CN109657967A - A kind of confirmation method and system of Transmission Expansion Planning in Electric evaluating indexesto scheme weight - Google Patents
A kind of confirmation method and system of Transmission Expansion Planning in Electric evaluating indexesto scheme weight Download PDFInfo
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Abstract
The present invention relates to Transmission Expansion Planning in Electric technical fields, the confirmation method and system of a kind of Transmission Expansion Planning in Electric evaluating indexesto scheme weight are provided, method includes: to carry out assignment according to the significance level of achievement data each in index system to each index, obtain the weight coefficient p of index jj；According to the dispersion degree of achievement data each in index system, assignment is carried out to each index, obtains the weight coefficient q of index jj；According to the weight coefficient p for the index j being calculatedjWith weight coefficient qjAnd comprehensive weight calculation formula, the comprehensive weight coefficient of parameter j to realize the confirmation of index weights in index system, while embodying the subjective information of policymaker and the objective information of data distribution, provide safeguard for power network planning scheme evaluation.
Description
Technical field
The invention belongs to Transmission Expansion Planning in Electric technical field more particularly to a kind of Transmission Expansion Planning in Electric evaluating indexesto scheme weights
Confirmation method and system.
Background technique
The target of Transmission Expansion Planning in Electric schemes synthesis evaluation and requirement are to integrate, quantitatively investigate each scheme of Transmission Expansion Planning in Electric
Situation and adaptedness with national economy and social development level are met to requirements such as safety, economy, the feature of environmental protection,
Foundation is provided to select most reasonable programme.Safety is the first element that Electric Power Network Planning considers, Electric Power Network Planning is necessary
Guarantee securely feeds load, is provided simultaneously with certain accident defence capability.Meanwhile power network planning scheme is needed in view of economy
The requirement of property and the feature of environmental protection, exchanges preferable environmental benefit for as far as possible with lesser economic cost.In addition, Electric Power Network Planning whether section
It learns rationally to bring to the safety and stability of power grid from now on operation and directly affect, reasonable Electric Power Network Planning structure should be able to adapt to a variety of
The possible method of operation guarantees the demand that future load increases and rack extends.
Transmission Expansion Planning in Electric schemes synthesis evaluation general frame mainly include following main process: explicit evaluation purpose, really
Surely it is evaluated object, assessment indicator system, establishment weight coefficient corresponding with every evaluation index, selection is established or constructs comprehensive
It closes evaluation model and calculates the comprehensive evaluation value of each system and be ranked up or classify, wherein the determination of index weights is comprehensive
Close the key problem of evaluation method.Each index is to the embodiment degree of power grid energy-saving benefit difference in index system, therefore answers
Suitable weight coefficient is assigned, respectively to embody different indexs to the percentage contribution of final appraisal results.
But Transmission Expansion Planning in Electric schemes synthesis is evaluated in frame structure at present, to index each in index system
The confirmation of weight generally uses two ways to realize, one is being assigned to weigh according to the relative importance degree of index, another kind is root
Power is assigned according to the dispersion degree of achievement data.But these two types of modes are problematic in that, according to the entitled side of relative importance degree
Method reflects the subjective intuition of policymaker, is but easy to be influenced by policymaker's shortage correlation experience and knowledge；Dispersed according to data
For the entitled method of degree based entirely on mathematical theory and method, calculated result is objective and accurate, but has ignored policymaker master completely
The influence of sight factor is not inconsistent with the original intention of many Process of Comprehensive Assessment.
Summary of the invention
For the defects in the prior art, the present invention provides a kind of subjective information for embodying policymaker simultaneously and data point
The confirmation method of the Transmission Expansion Planning in Electric evaluating indexesto scheme weight of the objective information of cloth.
The technical solution provided by the present invention is: a kind of confirmation method of Transmission Expansion Planning in Electric evaluating indexesto scheme weight, institute
The method of stating includes the following steps:
According to the significance level of achievement data each in index system, assignment is carried out to each index, obtains the power of index j
Weight coefficient pj；
According to the dispersion degree of achievement data each in index system, assignment is carried out to each index, obtains the power of index j
Weight coefficient qj；
According to the weight coefficient p for the index j being calculatedjWith weight coefficient qjAnd comprehensive weight calculation formula,
The comprehensive weight coefficient ω of parameter jj, wherein the comprehensive weight calculation formula are as follows:
ωj=k1pj+k2qj, in formula, k1And k2For undetermined constant, meet k1>0、k2> 0 and k1+k2=1.
As an improvement scheme, the significance level according to achievement data each in index system, to each finger
Mark carries out assignment, obtains the weight coefficient p of index jjThe step of specifically include the following steps:
In the index system, each single index data are compared two-by-two based on the importance of evaluation goal and are sentenced
It is disconnected, generate judgment matrix A；
In the judgment matrix A, feature vector corresponding to maximum eigenvalue in the judgment matrix A is subjected to normalizing
Change operation, and the parameter that normalization is obtained is as the weight coefficient p of index j in the index systemj。
As an improvement scheme, it is described in the index system, by each single index data be based on evaluation mesh
After the step of target importance carries out multilevel iudge two-by-two, generates judgment matrix A；It is described in the judgment matrix A, by institute
Stating the step of operation is normalized in feature vector corresponding to maximum eigenvalue in judgment matrix A further includes before following steps
It is rapid:
Consistency judgement is carried out to the judgment matrix A of generation；
When determining that the judgment matrix A meets consistency, then execution is described in the judgment matrix A, sentences described
The step of operation is normalized in feature vector corresponding to maximum eigenvalue in disconnected matrix A；
When determining that the judgment matrix A is inconsistent, then assignment is carried out to the judgment matrix A again, and return to execution
The judgment matrix A of described pair of generation carries out the step of consistency judgement.
As an improvement scheme, the significance level according to achievement data each in index system, to each finger
Mark carries out assignment, obtains the weight coefficient p of index jjThe step of specifically include the following steps:
According to the significance level of achievement data each in the index system, the index for generating the displacement of an order relation is important
Property sequencing table X；
In the index importance sequencing table X, assignment is carried out to the significance level of each index, obtains numerical value pk；
According to index significance level weight calculation formula, the weight coefficient p of parameter jj, wherein the index is important
Degree weight calculation formula are as follows:
ωk-1=rkωk, k=n, n-1 ..., 2, in formula, ri=pi-1/pi, i=2,3,4 ..., n.
As an improvement scheme, the dispersion degree according to achievement data each in index system, to each finger
Mark carries out assignment, obtains the weight coefficient q of index jjThe step of specifically include the following steps:
According to the dispersion degree of achievement data each in the index system, calculate under jth item index, i-th of power grid pair
The feature specific gravity p of elephantij, in which:Wherein, xijIndicate the index number of i-th of power network object of jth item index
According to；
According under the jth item index being calculated, the feature specific gravity p of i-th of power network objectij, calculate the entropy of jth item index
Value ej, whereinIn formula, k=1/ln m；
According to the entropy e for the jth item index being calculatedj, calculate the difference property coefficient g of jth item indexj, wherein gj=
1-ej；
According to the difference property coefficient g for the jth item index being calculatedj, determine the weight coefficient q of jth item indexj, wherein
It is described another object of the present invention is to provide a kind of confirmation system of Transmission Expansion Planning in Electric evaluating indexesto scheme weight
System includes:
First weight coefficient assignment module, for the significance level according to achievement data each in index system, to each
Index carries out assignment, obtains the weight coefficient p of index jj；
Second weight coefficient assignment module, for the dispersion degree according to achievement data each in index system, to each
Index carries out assignment, obtains the weight coefficient q of index jj；
Comprehensive weight coefficients calculation block, for the weight coefficient p according to the index j being calculatedjWith weight system
Number qjAnd comprehensive weight calculation formula, the comprehensive weight coefficient ω of parameter jj, wherein the comprehensive weight calculation formula
Are as follows:
ωj=k1pj+k2qj, in formula, k1And k2For undetermined constant, meet k1>0、k2> 0 and k1+k2=1.
As an improvement scheme, the first weight coefficient assignment module specifically includes:
Judgment matrix generation module, in the index system, each single index data to be based on evaluation goal
Importance carry out multilevel iudge two-by-two, generate judgment matrix A；
First weight coefficient confirmation module is used in the judgment matrix A, by feature maximum in the judgment matrix A
Operation is normalized in the corresponding feature vector of value, and the parameter that normalization is obtained is as index j in the index system
Weight coefficient pj。
As an improvement scheme, the first weight coefficient assignment module further include:
Consistency judgment module, for carrying out consistency judgement to the judgment matrix A of generation；
Again assignment module, for when determining that the judgment matrix A is inconsistent, then again to the judgment matrix A into
Row assignment, and the step of returning to the judgment matrix A progress consistency judgement for executing described pair of generation；
When determining that the judgment matrix A meets consistency, then execution is described in the judgment matrix A, sentences described
The step of operation is normalized in feature vector corresponding to maximum eigenvalue in disconnected matrix A.
As an improvement scheme, the first weight coefficient assignment module further include:
Index importance sequencing table generation module, for the important journey according to achievement data each in the index system
Degree generates the index importance sequencing table X of order relation displacement；
Assignment module, for carrying out assignment to the significance level of each index in the index importance sequencing table X,
Obtain numerical value pk；
Computing module, for according to index significance level weight calculation formula, the weight coefficient p of parameter jj, wherein
The index significance level weight calculation formula are as follows:
ωk-1=rkωk, k=n, n-1 ..., 2, in formula, ri=pi-1/pi, i=2,3,4 ..., n.
As an improvement scheme, the second weight coefficient assignment module specifically includes:
Aspect ratio re-computation module calculates jth for the dispersion degree according to achievement data each in the index system
Under item index, the feature specific gravity p of i-th of power network objectij, in which:Wherein, xijIndicate jth item index i-th
The achievement data of a power network object；
Entropy computing module, for according under the jth item index that is calculated, the feature specific gravity p of i-th of power network objectij,
Calculate the entropy e of jth item indexj, whereinIn formula, k=1/ln m；
Otherness coefficients calculation block, for the entropy e according to the jth item index being calculatedj, calculate jth item index
Difference property coefficient gj, wherein gj=1-ej；
Second weight coefficient confirmation module, for the difference property coefficient g according to the jth item index being calculatedj, determine
The weight coefficient q of j indexsj, wherein
In embodiments of the present invention, according to the significance level of achievement data each in index system, each index is carried out
Assignment obtains the weight coefficient p of index jj；According to the dispersion degree of achievement data each in index system, to each index into
Row assignment obtains the weight coefficient q of index jj；According to the weight coefficient p for the index j being calculatedjWith weight coefficient qj,
And comprehensive weight calculation formula, the comprehensive weight coefficient of parameter j, to realize that index weights are really in index system
Recognize, while embodying the subjective information of policymaker and the objective information of data distribution, is provided safeguard for power network planning scheme evaluation.
Detailed description of the invention
It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution in the prior art
Embodiment or attached drawing needed to be used in the description of the prior art are briefly described.In all the appended drawings, similar element
Or part is generally identified by similar appended drawing reference.In attached drawing, each element or part might not be drawn according to actual ratio.
Fig. 1 is the implementation flow chart of the confirmation method of Transmission Expansion Planning in Electric evaluating indexesto scheme weight provided by the invention；
Fig. 2 is the significance level according to achievement data each in index system that the embodiment of the present invention one provides, to each
Index carries out assignment, obtains the weight coefficient p of index jjImplementation flow chart；
Fig. 3 is the significance level provided by Embodiment 2 of the present invention according to achievement data each in index system, to each
Index carries out assignment, obtains the weight coefficient p of index jjImplementation flow chart；
Fig. 4 is the dispersion degree provided by the invention according to achievement data each in index system, is carried out to each index
Assignment obtains the weight coefficient q of index jjImplementation flow chart；
Fig. 5 is the structural frames of the confirmation system for the Transmission Expansion Planning in Electric evaluating indexesto scheme weight that the embodiment of the present invention one provides
Figure；
Fig. 6 is the structural frames of the confirmation system of Transmission Expansion Planning in Electric evaluating indexesto scheme weight provided by Embodiment 2 of the present invention
Figure；
Fig. 7 is the structural frames of the confirmation system for the Transmission Expansion Planning in Electric evaluating indexesto scheme weight that the embodiment of the present invention three provides
Figure.
Specific embodiment
It is described in detail below in conjunction with embodiment of the attached drawing to technical solution of the present invention.Following embodiment is only used for
Clearly illustrate of the invention, technical solution, therefore be only used as example, and cannot be used as a limitation and limit protection model of the invention
It encloses.
Fig. 1 is the implementation flow chart of the confirmation method of Transmission Expansion Planning in Electric evaluating indexesto scheme weight provided by the invention,
Specifically include the following steps:
In step s101, according to the significance level of achievement data each in index system, assignment is carried out to each index,
Obtain the weight coefficient p of index jj。
In step s 102, according to the dispersion degree of achievement data each in index system, assignment is carried out to each index,
Obtain the weight coefficient q of index jj。
In step s 103, according to the weight coefficient p for the index j being calculatedjWith weight coefficient qj, and it is comprehensive
Weight calculation formula, the comprehensive weight coefficient ω of parameter jj, wherein the comprehensive weight calculation formula are as follows:
ωj=k1pj+k2qj, in formula, k1And k2For undetermined constant, meet k1>0、k2> 0 and k1+k2=1.
In this embodiment, which determines that scheme is equal by the dispersion degree of the significance level of achievement data and achievement data
It takes into account, so that identified weight coefficient embodies the trunk information of policymaker and the objective information of data analysis simultaneously.
In embodiments of the present invention, according to the important of achievement data each in index system documented by above-mentioned steps S101
Degree carries out assignment to each index, obtains the weight coefficient p of index jjThe step of realization can use various ways, under
It states and provides two kinds of concrete implementations, specifically:
The first: analytic hierarchy process (AHP)
It is right Fig. 2 shows the significance level according to achievement data each in index system that the embodiment of the present invention one provides
Each index carries out assignment, obtains the weight coefficient p of index jjImplementation flow chart, specifically include the following steps:
In step s 201, in the index system, by each importance of the single index data based on evaluation goal
Multilevel iudge two-by-two is carried out, judgment matrix A is generated；
In step S202, in the judgment matrix A, by spy corresponding to maximum eigenvalue in the judgment matrix A
Operation is normalized in sign vector, and the parameter that normalization is obtained is as the weight coefficient p of index j in the index systemj。
In this embodiment, further include following step between step S201 and step S202:
(1) consistency judgement is carried out to the judgment matrix A of generation；
(2) when determining that the judgment matrix A meets consistency, then execution is described in the judgment matrix A, will be described
The step of operation is normalized in feature vector corresponding to maximum eigenvalue in judgment matrix A；
(3) when determining that the judgment matrix A is inconsistent, then assignment is carried out to the judgment matrix A again, and return and hold
The step of judgment matrix A of described pair of generation of row carries out consistency judgement.
Wherein, analytic hierarchy process AHP is one proposed by U.S. Pittsburg college professor Satie in early 1970s
Plant level weight method of decision analysis that is qualitative and quantitatively combining.Between relationship each index of power network planning scheme overall merit
On the basis of in-depth analysis, related each factor is resolved into two layers according to different attribute from top to down in conjunction with AHP method
Secondary: upper layer is destination layer, and decision objective can be every first class index；Lower layer is indicator layer, is to entitled each comprising factor
Item index.
In indicator layer, each single index is done into multilevel iudge two-by-two about the importance degree of evaluation goal, it is available
Judgment matrix A, specific relatively scale is as shown in following table 3-1:
Thus for a system containing n index, the judgment matrix of n × n rank can be formed.
Ideal judgment matrix should meet condition for consistence.So-called condition for consistence refers to that the element in judgment matrix A has
There is transitivity, that is, establishment of having ready conditions.However, being limited by judge condition, actual judgment matrix is not usually able to satisfy consistency item
Part.In this regard, the judgement quality to matrix is needed to carry out consistency check；
The quantitative index for measuring the inconsistent degree of judgment matrix is known as coincident indicator C.I., its calculation formula is:In formula, λmaxFor the maximum eigenvalue of judgment matrix.
The inconsistency of judgment matrix is related to its order, and the order of judgment matrix is bigger, multilevel iudge two-by-two between element
It is just more difficult to reach consistency；The consistency check critical value applicable to the judgment matrix of different rank in order to obtain, it is also necessary to
Consider the relationship of consistency and matrix order；For this purpose, introducing Aver-age Random Consistency Index R.I., C.I. is modified；It is logical
Cross a large amount of random samplings be calculated R.I. sample average it is as shown in the table:
| n | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| R.I. | 0 | 0.5419 | 0.8931 | 1.1185 | 1.2494 | 1.3450 | 1.4200 |
| n | 9 | 10 | 11 | 12 | 13 | 14 | 15 |
| R.I. | 1.4616 | 1.4874 | 1.5156 | 1.5405 | 1.5583 | 1.5779 | 1.5894 |
The ratio between the coincident indicator C.I. of judgment matrix and same order Aver-age Random Consistency Index R.I. are known as random one
Cause sex ratio C.R.；
WhenWhen, it is believed that the inconsistency of judgment matrix can receive, and otherwise just need to judgment matrix
Assignment again is carried out, until meeting condition for consistence.
For meeting the judgment matrix of condition for consistence, it is by the normalization of feature vector corresponding to its maximum eigenvalue
The weight coefficient of each evaluation index.
Second: G-1 method
Fig. 3 shows the significance level provided by Embodiment 2 of the present invention according to achievement data each in index system, right
Each index carries out assignment, obtains the weight coefficient p of index jjImplementation flow chart, specifically include the following steps:
In step S301, according to the significance level of achievement data each in the index system, an order relation is generated
The index importance sequencing table X of displacement；
In step s 302, in the index importance sequencing table X, assignment is carried out to the significance level of each index,
Obtain numerical value pk；
In step S303, according to index significance level weight calculation formula, the weight coefficient p of parameter jj, wherein
The index significance level weight calculation formula are as follows:
ωk-1=rkωk, k=n, n-1 ..., 2, in formula, ri=pi-1/pi, i=2,3,4 ..., n.
When wherein, using AHP method, the inconsistency of judgment matrix can seriously affect the calculated result of index weights.Meanwhile
With the increase of evaluation index number, the calculation amount of judgment matrix can also be doubled and redoubled.For this purpose, can be using without test and judge
The G-1 method of matrix consistency.
The key of G-1 method is ranked up for the importance of each index.Most important finger is selected in all indexs first
Mark, makes number one, is denoted as x1, most important one is then selected from remaining index, is come second, is denoted as x2, with such
It pushes away, finally obtains the unique index importance sequencing table of an order relation, be denoted as X, specific structure is as follows:
To evaluation index x adjacent in Xk-1With xkThe ratio between relative importance judged, r can be usedkTo indicate: rk=
pk-1/pk, k=2,3 ..., n
In formula, pkFor the corresponding weight of kth item evaluation index in index set X.
The above-mentioned scheme for giving two kinds of importance degrees by index and carrying out weight confirmation, herein not to limit this
Invention, naturally it is also possible to which by other means, details are not described herein.
In embodiments of the present invention, Fig. 4 is provided in an embodiment of the present invention according to achievement data each in index system
Dispersion degree carries out assignment to each index, obtains the weight coefficient q of index jjImplementation flow chart, specifically include following
Step:
In step S401, according to the dispersion degree of achievement data each in the index system, jth item index is calculated
Under, the feature specific gravity p of i-th of power network objectij, in which:Wherein, xijIndicate i-th of power grid of jth item index
The achievement data of object；
In step S402, according under the jth item index being calculated, the feature specific gravity p of i-th of power network objectij, calculate
The entropy e of jth item indexj, whereinIn formula, k=1/ln m；
In step S403, according to the entropy e for the jth item index being calculatedj, calculate the otherness system of jth item index
Number gj, wherein gj=1-ej；
In step s 404, according to the difference property coefficient g for the jth item index being calculatedj, determine the power of jth item index
Weight coefficient qj,
Wherein, which is entropy assessment, and entropy assessment is a kind of information content according to provided by indices observation
Size come the method that determines index weights.Entropy is a concept in thermodynamics, introduces information theory by Shen Nong earliest.According to letter
The definition of opinion is ceased, comentropy then reflects the disordering degree of information, is worth smaller, and the information utility value provided is bigger.If being
System is likely to be at a variety of different conditions, and the probability that every kind of state occurs is respectively pi(i=1,2 ..., m), the then entropy of the system
Is defined as:
As can be seen from the above equation, the probability occurred when the various states of system is identical, i.e. pi=1/m, (i=1,2 ...,
When m), the entropy of the system is maximum, and the information utility value provided at this time from the system to integrated decision-making person is minimum.Entropy assessment it is basic
Thought is: if a certain index entropy is smaller, illustrating that the degree of variation of the achievement data sequence is larger, should pay attention to the evaluation index
Effect for entire assessment models, weight are also answered larger, otherwise should just reduce its weight coefficient.
Fig. 5 is the knot for the confirmation system that embodiment of the embodiment of the present invention one provides Transmission Expansion Planning in Electric evaluating indexesto scheme weight
Structure block diagram only gives part related to the embodiment of the present invention for ease of description in figure.
The confirmation system of Transmission Expansion Planning in Electric evaluating indexesto scheme weight includes:
First weight coefficient assignment module 11, for the significance level according to achievement data each in index system, to each
A index carries out assignment, obtains the weight coefficient p of index jj；
Second weight coefficient assignment module 12, for the dispersion degree according to achievement data each in index system, to each
A index carries out assignment, obtains the weight coefficient q of index jj；
Comprehensive weight coefficients calculation block 13, for the weight coefficient p according to the index j being calculatedjAnd weight
Coefficient qjAnd comprehensive weight calculation formula, the comprehensive weight coefficient ω of parameter jj, wherein the comprehensive weight calculates public
Formula are as follows:
ωj=k1pj+k2qj, in formula, k1And k2For undetermined constant, meet k1>0、k2> 0 and k1+k2=1.
As shown in fig. 6, the first weight coefficient assignment module 11 specifically includes on the basis of embodiment shown in Fig. 5:
Judgment matrix generation module 14, in the index system, each single index data to be based on evaluation mesh
Target importance carries out multilevel iudge two-by-two, generates judgment matrix A；
First weight coefficient confirmation module 15 is used in the judgment matrix A, will be maximum special in the judgment matrix A
Operation is normalized in feature vector corresponding to value indicative, and the parameter that normalization is obtained is as index in the index system
The weight coefficient p of jj。
Wherein, the first weight coefficient assignment module 11 further include:
Consistency judgment module 16, for carrying out consistency judgement to the judgment matrix A of generation；
Again assignment module 17 is used for when determining that the judgment matrix A is inconsistent, then again to the judgment matrix A
Assignment is carried out, and the step of returning to the judgment matrix A progress consistency judgement for executing described pair of generation；
When determining that the judgment matrix A meets consistency, then execution is described in the judgment matrix A, sentences described
The step of operation is normalized in feature vector corresponding to maximum eigenvalue in disconnected matrix A.
In this embodiment, the second weight coefficient assignment module 12 specifically includes:
Aspect ratio re-computation module 18 is calculated for the dispersion degree according to achievement data each in the index system
Under jth item index, the feature specific gravity p of i-th of power network objectij, in which:Wherein, xijIndicate jth item index
The achievement data of i-th of power network object；
Entropy computing module 19, for according under the jth item index that is calculated, the feature specific gravity of i-th of power network object
Pij calculates the entropy e of jth item indexj, whereinIn formula, k=1/ln m；
Otherness coefficients calculation block 20, for the entropy e according to the jth item index being calculatedj, calculate jth item and refer to
Target difference property coefficient gj, wherein gj=1-ej；
Second weight coefficient confirmation module 21 is determined for the difference property coefficient gj according to the jth item index being calculated
The weight coefficient qj of jth item index,
On the basis of embodiment shown in Fig. 5, as shown in fig. 7, the difference with embodiment shown in fig. 6 is the first power
The structure of weight coefficient assignment module 11, specifically:
The first weight coefficient assignment module 11 includes:
Index importance sequencing table generation module 22, for the important journey according to achievement data each in the index system
Degree generates the index importance sequencing table X of order relation displacement；
Assignment module 23, for being assigned to the significance level of each index in the index importance sequencing table X
Value, obtains numerical value pk；
Computing module 24, for according to index significance level weight calculation formula, the weight coefficient p of parameter jj,
In, the index significance level weight calculation formula are as follows:
ωk-1=rkωk, k=n, n-1 ..., 2, in formula, ri=pi-1/pi, i=2,3,4 ..., n.
The function of above-mentioned modules is as recorded in above method embodiment, and details are not described herein.
In embodiments of the present invention, according to the significance level of achievement data each in index system, each index is carried out
Assignment obtains the weight coefficient p of index jj；According to the dispersion degree of achievement data each in index system, to each index into
Row assignment obtains the weight coefficient q of index jj；According to the weight coefficient p for the index j being calculatedjWith weight coefficient qj,
And comprehensive weight calculation formula, the comprehensive weight coefficient of parameter j, to realize that index weights are really in index system
Recognize, while embodying the subjective information of policymaker and the objective information of data distribution, is provided safeguard for power network planning scheme evaluation.
The above embodiments are only used to illustrate the technical solution of the present invention., rather than its limitations；Although referring to aforementioned each reality
Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified, or equivalent substitution of some or all of the technical features；And
These are modified or replaceed, the range for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution,
It should all cover within the scope of the claims and the description of the invention.
Claims (10)
1. a kind of confirmation method of Transmission Expansion Planning in Electric evaluating indexesto scheme weight, which is characterized in that the method includes following steps
It is rapid:
According to the significance level of achievement data each in index system, assignment is carried out to each index, obtains the weight system of index j
Number pj；
According to the dispersion degree of achievement data each in index system, assignment is carried out to each index, obtains the weight system of index j
Number qj；
According to the weight coefficient p for the index j being calculatedjWith weight coefficient qjAnd comprehensive weight calculation formula, it calculates
The comprehensive weight coefficient ω of index jj, wherein the comprehensive weight calculation formula are as follows:
ωj=k1pj+k2qj, in formula, k1And k2For undetermined constant, meet k1>0、k2> 0 and k1+k2=1.
2. the confirmation method of Transmission Expansion Planning in Electric evaluating indexesto scheme weight according to claim 1, which is characterized in that described
According to the significance level of achievement data each in index system, assignment is carried out to each index, obtains the weight coefficient p of index jj
The step of specifically include the following steps:
In the index system, each single index data are subjected to multilevel iudge two-by-two based on the importance of evaluation goal,
Generate judgment matrix A；
In the judgment matrix A, behaviour is normalized in feature vector corresponding to maximum eigenvalue in the judgment matrix A
Make, and the parameter that normalization is obtained is as the weight coefficient p of index j in the index systemj。
3. the confirmation method of Transmission Expansion Planning in Electric evaluating indexesto scheme weight according to claim 2, which is characterized in that described
In the index system, each single index data are subjected to multilevel iudge two-by-two based on the importance of evaluation goal, are generated
After the step of judgment matrix A；It is described in the judgment matrix A, will be corresponding to maximum eigenvalue in the judgment matrix A
Feature vector further includes following step before the step of operation is normalized:
Consistency judgement is carried out to the judgment matrix A of generation；
When determining that the judgment matrix A meets consistency, then execution is described in the judgment matrix A, by the judgement square
The step of operation is normalized in feature vector corresponding to maximum eigenvalue in battle array A；
When determining that the judgment matrix A is inconsistent, then assignment is carried out to the judgment matrix A again, and return described in execution
The step of consistency judgement is carried out to the judgment matrix A of generation.
4. the confirmation method of Transmission Expansion Planning in Electric evaluating indexesto scheme weight according to claim 1, which is characterized in that described
According to the significance level of achievement data each in index system, assignment is carried out to each index, obtains the weight coefficient p of index jj
The step of specifically include the following steps:
According to the significance level of achievement data each in the index system, the index importance row of an order relation displacement is generated
Sequence Table X；
In the index importance sequencing table X, assignment is carried out to the significance level of each index, obtains numerical value pk；
According to index significance level weight calculation formula, the weight coefficient p of parameter jj, wherein the index significance level power
Re-computation formula are as follows:
ωk-1=rkωk, k=n, n-1 ..., 2, in formula, ri=pi-1/pi, i=2,3,4 ..., n.
5. according to power can require 2 or 4 described in Transmission Expansion Planning in Electric evaluating indexesto scheme weight confirmation method, feature exists
In the dispersion degree according to achievement data each in index system carries out assignment to each index, obtains the power of index j
Weight coefficient qjThe step of specifically include the following steps:
According to the dispersion degree of achievement data each in the index system, calculate under jth item index, i-th power network object
Feature specific gravity pij, in which:Wherein, xijIndicate the achievement data of i-th of power network object of jth item index；
According under the jth item index being calculated, the feature specific gravity p of i-th of power network objectij, calculate the entropy of jth item index
ej, whereinIn formula, k=1/ln m；
According to the entropy e for the jth item index being calculatedj, calculate the difference property coefficient g of jth item indexj, wherein gj=1-ej；
According to the difference property coefficient g for the jth item index being calculatedj, determine the weight coefficient q of jth item indexj, wherein
6. a kind of confirmation system of Transmission Expansion Planning in Electric evaluating indexesto scheme weight, which is characterized in that the system comprises:
First weight coefficient assignment module, for the significance level according to achievement data each in index system, to each index
Assignment is carried out, the weight coefficient p of index j is obtainedj；
Second weight coefficient assignment module, for the dispersion degree according to achievement data each in index system, to each index
Assignment is carried out, the weight coefficient q of index j is obtainedj；
Comprehensive weight coefficients calculation block, for the weight coefficient p according to the index j being calculatedjWith weight coefficient qj,
And comprehensive weight calculation formula, the comprehensive weight coefficient ω of parameter jj, wherein the comprehensive weight calculation formula are as follows:
ωj=k1pj+k2qj, in formula, k1And k2For undetermined constant, meet k1>0、k2> 0 and k1+k2=1.
7. the confirmation system of Transmission Expansion Planning in Electric evaluating indexesto scheme weight according to claim 6, which is characterized in that described
First weight coefficient assignment module specifically includes:
Judgment matrix generation module is used in the index system, by each weight of the single index data based on evaluation goal
The property wanted carries out multilevel iudge two-by-two, generates judgment matrix A；
First weight coefficient confirmation module is used in the judgment matrix A, by maximum eigenvalue institute in the judgment matrix A
Operation is normalized in corresponding feature vector, and the parameter that normalization is obtained is as the power of index j in the index system
Weight coefficient pj。
8. the confirmation system of Transmission Expansion Planning in Electric evaluating indexesto scheme weight according to claim 7, which is characterized in that described
First weight coefficient assignment module further include:
Consistency judgment module, for carrying out consistency judgement to the judgment matrix A of generation；
Again assignment module, for when determining that the judgment matrix A is inconsistent, then being assigned again to the judgment matrix A
Value, and the step of returning to the judgment matrix A progress consistency judgement for executing described pair of generation；
When determining that the judgment matrix A meets consistency, then execution is described in the judgment matrix A, by the judgement square
The step of operation is normalized in feature vector corresponding to maximum eigenvalue in battle array A.
9. the confirmation system of Transmission Expansion Planning in Electric evaluating indexesto scheme weight according to claim 6, which is characterized in that described
First weight coefficient assignment module further include:
Index importance sequencing table generation module, it is raw for the significance level according to achievement data each in the index system
The index importance sequencing table X being displaced at an order relation；
Assignment module, for carrying out assignment to the significance level of each index, obtaining in the index importance sequencing table X
Numerical value pk；
Computing module, for according to index significance level weight calculation formula, the weight coefficient p of parameter jj, wherein it is described
Index significance level weight calculation formula are as follows:
ωk-1=rkωk, k=n, n-1 ..., 2, in formula, ri=pi-1/pi, i=2,3,4 ..., n.
10. according to power can require 7 or 9 described in Transmission Expansion Planning in Electric evaluating indexesto scheme weight confirmation system, feature exists
In the second weight coefficient assignment module specifically includes:
Aspect ratio re-computation module calculates jth item and refers to for the dispersion degree according to achievement data each in the index system
Under mark, the feature specific gravity p of i-th of power network objectij, in which:Wherein, xijIndicate i-th of electricity of jth item index
The achievement data of net object；
Entropy computing module, for according under the jth item index that is calculated, the feature specific gravity p of i-th of power network objectij, calculate
The entropy e of jth item indexj, whereinIn formula, k=1/ln m；
Otherness coefficients calculation block, for the entropy e according to the jth item index being calculatedj, calculate the difference of jth item index
Property coefficient gj, wherein gj=1-ej；
Second weight coefficient confirmation module, for the difference property coefficient g according to the jth item index being calculatedj, determine that jth item refers to
Target weight coefficient qj, wherein
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112766788A (en) * | 2021-01-29 | 2021-05-07 | 北京明略软件系统有限公司 | High-tech enterprise evaluation method, system, computer equipment and storage medium |
| CN113327062A (en) * | 2021-06-25 | 2021-08-31 | 贵州电网有限责任公司电力科学研究院 | Information grade determining method and device, computer equipment and storage medium |
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| CN103606115A (en) * | 2013-12-05 | 2014-02-26 | 国家电网公司 | Evaluation method of energy-saving type power grid |
| CN107330610A (en) * | 2017-06-28 | 2017-11-07 | 国网山东省电力公司经济技术研究院 | A kind of power network energy-saving and emission-reduction benefit method for quantitatively evaluating |
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| CN103606115A (en) * | 2013-12-05 | 2014-02-26 | 国家电网公司 | Evaluation method of energy-saving type power grid |
| CN107330610A (en) * | 2017-06-28 | 2017-11-07 | 国网山东省电力公司经济技术研究院 | A kind of power network energy-saving and emission-reduction benefit method for quantitatively evaluating |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112766788A (en) * | 2021-01-29 | 2021-05-07 | 北京明略软件系统有限公司 | High-tech enterprise evaluation method, system, computer equipment and storage medium |
| CN113327062A (en) * | 2021-06-25 | 2021-08-31 | 贵州电网有限责任公司电力科学研究院 | Information grade determining method and device, computer equipment and storage medium |
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