obtain the health state of the intelligent box-type substation. The method is based on a TOPSIS method, a decision matrix is constructed according to each evaluation index of the intelligent box-type substation, and the TOPSIS method is adopted for analysis to obtain the health state of the intelligent box-type substation, so that operation and maintenance personnel can know the state of the whole intelligent box-type substation and the states of all parts in operation in real time, and the overhaul, maintenance and arrangement of the intelligent box-type substation and the establishment of a health report are conveniently completed.
The application also provides an intelligent box-type substation operation state evaluation device based on the TOPSIS method, and the device described below can be correspondingly referred to with the method described above. Referring to fig. 2, fig. 2 is a schematic diagram of an intelligent substation operating state evaluation apparatus based on the TOPSIS method according to an embodiment of the present application, and referring to fig. 2, the apparatus includes:
the first construction module 10 is used for constructing a decision matrix according to each evaluation index of the intelligent box-type substation;
a second constructing module 20, configured to construct a weighted decision matrix by using an analytic hierarchy process according to the decision matrix;
the analysis module 30 is configured to analyze the weighted decision matrix by using a TOPSIS method to obtain an estimated value of the health state of the intelligent box-type substation;
and the comparison module 40 is used for comparing the health state estimated value of the intelligent box-type substation with the health state grade classification table of the intelligent box-type substation to obtain the health state of the intelligent box-type substation.
On the basis of the above embodiments, as a specific implementation manner, the evaluation index includes an operation parameter and an environmental parameter of electrical equipment of a high-voltage chamber, a low-voltage chamber and a transformer chamber of the intelligent box-type substation.
On the basis of the above embodiment, optionally, the method further includes:
the non-dimensionalization processing module is used for carrying out non-dimensionalization processing on the decision matrix to obtain a normalized decision matrix;
correspondingly, the second constructing module 20 is specifically configured to construct the weighted decision matrix by using an analytic hierarchy process according to the normalized decision matrix.
On the basis of the foregoing embodiment, optionally, the non-dimensionalization processing module is specifically configured to:
according to the formula
Performing non-dimensionalization on the decision matrix, or according to a formula
Carrying out dimensionless processing on the decision matrix;
wherein v isijProcessing value, x, of the jth evaluation index for the ith evaluation objectijThe original value of the j-th evaluation index as the ith evaluation object. min (x)j) Is the minimum value of the jth evaluation index, max (x)j) Is the maximum value of the j-th evaluation index.
On the basis of the above embodiment, the second construction module 20 includes:
the comparison matrix establishing unit is used for establishing a comparison matrix for pairwise comparison of the evaluation indexes in the same level by taking the intelligent box-type substation as a target layer, taking the high-voltage chamber, the transformer chamber and the low-voltage chamber as a criterion layer, taking the operation parameters and the environmental parameters of the electrical equipment as index layers;
the first calculation unit is used for solving to obtain a maximum characteristic root of the comparison matrix and calculating to obtain a characteristic vector corresponding to the maximum characteristic root;
the normalization processing unit is used for performing normalization processing on the feature vector to obtain a weight vector;
a second calculating unit, configured to calculate a weight of importance of each of the evaluation indicators in the indicator layer with respect to the target layer;
and the third calculating unit is used for multiplying the weight by the normalized decision matrix to obtain the weighted decision matrix.
On the basis of the above embodiment, optionally, the analysis module 30 includes:
the searching unit is used for searching the optimal value of each row and the worst value of each row in the weighting decision matrix, obtaining an optimal solution vector according to the optimal value and obtaining a worst solution vector according to the worst value;
and the calculation unit is used for calculating Euclidean distances between each intelligent box-type substation and the optimal vector and between each intelligent box-type substation and the worst vector respectively, and obtaining the health state estimated value of the intelligent box-type substation according to the Euclidean distances.
The application also provides intelligent box-type substation operation state evaluation equipment based on the TOPSIS method, and the equipment comprises a memory 1 and a processor 2, which are shown in a reference figure 3.
A memory 1 for storing a computer program;
a processor 2 for executing a computer program to implement the steps of:
constructing a decision matrix according to each evaluation index of the intelligent box-type substation; constructing a weighted decision matrix by using an analytic hierarchy process according to the decision matrix; analyzing the weighted decision matrix by adopting a TOPSIS method to obtain the health state estimation value of the intelligent box-type substation; and comparing the health state estimated value of the intelligent box-type substation with the health state grade classification table of the intelligent box-type substation to obtain the health state of the intelligent box-type substation.
For the introduction of the device provided in the present application, please refer to the above method embodiment, which is not described herein again.
The present application further provides a computer readable storage medium having a computer program stored thereon, which when executed by a processor, performs the steps of:
constructing a decision matrix according to each evaluation index of the intelligent box-type substation; constructing a weighted decision matrix by using an analytic hierarchy process according to the decision matrix; analyzing the weighted decision matrix by adopting a TOPSIS method to obtain the health state estimation value of the intelligent box-type substation; and comparing the health state estimated value of the intelligent box-type substation with the health state grade classification table of the intelligent box-type substation to obtain the health state of the intelligent box-type substation.
The computer-readable storage medium may include: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
For the introduction of the computer-readable storage medium provided in the present application, please refer to the above method embodiments, which are not described herein again.
The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device, the apparatus and the computer-readable storage medium disclosed by the embodiments correspond to the method disclosed by the embodiments, so that the description is simple, and the relevant points can be referred to the description of the method.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The method, the device, the equipment and the computer readable storage medium for evaluating the operating state of the intelligent box-type substation based on the TOPSIS method provided by the application are described in detail above. The principles and embodiments of the present application are explained herein using specific examples, which are provided only to help understand the method and the core idea of the present application. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and such improvements and modifications also fall within the scope of the claims of the present application.
Claims (10)
1. A TOPSIS method-based intelligent box-type substation operation state assessment method is characterized by comprising the following steps:
constructing a decision matrix according to each evaluation index of the intelligent box-type substation;
constructing a weighted decision matrix by using an analytic hierarchy process according to the decision matrix;
analyzing the weighted decision matrix by adopting a TOPSIS method to obtain the health state estimation value of the intelligent box-type substation;
and comparing the health state estimated value of the intelligent box-type substation with the health state grade classification table of the intelligent box-type substation to obtain the health state of the intelligent box-type substation.
2. The intelligent substation cabinet operation state evaluation method according to claim 1, wherein the evaluation index includes electrical equipment operation parameters and environmental parameters of a high-voltage chamber, a low-voltage chamber and a transformer chamber of the intelligent substation cabinet.
3. The method for evaluating the operation state of the intelligent box-type substation according to claim 2, wherein before constructing the weighted decision matrix by using an analytic hierarchy process according to the decision matrix, the method further comprises the following steps:
carrying out dimensionless processing on the decision matrix to obtain a normalized decision matrix;
correspondingly, the constructing a weighted decision matrix by using an analytic hierarchy process according to the decision matrix comprises:
and constructing the weighting decision matrix by using an analytic hierarchy process according to the normalized decision matrix.
4. The method for evaluating the operating state of the intelligent box-type substation according to claim 3, wherein the non-dimensionalizing the decision matrix to obtain a normalized decision matrix comprises:
according to the formula
Performing non-dimensionalization on the decision matrix, or according to a formula
Carrying out dimensionless processing on the decision matrix;
wherein v isijProcessing value, x, of the jth evaluation index for the ith evaluation objectijThe original value of the j-th evaluation index as the ith evaluation object. min (x)j) Is the minimum value of the jth evaluation index, max (x)j) Is the maximum value of the j-th evaluation index.
5. The method for evaluating the operating state of the intelligent box-type substation according to claim 4, wherein the constructing the weighted decision matrix by using an analytic hierarchy process according to the normalized decision matrix comprises:
taking an intelligent box-type substation as a target layer, taking a high-voltage chamber, a transformer chamber and a low-voltage chamber as a criterion layer, taking the operation parameters and the environmental parameters of electrical equipment as index layers, and establishing a comparison matrix for pairwise comparison of the evaluation indexes in the same layer;
solving to obtain a maximum characteristic root of the comparison matrix, and calculating to obtain a characteristic vector corresponding to the maximum characteristic root;
normalizing the feature vector to obtain a weight vector;
calculating the weight of the importance of each evaluation index in the index layer relative to the target layer;
and multiplying the weight by the normalized decision matrix to obtain the weighted decision matrix.
6. The method for assessing the operational status of an intelligent substation cabinet according to claim 5, wherein the analyzing the weighted decision matrix using TOPSIS to obtain the health status estimate of the intelligent substation cabinet comprises:
searching an optimal value of each row and a worst value of each row in the weighting decision matrix, obtaining an optimal solution vector according to the optimal value, and obtaining a worst solution vector according to the worst value;
and respectively calculating Euclidean distances between each intelligent box-type substation and the optimal vector and between each intelligent box-type substation and the worst vector, and obtaining the health state estimated value of the intelligent box-type substation according to the Euclidean distances.
7. The utility model provides an intelligent box-type substation running state evaluation device based on TOPSIS method which characterized in that includes:
the first construction module is used for constructing a decision matrix according to each evaluation index of the intelligent box-type substation;
the second construction module is used for constructing a weighted decision matrix by using an analytic hierarchy process according to the decision matrix;
the analysis module is used for analyzing the weighted decision matrix by adopting a TOPSIS method to obtain the health state estimation value of the intelligent box-type substation;
and the comparison module is used for comparing the health state estimated value of the intelligent box-type substation with the health state grade classification table of the intelligent box-type substation to obtain the health state of the intelligent box-type substation.
8. The intelligent box-type substation operation state evaluation device of claim 7, further comprising:
the non-dimensionalization processing module is used for carrying out non-dimensionalization processing on the decision matrix to obtain a normalized decision matrix;
correspondingly, the second construction module is specifically configured to construct the weighted decision matrix by using an analytic hierarchy process according to the normalized decision matrix.
9. The utility model provides an intelligent box-type substation running state evaluation equipment based on TOPSIS method which characterized in that includes:
a memory for storing a computer program;
a processor for implementing the steps of the TOPSIS method-based intelligent substation operating state assessment method according to any one of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, implements the steps of the TOPSIS method-based intelligent substation operational state assessment method according to any one of claims 1 to 6.
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