CN116341992A - Comprehensive evaluation method and device for power distribution network, electronic equipment and storage medium - Google Patents
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Abstract
The invention discloses a comprehensive evaluation method, a comprehensive evaluation device, electronic equipment and a storage medium for a power distribution network, which are used for solving the technical problems that misjudgment is easy to generate or important factors are ignored or weight coefficient distribution errors occur in the existing comprehensive evaluation work of the power distribution network. The invention comprises the following steps: acquiring an evaluation index of the power distribution network; checking the evaluation index to obtain a check index; calculating the relative importance degree among the check indexes, and calculating the subjective weight of the check indexes according to the relative importance degree; calculating the objective weight of the check index; combining the subjective weight and the objective weight to generate a combined weight of the check index; and obtaining the score of each check index, and carrying out comprehensive evaluation on the power distribution network according to the combination weight of each check index and the corresponding score to obtain an evaluation result.
Description
Technical Field
The invention relates to the technical field of power distribution networks, in particular to a comprehensive evaluation method and device for a power distribution network, electronic equipment and a storage medium.
Background
With the change of power transmission and distribution prices and the continuous promotion of 'double carbon' targets, the power distribution network gradually becomes an investment construction focus. The method has the advantages that higher requirements and standards are provided for the investment evaluation of the power distribution network, but the current investment evaluation of the power distribution network has the problems of numerous projects, difficulty in benefit quantification, poor descriptive structure and the like, and the evaluation optimization method is single, so that the conditions of human intervention and low decision efficiency exist.
The conventional comprehensive evaluation method of the power distribution network comprises an analytic hierarchy process, an entropy weight process and a CRITIC process:
analytical hierarchy process: the subjective weighting method is characterized in that the basic idea is to hierarchy the complex problem, split the problem into a plurality of layers, and divide the problem into a target layer, a criterion layer and a scheme layer from top to bottom. And determining a judgment matrix and a weight coefficient between layers by making a hierarchical structure and utilizing expert knowledge and experience, and finally obtaining the comprehensive evaluation value of each scheme, and making a decision based on the comprehensive evaluation value.
Entropy weight method: the objective weighting method is a weight determining method based on information entropy, and the basic idea is to determine the weight coefficient according to the information entropy of each attribute index, namely, the larger the information entropy is, the smaller the weight coefficient is.
CRITIC method: the objective weighting method is used for calculating the interrelationship between different attributes, thereby determining the importance weight of each attribute. The calculation method is similar to the entropy weighting method, is an objective weighting method, and is characterized in that the correlation among indexes, namely the variability and the conflict among the indexes are determined to analyze and evaluate a decision scheme.
However, the conventional subjective weighting method relies on subjective judgment and personal preference of an expert, is complex in calculation, has the problem of subjectivity of weighting, and can generate misjudgment or neglect important factors, so that the implementation effect of the scheme is not ideal. The objective weighting method is affected by the data samples, and the situation of weight coefficient distribution errors is easy to occur when the data samples are fewer.
Disclosure of Invention
The invention provides a comprehensive evaluation method, a comprehensive evaluation device, electronic equipment and a storage medium for a power distribution network, which are used for solving the technical problems that misjudgment is easy to generate or important factors are ignored or weight coefficient distribution errors occur in the existing comprehensive evaluation work of the power distribution network.
The invention provides a comprehensive evaluation method of a power distribution network, which comprises the following steps:
acquiring an evaluation index of the power distribution network;
checking the evaluation index to obtain a check index;
calculating the relative importance degree among the check indexes, and calculating the subjective weight of the check indexes according to the relative importance degree;
calculating the objective weight of the check index;
combining the subjective weight and the objective weight to generate a combined weight of the check index;
and obtaining the score of each check index, and carrying out comprehensive evaluation on the power distribution network according to the combination weight of each check index and the corresponding score to obtain an evaluation result.
Optionally, the step of verifying the evaluation index to obtain a verification index includes:
acquiring the number of the evaluation indexes and the evaluation score of each evaluation index;
calculating a credibility coefficient according to the number of the evaluation indexes and the evaluation score;
when the credibility coefficient reaches a preset credibility threshold, calculating the validity coefficient of the evaluation index;
and taking an evaluation index of which the effectiveness coefficient reaches a preset effectiveness threshold as a check index.
Optionally, the relative importance levels include a first relative importance level and a second relative importance level; the step of calculating the relative importance degree among the check indexes and calculating the subjective weight of the check indexes according to the relative importance degree comprises the following steps:
determining an optimal index and a worst index in the check indexes;
calculating a first relative importance degree between the optimal index and each check index;
calculating a second relative importance between each of the verification indexes and the worst indexes;
and calculating subjective weight of each check index according to the first relative importance degree and the second relative importance degree.
Optionally, the step of calculating the objective weight of the check index includes:
normalizing the check index to obtain a normalized index;
calculating index variability of each normalized index according to the optimal index and the worst index;
acquiring the data information quantity of each normalized index, and calculating the index conflict of each normalized index according to the data information quantity and the index variability;
and calculating the objective weight of each normalized index according to the index conflict.
Optionally, the step of generating the combination weight of the verification indicator according to the subjective weight and the objective weight includes:
calculating the relative entropy of the subjective weight and the objective weight;
and calculating the combination weight of the check index according to the relative entropy.
The invention also provides a comprehensive evaluation device of the power distribution network, which comprises:
the evaluation index acquisition module is used for acquiring the evaluation index of the power distribution network;
the verification module is used for verifying the evaluation index to obtain a verification index;
the subjective weight calculation module is used for calculating the relative importance degree among the check indexes and calculating the subjective weight of the check indexes according to the relative importance degree;
the objective weight calculation module is used for calculating the objective weight of the check index;
the combination weight generation module is used for combining the subjective weight and the objective weight to generate the combination weight of the check index;
and the evaluation module is used for acquiring the scores of the check indexes, and carrying out comprehensive evaluation on the power distribution network according to the combination weights of the check indexes and the corresponding scores to obtain an evaluation result.
Optionally, the verification module includes:
the number and evaluation score acquisition sub-module is used for acquiring the number of the evaluation indexes and the evaluation score of each evaluation index;
the credibility coefficient calculation sub-module is used for calculating a credibility coefficient according to the number of the evaluation indexes and the evaluation score;
the validity coefficient calculation sub-module is used for calculating the validity coefficient of the evaluation index when the credibility coefficient reaches a preset credibility threshold;
and the verification index generation sub-module is used for taking an evaluation index with the effectiveness coefficient reaching a preset effectiveness threshold as a verification index.
Optionally, the relative importance levels include a first relative importance level and a second relative importance level; the subjective weight calculation module comprises:
the optimal index and the worst index determining submodule is used for determining an optimal index and a worst index in the check indexes;
a first relative importance degree calculating sub-module, configured to calculate a first relative importance degree between the optimal index and each of the check indexes;
a second relative extent calculation sub-module for calculating a second relative extent between each of the check indicators and the worst indicator;
and the subjective weight calculation sub-module is used for calculating the subjective weight of each check index according to the first relative importance degree and the second relative importance degree.
The invention also provides an electronic device comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute the comprehensive evaluation method for the power distribution network according to any one of the above instructions in the program code.
The invention also provides a computer readable storage medium for storing program code for performing the comprehensive evaluation method of a power distribution network as described in any one of the above.
From the above technical scheme, the invention has the following advantages: the invention discloses a comprehensive evaluation method of a power distribution network, which comprises the following steps: acquiring an evaluation index of the power distribution network; checking the evaluation index system to obtain a check index; calculating the relative importance degree among the check indexes, and calculating the subjective weight of the check indexes according to the relative importance degree; calculating the objective weight of the check index; combining the subjective weight and the objective weight to generate a combined weight of the check index; and obtaining the score of each check index, and carrying out comprehensive evaluation on the power distribution network according to the combination weight of each check index and the corresponding score to obtain an evaluation result.
The invention adopts subjective weighting and objective weighting to weight the check index, thereby reducing subjectivity and uncertainty of a single weighting method and improving accuracy and reliability of weighting results. Meanwhile, the situation that the weighting effect difference of different weighting methods on different evaluation indexes is large is avoided, and the accuracy of the relative weights of the evaluation indexes in comprehensive evaluation is ensured.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained from these drawings without inventive faculty for a person skilled in the art.
Fig. 1 is a flowchart of steps of a comprehensive evaluation method for a power distribution network according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of secondary indicators included in the grid structure level indicators;
FIG. 3 is a schematic diagram of secondary indicators included in the load supply capability indicators and secondary indicators included in the electricity consumption reliability indicators;
FIG. 4 is a schematic diagram of a secondary indicator included in the equipment skill level indicator;
FIG. 5 is a schematic diagram of secondary indicators included in the intelligent level indicators;
fig. 6 is a flowchart illustrating steps of a comprehensive evaluation method for a power distribution network according to another embodiment of the present invention;
fig. 7 is a block diagram of a comprehensive evaluation device for a power distribution network according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a comprehensive evaluation method, a comprehensive evaluation device, electronic equipment and a storage medium for a power distribution network, which are used for solving the technical problems that misjudgment is easy to generate or important factors are ignored or weight coefficient distribution errors occur in the existing comprehensive evaluation work of the power distribution network.
In order to make the objects, features and advantages of the present invention more comprehensible, the technical solutions in the embodiments of the present invention are described in detail below with reference to the accompanying drawings, and it is apparent that the embodiments described below are only some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, fig. 1 is a flowchart illustrating steps of a comprehensive evaluation method for a power distribution network according to an embodiment of the present invention.
The invention provides a comprehensive evaluation method of a power distribution network, which specifically comprises the following steps:
in the embodiment of the invention, as the influence factors related to various requirements are complex, certain similarity exists between different influence factors. In order to improve the comprehensiveness and rationality of the power distribution network evaluation, the evaluation index should not only contain quantitative indexes but also qualitative indexes.
In one example, the selection of the metrics may be referred to the following criteria:
1. principle of purposefulness. The selected index has the clear and clear evaluation purpose, and the overall performance and planning requirements of the power distribution network are objectively and comprehensively analyzed for the research, so that a data basis is provided for planning decision-making personnel.
2. Scientific normative principles. In practical engineering evaluation research, the most basic requirement is whether the evaluation can be accurate and objective. Therefore, when the evaluation index of the power distribution network is selected, the requirements of planning technical guidelines related to power grid companies are met, and the index classification and the data calculation are scientifically and normally carried out.
3. General systematic principles. The index selection should consider the global angle, and the aspects of ensuring the power grid structure, economic effect, technical level, equipment level and the like are all related, so as to avoid the phenomenon of single evaluation. The index system target layer and the evaluation layer should also have layering and logic.
4. Principle of independence. The indexes under the same level have mutual independence, so that the condition of crossing indexes during evaluation and analysis is avoided. The indexes are not too much to be selected, and the standard, strict and reasonable index system is ensured in order to avoid excessive redundancy of the indexes and overlarge association degree among the indexes.
5. Flexibility principles. Different planning emphasis points exist when planning staff makes decisions, such as reliability improvement or economical efficiency improvement during evaluation, and the planning evaluation index system should be correspondingly adjusted according to the decision direction change. Therefore, the index needs to have operability and adjustability so as to better cope with the actual engineering requirements.
6. Practical principles. The basic data of the selected index is easy to collect and acquire in actual engineering, and the running states of different evaluation dimensions of the power distribution network can be reflected truly. In addition, the index should also be quantifiable for ease of evaluation and analysis.
In practical application, the evaluation indexes considered by different requirements are different, and the different evaluation indexes often have a hierarchical association relationship, and can be specifically divided into a first-level index and a second-level index contained in the first-level index, so that in order to analyze the problem and propose a solution according to the evaluation indexes and requirements, the characteristics of the problem can be associated and integrated in a fishbone diagram mode, a visual, layered and concise graph is formed, and root cause diagnosis and analysis are performed on the problem. It is shaped like a skeleton of a fish, with a problem or objective being the fish head, subdividing the root cause of the problem and related factors into fish bones, facilitating better analysis of the problem and solution.
In the embodiment of the invention, the fish heads in the fish bone map are set as the safety requirement, the reliability requirement, the environmental requirement and the intelligence requirement of the power distribution network. The fish bones are internal characteristics under various characteristics, and the fishbones are specific indexes of the internal characteristics. According to the evaluation requirement of the power distribution network, the grid structure level, the load supply capacity, the equipment technical level, the intelligent level and the electricity reliability of the power distribution network can be selected as primary indexes of the power distribution network.
As shown in fig. 2, fig. 2 is a schematic diagram of secondary indexes included in the grid structure level index:
line ring network rate = 10kV line number/10 kV line total number x 100% of the ring network already formed;
line inter-station connection rate = 10kV line number of inter-station interconnections/10 kV line total number x 100%;
line rotatable power supply rate = 10kV line number of rotatable power supply/10 kV line total number x 100%;
line typical connection ratio = line number of 10kV typical connection/10 kV line total number x 100%.
As shown in fig. 3, fig. 3 is a schematic diagram of a secondary index included in the load supply capability index and a secondary index included in the electricity reliability index:
line average load rate = 10kV line average load/line rated capacity x 100%;
heavy-load line proportion = 10kV line number/bus line number x 100% exceeding 80% of rated load capacity;
overload line ratio = 10kV line number/bus line number over 100% of rated load capacity x 100%;
terminal voltage reject line proportion = 10kV line terminal voltage offset count/10 kV line total count;
heavy load distribution ratio = 10kV line number/bus line number x 100% exceeding 80% of rated load capacity;
overload distribution ratio = number of distribution transformers/total number of distribution transformers x 100% exceeding 100% of rated load capacity;
voltage higher area ratio = higher voltage area number/total area number x 100%;
voltage lower cell ratio = lower voltage cell number/total cell number x 100%.
Power supply reliability RS-3= [ monitoring total time-monitor power failure time (off-gate limit not recorded) ]/monitoring total time x 100%;
10kV line loss rate = 10kV line actual loss/active power x 100%;
the statistical loss rate of the 0.4kV distribution transformer area=0.4 kV distribution transformer area line loss total amount/distribution transformer area sales power multiplied by 100%.
As shown in fig. 4, fig. 4 is a schematic diagram of secondary indicators included in the equipment technical level indicator:
medium voltage line insulation rate = medium voltage line insulation line length/line total length x 100%;
line cabling rate = 10kV line cable length/10 kV line total length x 100%;
low line insulation = low line insulation length/low line total length x 100%;
high loss distribution transformer number ratio = high loss transformer number/total number of transformers x 100%;
one-household one-meter rate = number of installed smart meters/total number of households x 100%;
switch oilless rate = oilless total number of switches/total number of switches x 100%;
proportion of distribution transformer operating years greater than 15 years = number of transformers operating years greater than 15 years/total number of transformers x 100%.
As shown in fig. 5, fig. 5 is a schematic diagram of secondary indicators included in the intelligent level indicator:
distribution automation coverage = number of automation switches/number of total switches x 100%;
distribution automation effective coverage = number of switches/total number of switches x 100% meeting distribution terminal configuration requirements;
smart meter coverage = smart meter number/total user number x 100%;
low voltage meter reading coverage = low voltage meter reading count/10 kV line total count x 100%;
distribution network communication coverage = distribution network communication correct node number/summary node number x 100%;
three-teleterminal optical fiber coverage = three-teleterminal optical fiber number/total number of communication lines x 100%.
in the embodiment of the invention, after the evaluation index is obtained, the evaluation index can be checked to obtain a check index.
In one example, the check may include a plausibility check and a validity check. The method is used for verifying the credibility and the validity of the evaluation indexes, and reducing the adverse effect of the evaluation indexes with lower credibility and validity on the evaluation of the power distribution network.
104, calculating the objective weight of the check index;
the relative importance between the various check indexes refers to which one check index is more important than the other check index.
After the evaluation indexes are checked, the relative importance degree among the check indexes can be calculated, and the subjective weight of the check indexes is calculated according to the relative importance degree. And calculating the objective weight of each check index.
in the embodiment of the invention, after the subjective weight and the objective weight of each check index are obtained through calculation, the subjective weight and the objective weight can be adopted to generate the combined weight of the check index.
And 106, obtaining the score of each check index, and carrying out comprehensive evaluation on the power distribution network according to the combination weight of each check index and the corresponding score to obtain an evaluation result.
After the combination weights of the check indexes are calculated, the original data of the power distribution network can be obtained, and comprehensive evaluation of the power distribution network is carried out according to the original data of the power distribution network and the combination weights of the check indexes, so that an evaluation result is obtained.
The invention adopts subjective weighting and objective weighting to weight the check index, thereby reducing subjectivity and uncertainty of a single weighting method and improving accuracy and reliability of weighting results. Meanwhile, the situation that the weighting effect difference of different weighting methods on different evaluation indexes is large is avoided, and the accuracy of the relative weights of the evaluation indexes in comprehensive evaluation is ensured.
Referring to fig. 6, fig. 6 is a flowchart illustrating steps of a comprehensive evaluation method for a power distribution network according to another embodiment of the present invention. The method specifically comprises the following steps:
step 601 is the same as step 101, and specific reference may be made to the description of step 101, which is not repeated here.
in the embodiment of the invention, the evaluation scores of the first-level index and the second-level index of the technicians can be obtained, and then the credibility coefficient of the evaluation index is calculated through the following formulaa：
Wherein, the liquid crystal display device comprises a liquid crystal display device,
the value of (2) is 0-1, the closer the value is to 1, the more reliable the evaluation index is, the closer the value is to 0, the more unreliable the evaluation index is, if +.>
It indicates that the evaluation index passes the reliability check. />
For index quantity, & gt>
Scoring the index with a value->
Scoring variance for the ith index, +.>
Is the total score variance.
when the reliability coefficient reaches a preset reliability threshold, the validity coefficient of the evaluation index can be calculated
：
Wherein, the liquid crystal display device comprises a liquid crystal display device,
to consider the total number of people for which the index is effective in practical use, < >>
Is the root ofTotal number of people evaluated. When->
When equal to 1, the representation is completely accurate; while->
When equal to 0, this indicates complete inaccuracy. In general, when->
Not less than 0.6, then the test is considered to be satisfied.
after the evaluation indexes are checked, the relative importance degree among the check indexes can be calculated, and the subjective weight of the check indexes is calculated according to the relative importance degree.
In one example, the relative importance levels include a first relative importance level and a second relative importance level; the step of calculating the relative importance degree between the check indexes and calculating the subjective weight of the check indexes according to the relative importance degree may include the sub-steps of:
s61, determining an optimal index and a worst index in the check indexes;
s62, calculating a first relative importance degree between the optimal index and each check index;
s63, calculating a second relative importance degree between each check index and the worst index;
s64, calculating subjective weight of each check index according to the first relative importance degree and the second relative importance degree.
In the specific implementation, the most important index and the least important index in the primary index and the secondary index can be determined in all check indexes, namely the optimal index
And worst index->
. The optimal index is considered to have a significant impact on the evaluation result, and the worst index is the least impact on the evaluation result. If the planning decision maker considers that the planning decision maker has a plurality of optimal or worst indexes, one optimal or worst index can be selected from the plurality of optimal or worst indexes.
Comparing the optimal indexes with other indexes one by one through relative importance degrees, and scoring the optimal indexes by using a scaling method to construct a comparison vector based on the optimal indexes
，/>
A first relative importance degree of the optimal index B relative to the first index of the other indexes is represented by an integer of 1 to 9, 1 represents that two indexes are as important, and 9 represents that the former is extremely important compared with the latter, so->
。
Comparing the worst index with other indexes in the above mode to construct a comparison vector based on the worst index
。/>
Representing the second relative importance of the first of the other indicators with respect to the optimal indicator W.
It is worth noting that the optimal index contrast vector is used for comparing the optimal index with other indexes, the worst index contrast vector is used for comparing the other indexes with the worst index, and the front and back sequences of the comparison are opposite.
After the first relative importance degree and the second relative importance degree are obtained through calculation, a linear BWM data planning model can be constructed, and the relative importance degree is a weight size relation, so that the optimal index weight, namely the subjective weight of each check index, can be obtained through calculation through the following formula:
wherein, the liquid crystal display device comprises a liquid crystal display device,
the weight of the optimal index; />
The weight of the worst index; />
Is->
Subjective weight of each check index.
The model thereof can be further expressed as:
wherein, the liquid crystal display device comprises a liquid crystal display device,
is the maximum absolute difference of the weights, +.>
The smaller the error representing the calculation of the weighting of the index is, the smaller the error is, when +>
The weight confidence is greater the closer to 0.
in an embodiment of the present invention, the step of calculating the objective weight of the check index may include the following sub-steps:
s71, normalizing the check index to obtain a normalized index;
s72, calculating index variability of each normalized index according to the optimal index and the worst index;
s73, acquiring the data information quantity of each normalized index, and calculating the index conflict of each normalized index according to the data information quantity and the index variability;
s74, calculating objective weights of all the normalized indexes according to index conflict.
In the embodiment of the invention, the check indexes can be subjected to dimensionless treatment, and all the check indexes are subjected to normalization treatment to obtain the normalization indexes. Then calculate index variability of the normalized indexS j The calculation formula is as follows:
wherein, the liquid crystal display device comprises a liquid crystal display device,
normalized index of the worst index, +.>
Normalized index of optimal index, < > for>
Is the j-th normalized index.
After calculating the index variability, the index conflict of the normalized index can be calculated
：
Wherein, the liquid crystal display device comprises a liquid crystal display device,
representing the amount of data information after improvement, +.>
Is the average.
After the index conflict is calculated, the objective weight of the normalized index can be calculated according to the index conflict
：
in the embodiment of the present invention, the step of generating the combining weight of the check index according to the subjective weight and the objective weight may include the following sub-steps:
s81, calculating the relative entropy of the subjective weight and the objective weight;
s82, calculating the combination weight of the check index according to the relative entropy.
In practical applications, the relative entropy is a method for measuring the difference between two probability distributions, and can be used for comparing the evaluation results of experts on different factors. The relative entropy combination weighting method converts the variability between expert evaluation results into weights, so that the opinions of different experts can be scientifically integrated. In addition, the relative entropy combination weighting method has the advantages of high reliability and strong operability, so in the embodiment of the invention, the subjective weight based on the BWM method and the objective weight based on the improved CRITIC method can be combined and weighted by using the relative entropy combination weighting method, and the process is as follows:
first, the relative entropy of two weights is calculated
：
Further expressed by a mathematical model:
the combination weight of the ith check index can be obtained according to the formula
：
And step 609, obtaining the score of each check index, and carrying out comprehensive evaluation on the power distribution network according to the combination weight of each check index and the corresponding score to obtain an evaluation result.
After the combination weight of each check index is calculated, the power distribution network can be comprehensively evaluated by combining the scores of each check index, so that a comprehensive evaluation result is obtained:
wherein, the liquid crystal display device comprises a liquid crystal display device,
score representing each secondary index, +.>
Expressed as a composite score, < >>
Is the integrated score of the first level index.
The invention adopts subjective weighting and objective weighting to weight the check index, thereby reducing subjectivity and uncertainty of a single weighting method and improving accuracy and reliability of weighting results. Meanwhile, the situation that the weighting effect difference of different weighting methods on different evaluation indexes is large is avoided, and the accuracy of the relative weights of the evaluation indexes in comprehensive evaluation is ensured.
For ease of understanding, the following is illustrated by way of specific examples:
table 1 shows actual data of a power grid in a certain area:
scoring was performed in 10 minutes according to BWM method rules, and the first-order index layer optimum index, the worst index, and the relative importance are shown in table 2:
similarly, the optimum index, the worst index, and the relative importance of each secondary index are shown in tables 3, 4, 5, 6, and 7.
Weight data calculated from the above data is as follows:
the subjective weight of the first-level index is as follows:
；
the second-level index weights are respectively as follows:
grid structure level:
；
load supply capability:
；
the technical level of equipment:
；
level of intelligence:
；
reliability of electricity consumption:
；
the conflict and variability are then calculated from the data itself values by modifying CRITIC method. As shown in table 8 below:
then, according to a calculation formula of the relative entropy combination method, the subjective weight and the objective weight ratio can be obtained as shown in the following table 9:
finally, normalization processing and weight combination are carried out on each index, so that the results shown in tables 10a and 10b can be obtained:
referring to fig. 7, fig. 7 is a block diagram of a comprehensive evaluation device for a power distribution network according to an embodiment of the present invention.
The embodiment of the invention provides a comprehensive evaluation device for a power distribution network, which comprises the following components:
an evaluation index acquisition module 701, configured to acquire an evaluation index of the power distribution network;
the verification module 702 is configured to verify the evaluation index to obtain a verification index;
the subjective weight calculation module 703 is configured to calculate a relative importance degree between each of the check indexes, and calculate subjective weight of the check indexes according to the relative importance degree;
an objective weight calculation module 704, configured to calculate an objective weight of the check index;
the combination weight generating module 705 is configured to combine the subjective weight and the objective weight to generate a combination weight of the check index;
and the evaluation module 706 is configured to obtain the scores of the check indexes, and perform comprehensive evaluation on the power distribution network according to the combination weights of the check indexes and the corresponding scores, so as to obtain an evaluation result.
In an embodiment of the present invention, the verification module 702 includes:
the number and evaluation score acquisition sub-module is used for acquiring the number of the evaluation indexes and the evaluation score of each evaluation index;
the credibility coefficient calculation sub-module is used for calculating a credibility coefficient according to the number of the evaluation indexes and the evaluation score;
the validity coefficient calculation sub-module is used for calculating the validity coefficient of the evaluation index when the credibility coefficient reaches a preset credibility threshold;
and the verification index generation sub-module is used for taking an evaluation index with the effectiveness coefficient reaching a preset effectiveness threshold as a verification index.
In an embodiment of the present invention, the relative importance levels include a first relative importance level and a second relative importance level; the subjective weight calculation module 703 includes:
the optimal index and worst index determining submodule is used for determining an optimal index and a worst index in the check indexes;
the first relative importance degree calculating sub-module is used for calculating the first relative importance degree between the optimal index and each check index;
a second relative degree computing sub-module for computing a second relative degree of relationship between each of the check indexes and the worst index;
and the subjective weight calculation sub-module is used for calculating the subjective weight of each check index according to the first relative importance degree and the second relative importance degree.
In an embodiment of the present invention, the objective weight calculation module 704 includes:
the normalization sub-module is used for carrying out normalization processing on the check indexes to obtain normalization indexes;
the index variability calculation sub-module is used for calculating the index variability of each normalized index according to the optimal index and the worst index;
the index conflict computing sub-module is used for obtaining the data information quantity of each normalized index and computing the index conflict of each normalized index according to the data information quantity and the index variability;
and the objective weight calculation sub-module is used for calculating the objective weight of each normalized index according to the index conflict.
In an embodiment of the present invention, the combining weight generating module 705 includes:
the relative entropy calculation sub-module is used for calculating the relative entropy of the subjective weight and the objective weight;
and the combination weight calculation sub-module is used for calculating the combination weight of the check index according to the relative entropy.
The embodiment of the invention also provides electronic equipment, which comprises a processor and a memory:
the memory is used for storing the program codes and transmitting the program codes to the processor;
the processor is used for executing the comprehensive evaluation method of the power distribution network according to the embodiment of the invention according to the instructions in the program codes.
The embodiment of the invention also provides a computer readable storage medium, which is used for storing program codes, and the program codes are used for executing the comprehensive evaluation method of the power distribution network.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described by differences from other embodiments, and identical and similar parts between the embodiments are all enough to be referred to each other.
It will be apparent to those skilled in the art that embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the invention may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the scope of the embodiments of the invention.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or terminal device comprising the element.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. The comprehensive evaluation method for the power distribution network is characterized by comprising the following steps of:
acquiring an evaluation index of the power distribution network;
checking the evaluation index to obtain a check index;
calculating the relative importance degree among the check indexes, and calculating the subjective weight of the check indexes according to the relative importance degree;
calculating the objective weight of the check index;
combining the subjective weight and the objective weight to generate a combined weight of the check index;
and obtaining the score of each check index, and carrying out comprehensive evaluation on the power distribution network according to the combination weight of each check index and the corresponding score to obtain an evaluation result.
2. The method of claim 1, wherein the step of verifying the evaluation index to obtain a verification index comprises:
acquiring the number of the evaluation indexes and the evaluation score of each evaluation index;
calculating a credibility coefficient according to the number of the evaluation indexes and the evaluation score;
when the credibility coefficient reaches a preset credibility threshold, calculating the validity coefficient of the evaluation index;
and taking an evaluation index of which the effectiveness coefficient reaches a preset effectiveness threshold as a check index.
3. The method of claim 1, wherein the relative importance levels include a first relative importance level and a second relative importance level; the step of calculating the relative importance degree among the check indexes and calculating the subjective weight of the check indexes according to the relative importance degree comprises the following steps:
determining an optimal index and a worst index in the check indexes;
calculating a first relative importance degree between the optimal index and each check index;
calculating a second relative importance between each of the verification indexes and the worst indexes;
and calculating subjective weight of each check index according to the first relative importance degree and the second relative importance degree.
4. A method according to claim 3, wherein the step of calculating the objective weight of the verification indicator comprises:
normalizing the check index to obtain a normalized index;
calculating index variability of each normalized index according to the optimal index and the worst index;
acquiring the data information quantity of each normalized index, and calculating the index conflict of each normalized index according to the data information quantity and the index variability;
and calculating the objective weight of each normalized index according to the index conflict.
5. The method according to claim 1, wherein the step of generating the combining weights of the check index according to the subjective weights and the objective weights comprises:
calculating the relative entropy of the subjective weight and the objective weight;
and calculating the combination weight of the check index according to the relative entropy.
6. An integrated power distribution network assessment device, comprising:
the evaluation index acquisition module is used for acquiring the evaluation index of the power distribution network;
the verification module is used for verifying the evaluation index to obtain a verification index;
the subjective weight calculation module is used for calculating the relative importance degree among the check indexes and calculating the subjective weight of the check indexes according to the relative importance degree;
the objective weight calculation module is used for calculating the objective weight of the check index;
the combination weight generation module is used for combining the subjective weight and the objective weight to generate the combination weight of the check index;
and the evaluation module is used for acquiring the scores of the check indexes, and carrying out comprehensive evaluation on the power distribution network according to the combination weights of the check indexes and the corresponding scores to obtain an evaluation result.
7. The apparatus of claim 6, wherein the verification module comprises:
the number and evaluation score acquisition sub-module is used for acquiring the number of the evaluation indexes and the evaluation score of each evaluation index;
the credibility coefficient calculation sub-module is used for calculating a credibility coefficient according to the number of the evaluation indexes and the evaluation score;
the validity coefficient calculation sub-module is used for calculating the validity coefficient of the evaluation index when the credibility coefficient reaches a preset credibility threshold;
and the verification index generation sub-module is used for taking an evaluation index with the effectiveness coefficient reaching a preset effectiveness threshold as a verification index.
8. The apparatus of claim 6, wherein the relative importance levels include a first relative importance level and a second relative importance level; the subjective weight calculation module comprises:
the optimal index and the worst index determining submodule is used for determining an optimal index and a worst index in the check indexes;
a first relative importance degree calculating sub-module, configured to calculate a first relative importance degree between the optimal index and each of the check indexes;
a second relative extent calculation sub-module for calculating a second relative extent between each of the check indicators and the worst indicator;
and the subjective weight calculation sub-module is used for calculating the subjective weight of each check index according to the first relative importance degree and the second relative importance degree.
9. An electronic device, the device comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute the comprehensive evaluation method for the power distribution network according to any one of claims 1 to 5 according to the instructions in the program code.
10. A computer readable storage medium for storing program code for performing the comprehensive assessment method of a power distribution network according to any one of claims 1-5.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130328786A1 (en) * | 2012-06-07 | 2013-12-12 | Microsoft Corporation | Information triage using screen-contacting gestures |
| US20170255378A1 (en) * | 2016-03-02 | 2017-09-07 | Airwatch, Llc | Systems and methods for performing erasures within a graphical user interface |
| CN114971227A (en) * | 2022-05-10 | 2022-08-30 | 河海大学 | Power distribution network equipment risk assessment method based on MARCOS method |
| CN115729434A (en) * | 2021-08-31 | 2023-03-03 | 华为技术有限公司 | Writing and drawing content display method and related equipment |
| CN115759538A (en) * | 2022-11-23 | 2023-03-07 | 山东大学 | Comprehensive evaluation method and system for multivariate voltage regulation characteristics of deep peak regulation thermal power generating unit |
| WO2023035499A1 (en) * | 2021-09-10 | 2023-03-16 | 国网上海市电力公司 | Method and system for comprehensive evaluation of resilience of power distribution network |
| CN115952897A (en) * | 2022-12-19 | 2023-04-11 | 国网吉林省电力有限公司经济技术研究院 | Optimal configuration method of urban energy system |
-
2023
- 2023-05-29 CN CN202310611414.7A patent/CN116341992A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130328786A1 (en) * | 2012-06-07 | 2013-12-12 | Microsoft Corporation | Information triage using screen-contacting gestures |
| US20170255378A1 (en) * | 2016-03-02 | 2017-09-07 | Airwatch, Llc | Systems and methods for performing erasures within a graphical user interface |
| CN115729434A (en) * | 2021-08-31 | 2023-03-03 | 华为技术有限公司 | Writing and drawing content display method and related equipment |
| WO2023030377A1 (en) * | 2021-08-31 | 2023-03-09 | 华为技术有限公司 | Writing/drawing content display method and related device |
| WO2023035499A1 (en) * | 2021-09-10 | 2023-03-16 | 国网上海市电力公司 | Method and system for comprehensive evaluation of resilience of power distribution network |
| CN114971227A (en) * | 2022-05-10 | 2022-08-30 | 河海大学 | Power distribution network equipment risk assessment method based on MARCOS method |
| CN115759538A (en) * | 2022-11-23 | 2023-03-07 | 山东大学 | Comprehensive evaluation method and system for multivariate voltage regulation characteristics of deep peak regulation thermal power generating unit |
| CN115952897A (en) * | 2022-12-19 | 2023-04-11 | 国网吉林省电力有限公司经济技术研究院 | Optimal configuration method of urban energy system |
Non-Patent Citations (3)
| Title |
|---|
| 欧阳森: "考虑负荷恢复过程的配电网用电可靠性评估指标与方法", 《电力自动化设备》, vol. 41, no. 3, pages 33 - 40 * |
| 谢骐泽;: "基于R软件的评分者可信度分析", 数学学习与研究, no. 01, pages 150 * |
| 陈利和 等: "农村药品"监督与供应"网络建设评价体系指标的信度分析*", 《中国卫生经济》, pages 87 - 90 * |
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