CN106384198A - Method for selecting evaluation indexes of transmission and transformation project of intelligent power grid - Google Patents
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Abstract
The invention discloses a method for selecting evaluation indexes of a transmission and transformation project of an intelligent power grid, and the method comprises the steps: selecting and scoring candidate evaluation indexes; constructing a structural entropy matrix; calculating and ordering the total acquaintance degrees of all candidate evaluation indexes; judging whether the static structural entropy matrix of the candidate evaluation indexes is suitable for factor analysis or not; obtaining the capability condition table, suitable for the factor analysis, of each common factor for the explanation of the total variance of the static structural entropy matrix, and extracting common factors with the feature values being greater than one; judging the maximum factor load of the candidate indexes and optimizing the maximum factor load; carrying out the standardization processing and combined credibility and average variance extraction inspection of candidate index factor load matrixes before and after optimization, and judging the reasonability of the candidate indexes; and selecting the optimized candidate indexes which pass through the verification as the final evaluation indexes. The method solves problems that the prior art is short of necessary data and the subjectivity in index selection is bigger, reduces the mutual redundancy in index evaluation, reduces the model computing and solving time, improves the precision, and is good in adaptability.
Description
Technical field
Present invention relates particularly to a kind of evaluation index choosing method of intelligent grid project of transmitting and converting electricity.
Background technology
Development with China's economic technology and the raising of people's living standard, electric energy has had become as people's daily life
In one of the requisite energy, and people are also increasing for the demand of electric energy.
And current, China's power grid construction and transformation lag behind China's expanding economy for a long time, there is existing Net Frame of Electric Network thin
Weak, conveying capacity is limited, the equipment general level of the health is low and the low problem of safety and economic operation level.Power department takes multiple sides
Formula strengthens electric network reconstruction technology, and develops intelligent grid.Wherein, engineering comprehensive evaluation is requisite part.Engineering comprehensive
Evaluation can prove the reference frame of the whether feasible offer science of project for project administrator, can strengthen to engineering construction simultaneously
The comprehensive management of project, provide reference and reference for same type engineering construction, and provide experience and religion for later project decision
Instruction, is favorably improved the returns of investment of project.
However, existing carry out overall merit to project of transmitting and converting electricity, during index for selection, generally do not account for presence between index
Correlation, and choose evaluation index only by the subjective experience of appraiser, and treat evaluation engineering and evaluated.Substantially
, the choosing method of existing evaluation index relies on subjective experience, leads to the random of selecting index and not scientific, and respectively
There may be redundancy between individual index thus have impact on speed and the precision of calculating, so that the workload of evaluation is increased.
Content of the invention
It is an object of the invention to provide a kind of intelligence electricity that is scientific and reasonable, considering relation between each evaluation index
The evaluation index choosing method of net project of transmitting and converting electricity.
The evaluation index choosing method of this intelligent grid project of transmitting and converting electricity that the present invention provides, comprises the steps：
S1. choose the candidate evaluations index of intelligent grid project of transmitting and converting electricity to be evaluated, and waited according to each by expert group
Select evaluation index that the significance level of intelligent grid project of transmitting and converting electricity to be evaluated is scored：Candidate evaluations index is to be evaluated
Intelligent grid project of transmitting and converting electricity importance bigger, then the scoring to candidate evaluations index is higher；
The score of each candidate's index S2. being obtained according to step S1, structural texture entropy matrix；
The structure entropy matrix of each candidate's index S3. being obtained according to step S2, calculates averagely recognizing of each candidate's index
Knowledge and magnanimity and understanding darkness, obtain the general cognition degree of each candidate's index, and each candidate's index are ranked up：Index total
Realization knowledge and magnanimity are less, illustrate that the information content of this index reflection is bigger, representative stronger；
S4. the static structure entropy matrix of candidate's index is standardized processing, and carries out appropriateness inspection and spherical inspection
Test, judge the static structure entropy matrix of each candidate's index if appropriate for carrying out factorial analysis：The value of appropriateness inspection is bigger, then get over
It is appropriate to factorial analysis；
S5. step S4 is confirmed to be appropriate to the static structure entropy matrix of factorial analysis, using PCA to time
Select index to carry out orthogonal rotation, obtain the capabilities might table that each common factor explains population variance, and extract the public affairs that characteristic value is more than 1
The factor；
S6. explain the capabilities might table of population variance according to each common factor that step S5 obtains, judge each candidate's index
Maximum factor loading, and be optimized according to the maximum factor loading of each candidate's index；
The Factor load-matrix of the candidate's index before and after the optimization that S7. step S6 obtains is standardized processing, then carries out
Combination reliability and the inspection of average variance extraction amount, judge the reasonability of candidate's selecting index；And to the candidate's index after optimizing
Test again, the evaluation index that the candidate upchecking selecting index is final intelligent grid project of transmitting and converting electricity.
Structural texture entropy matrix described in step S2, specifically includes following steps：
1) each expert constitutes an index set to the evaluation of candidate's index, is designated as U={ u1,u2,…,un, n is to wait
Select index number；This index set corresponding typical case sorting data is denoted as { ai1,ai2,…,ain}；It is made up of the index set of k position expert
Ordinal matrix be designated as A={ aij}k×n, wherein aijRepresent i-th expert evaluation to j-th index, i=1,2 ..., k；J=
1,2…,n；
2) construction entropy model is as follows：
In formula, μ (I) is aijCorresponding membership function value, I, m are Transformation Parameters amount, make I=q+1, m=q+2 then have
In formula, q is the importance ranking to candidate's index for the expert：What sequence was more forward shows project of transmitting and converting electricity is affected more
Greatly；Q value is n, and n is the number of candidate's index；
Can be obtained according to above formula：
By a in ordinal matrix AijIt is updated toIn, obtain aijStructure entropy bij(bij=μ
(aij)), it is consequently formed structure entropy matrix, be designated as B={ bij}k×n.
The general cognition of the average understanding degree, understanding darkness and candidate's index of each candidate's index of calculating described in step S3
Degree, specifically includes and includes following steps：
A. set k estimator to index μjRanking results identical, then to k estimator with regard to index μjAverage understanding
Degree is calculated, and is denoted as bj,
bj=(b1j+b2j+…+bkj)/k
B. define estimator to factor μjThe uncertainty being produced by cognition, referred to as recognizes darkness, is denoted as QjIt is clear that Qj≥
0；
Qj==| | max (b1j,b2j,…,bij)-bj|+|min(b1j,b2j,…,bij)-bj|}/2|
C. according to estimator with regard to index μjAverage understanding degree and understanding darkness, calculate k estimator to index μjTotal
Realization knowledge and magnanimity, are denoted as xj：
xj=bj(1-Qj)
D. by xjThe general cognition degree to given index for all estimators can be formed, be denoted as X, then X=(x1,x2,…,xn).
Described in step S4 appropriateness inspection and sphericity test be Kaiser-Meryer-Olkin sampling appropriateness inspection with
Bartlett sphericity test.
Judging whether described in step S4 is appropriate to factorial analysis, is when Kaiser-Meryer-Olkin sampling is suitable
Property inspection value be more than 0.6 when, be judged to be appropriate to factorial analysis.
Orthogonal described in step S5 rotates to be the orthogonal rotation of Varimax variance.
The maximum factor loading according to each candidate's index described in step S6 is optimized, for retaining each candidate's index
Candidate's index that middle maximum factor loading is more than 0.040, and other candidate's indexs are deleted.
The reasonability judging candidate's selecting index described in step S7, is to recognize when the combination reliability of candidate's index is more than 0.5
It is rational for this candidate's index.
The candidate's index after optimizing is tested again described in step S7, is that the candidate's index after optimizing is carried out
Kaiser-Meryer-Olkin sampling appropriateness inspection.
The evaluation index choosing method of this intelligent grid project of transmitting and converting electricity that the present invention provides, first adopts selection of specialists to wait
Select index, and candidate's index scored, then using mathematics and statistical method to selection of specialists and subjective scoring candidate
Index carries out selecting index, deletes and the less index of the project of transmitting and converting electricity degree of correlation, retains comment related to engineering evaluation core
Valency index, solves and lacks necessary data in prior art and selecting index has the disadvantage of larger subjectivity, simultaneously this
Bright method can effectively reduce the mutual redundancy in evaluation index, reduce the calculating of model and solve the time, increase result of calculation
Precision, and different engineering evaluation indexs can be formulated for different user or project, applicability is good.
Brief description
Fig. 1 is method of the present invention flow chart.
Specific embodiment
It is illustrated in figure 1 method of the present invention flow chart：The commenting of this intelligent grid project of transmitting and converting electricity that the present invention provides
Valency selecting index method, comprises the steps：
S1. choose the candidate evaluations index of intelligent grid project of transmitting and converting electricity to be evaluated, and waited according to each by expert group
Select evaluation index that the significance level of intelligent grid project of transmitting and converting electricity to be evaluated is scored：Candidate evaluations index is to be evaluated
Intelligent grid project of transmitting and converting electricity importance bigger, then the scoring to candidate evaluations index is higher；
The score of each candidate's index S2. being obtained according to step S1, structural texture entropy matrix：
1) each expert constitutes an index set to the evaluation of candidate's index, is designated as U={ u1,u2,…,un, n is to wait
Select index number；This index set corresponding typical case sorting data is denoted as { ai1,ai2,…,ain}；It is made up of the index set of k position expert
Ordinal matrix be designated as A={ aij}k×n, wherein aijRepresent i-th expert evaluation to j-th index, i=1,2 ..., k；J=
1,2…,n；
2) construction entropy model is as follows：
In formula, μ (I) is aijCorresponding membership function value, I, m are Transformation Parameters amount, make I=q+1, m=q+2 then have
In formula, q is the importance ranking to candidate's index for the expert：What sequence was more forward shows project of transmitting and converting electricity is affected more
Greatly；Q value is n, and n is the number of candidate's index；
Can be obtained according to above formula：
By a in ordinal matrix AijIt is updated toIn, obtain aijStructure entropy bij(bij=μ
(aij)), it is consequently formed structure entropy matrix, be designated as B={ bij}k×n；
The structure entropy matrix of each candidate's index S3. being obtained according to step S2, calculates averagely recognizing of each candidate's index
Knowledge and magnanimity and understanding darkness, obtain the general cognition degree of each candidate's index：
A. set k estimator to index μjRanking results identical, then to k estimator with regard to index μjAverage understanding
Degree is calculated, and is denoted as bj,
bj=(b1j+b2j+…+bkj)/k
B. define estimator to factor μjThe uncertainty being produced by cognition, referred to as recognizes darkness, is denoted as QjIt is clear that Qj≥
0；
Qj==| | max (b1j,b2j,…,bij)-bj|+|min(b1j,b2j,…,bij)-bj|}/2|
C. according to estimator with regard to index μjAverage understanding degree and understanding darkness, calculate k estimator to index μjTotal
Realization knowledge and magnanimity, are denoted as xj：
xj=bj(1-Qj)
D. by xjThe general cognition degree to given index for all estimators can be formed, be denoted as X, then X=(x1,x2,…,xn)；
After obtaining the general cognition degree of candidate's index, each candidate's index is ranked up：The general cognition degree of index is got over
Little, illustrate that the information content of this index reflection is bigger, representative stronger；
S4. the static structure entropy matrix of candidate's index is standardized processing, and carries out KMO (Kaiser-Meryer-
Olkin) the inspection of sampling appropriateness and Bartlett sphericity test, judge the static structure entropy matrix of each candidate's index if appropriate for
Carry out factorial analysis：The value of appropriateness inspection is bigger, then be more appropriate to factorial analysis, specially work as Kaiser-Meryer-
When the value of Olkin sampling appropriateness inspection is more than 0.6, it is judged to be appropriate to factorial analysis；
S5. step S4 is confirmed to be appropriate to the static structure entropy matrix of factorial analysis, using PCA to time
Select index to carry out the orthogonal rotation of Varimax variance, obtain the capabilities might table that each common factor explains population variance, and extract feature
The common factor more than 1 for the value；
S6. explain the capabilities might table of population variance according to each common factor that step S5 obtains, judge each candidate's index
Maximum factor loading, and be optimized according to the maximum factor loading of each candidate's index：Retain in each candidate's index
Candidate's index that big factor loading is more than 0.040, and other candidate's indexs are deleted；
The Factor load-matrix of the candidate's index before and after the optimization that S7. step S6 obtains is standardized processing, then carries out
Combination reliability and the inspection of average variance extraction amount, judge the reasonability of candidate's selecting index：The combination reliability of candidate's index is big
Think that this candidate's index is rational when 0.5；And Kaiser-Meryer-Olkin is carried out again to the candidate's index after optimizing
Sampling appropriateness inspection, the evaluation index that the candidate upchecking selecting index is final electrical network project of transmitting and converting electricity.
Below in conjunction with a specific embodiment, the present invention is further described：
The a certain project of transmitting and converting electricity to intelligent grid, chooses the evaluation index 18 of candidate, specifically as shown in table 1 altogether：
Table 1 candidate evaluations index illustrates table
The evaluation index asking 10 experts to be candidate altogether is scored, and the typical ordinal matrix being obtained according to appraisal result is such as
Shown in table 2：
Expert analysis mode typical case's ordinal matrix table of table 2 candidate evaluations index
Structural texture entropy matrix, calculates the average understanding degree of each candidate's index, recognizes darkness and calculate general cognition degree,
And according to general cognition degree, each candidate's index is ranked up, specifically as shown in table 3：
The structure entropy matrix sort table of each candidate's index of table 3
Static State Index structure entropy matrix through standardization is carried out with KMO (Kaiser-Meryer-Olkin) sampling
Appropriateness inspection and Bartlett sphericity test, assay shows, the KMO value of achievement data is spherical for 0.834, Bartlett
The χ of inspection2It is worth for 152.320 (free degree is 136).It is generally believed that when KMO value is more than 0.60, the availability of data is described
Higher, factorial analysis can be carried out.Afterwards, using PCA, the related data that the index judging primary election is gone or stayed is entered
The orthogonal rotation of row Varimax variance, obtains each common factor after orthogonal and explains population variance capabilities might table, such as table 4.Extract special
The common factor that value indicative is more than 1, wherein, the maximum explanation degree highest to intelligent grid project of transmitting and converting electricity of characteristic value.
Table 4 index common factor explains population variance capabilities might table
Explain the capabilities might table of population variance according to each common factor obtaining, judge the maximum factor of each candidate's index
Load, and be optimized according to the maximum factor loading of each candidate's index：Retain maximum factor loading in each candidate's index
Candidate's index more than 0.040, and other candidate's indexs are deleted, obtain Factor load-matrix and index optimization result such as table 5
Shown：
Table 5 Factor load-matrix and index optimization result
The Factor load-matrix of the candidate's index before and after the optimization obtaining is standardized processing, then is combined reliability
With the inspection of average variance extraction amount, judge the reasonability of candidate's selecting index：The combination reliability of candidate's index is recognized when being more than 0.5
It is rational for this candidate's index；And Kaiser-Meryer-Olkin sampling is carried out again suitably to the candidate's index after optimizing
Property inspection, the evaluation index that the candidate upchecking selecting index is final intelligent grid project of transmitting and converting electricity, concrete as table 6
Shown：
Table 6 intelligent grid project of transmitting and converting electricity optimum results
Claims (9)
1. a kind of evaluation index choosing method of intelligent grid project of transmitting and converting electricity, comprises the steps：
S1. choose the candidate evaluations index of intelligent grid project of transmitting and converting electricity to be evaluated, and commented according to each candidate by expert group
Valency index scores to the significance level of intelligent grid project of transmitting and converting electricity to be evaluated：Candidate evaluations index is to intelligence to be evaluated
The importance of energy electrical network project of transmitting and converting electricity is bigger, then the scoring to candidate evaluations index is higher；
The score of each candidate's index S2. being obtained according to step S1, structural texture entropy matrix；
The structure entropy matrix of each candidate's index S3. being obtained according to step S2, calculates the average understanding degree of each candidate's index
With understanding darkness, obtain the general cognition degree of each candidate's index, and each candidate's index is ranked up：Total realization of index
Knowledge and magnanimity are less, illustrate that the information content of this index reflection is bigger, representative stronger；
S4. the static structure entropy matrix of candidate's index is standardized processing, and carries out appropriateness inspection and sphericity test, sentence
The static structure entropy matrix of each candidate's index of breaking is if appropriate for carrying out factorial analysis：The value of appropriateness inspection is bigger, then more suitable
Carry out factorial analysis；
S5. step S4 is confirmed to be appropriate to the static structure entropy matrix of factorial analysis, using PCA, candidate is referred to
Mark carry out orthogonal rotation, obtain each common factor explain population variance capabilities might table, and extract characteristic value be more than 1 public affairs because
Son；
S6. explain the capabilities might table of population variance according to each common factor that step S5 obtains, judge each candidate's index
Big factor loading, and be optimized according to the maximum factor loading of each candidate's index；
The Factor load-matrix of the candidate's index before and after the optimization that S7. step S6 obtains is standardized processing, then is combined
Reliability and the inspection of average variance extraction amount, judge the reasonability of candidate's selecting index；And to the candidate's index after optimizing again
Test, the evaluation index that the candidate upchecking selecting index is final intelligent grid project of transmitting and converting electricity.
2. the evaluation index choosing method of intelligent grid project of transmitting and converting electricity according to claim 1 is it is characterised in that step
Structural texture entropy matrix described in S2 specifically includes following steps：
1) each expert constitutes an index set to the evaluation of candidate's index, is designated as U={ u1,u2,…,un, n refers to for candidate
Mark number；This index set corresponding typical case sorting data is denoted as { ai1,ai2,…,ain}；The row being made up of the index set of k position expert
Sequence matrix is designated as A={ aij}k×n, wherein aijRepresent i-th expert evaluation to j-th index, i=1,2 ..., k；J=1,
2…,n；
2) construction entropy model is as follows：
In formula, μ (I) is aijCorresponding membership function value, I, m are Transformation Parameters amount, make I=q+1, m=q+2 then have
In formula, q is the importance ranking to candidate's index for the expert：What sequence was more forward shows bigger on project of transmitting and converting electricity impact；q
Value is n, and n is the number of candidate's index；
Can be obtained according to above formula：
By a in ordinal matrix AijIt is updated toIn, obtain aijStructure entropy bij(bij=μ (aij)), by
This forms structure entropy matrix, is designated as B={ bij}k×n.
3. the evaluation index choosing method of intelligent grid project of transmitting and converting electricity according to claim 1 is it is characterised in that step
The general cognition degree of the average understanding degree, understanding darkness and candidate's index of each candidate's index of calculating described in S3 specifically includes and includes
Following steps：
A. set k estimator to index μjRanking results identical, then to k estimator with regard to index μjAverage understanding degree enter
Row calculates, and is denoted as bj,
bj=(b1j+b2j+…+bkj)/k
B. define estimator to factor μjThe uncertainty being produced by cognition, referred to as recognizes darkness, is denoted as QjIt is clear that Qj≥0；
Qj==| | max (b1j,b2j,…,bij)-bj|+|min(b1j,b2j,…,bij)-bj|}/2|
C. according to estimator with regard to index μjAverage understanding degree and understanding darkness, calculate k estimator to index μjTotal realization
Knowledge and magnanimity, are denoted as xj：
xj=bj(1-Qj)
D. by xjThe general cognition degree to given index for all estimators can be formed, be denoted as X, then X=(x1,x2,…,xn).
4. the evaluation index choosing method of the intelligent grid project of transmitting and converting electricity according to one of claims 1 to 3, its feature exists
Described in step S4 appropriateness inspection and sphericity test be Kaiser-Meryer-Olkin sampling appropriateness inspection with
Bartlett sphericity test.
5. the evaluation index choosing method of the intelligent grid project of transmitting and converting electricity according to one of claims 1 to 3, its feature exists
Judging whether described in step S4 is appropriate to factorial analysis, is when Kaiser-Meryer-Olkin sampling appropriateness inspection
Value be more than 0.6 when, be judged to be appropriate to factorial analysis.
6. the evaluation index choosing method of the intelligent grid project of transmitting and converting electricity according to one of claims 1 to 3, its feature exists
Orthogonal described in step S5 rotates to be the orthogonal rotation of Varimax variance.
7. the evaluation index choosing method of the intelligent grid project of transmitting and converting electricity according to one of claims 1 to 3, its feature exists
The maximum factor loading according to each candidate's index described in step S6 is optimized, maximum in each candidate's index for retaining
Candidate's index that factor loading is more than 0.040, and other candidate's indexs are deleted.
8. the evaluation index choosing method of the intelligent grid project of transmitting and converting electricity according to one of claims 1 to 3, its feature exists
The reasonability judging candidate's selecting index described in step S7, is to think this time when the combination reliability of candidate's index is more than 0.5
Index is selected to be rational.
9. the evaluation index choosing method of the intelligent grid project of transmitting and converting electricity according to one of claims 1 to 3, its feature exists
The candidate's index after optimizing is tested again described in step S7, is to carry out Kaiser- to the candidate's index after optimizing
Meryer-Olkin sampling appropriateness inspection.
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| CN110533340A (en) * | 2019-09-04 | 2019-12-03 | 国网黑龙江省电力有限公司电力科学研究院 | The quantization method of intelligent electric energy meter reliability index under a kind of typical environment |
| CN110853679A (en) * | 2019-10-23 | 2020-02-28 | 百度在线网络技术（北京）有限公司 | Speech synthesis evaluation method and device, electronic equipment and readable storage medium |
| CN110853679B (en) * | 2019-10-23 | 2022-06-28 | 百度在线网络技术（北京）有限公司 | Speech synthesis evaluation method and device, electronic equipment and readable storage medium |
| CN112070603A (en) * | 2020-09-11 | 2020-12-11 | 重庆誉存大数据科技有限公司 | Grading card model, configuration system thereof and grading processing method |
| CN112330179A (en) * | 2020-11-17 | 2021-02-05 | 华能国际电力股份有限公司上海石洞口第二电厂 | Fuzzy comprehensive evaluation method for coal blending combustion based on improved entropy weight method |
| CN112465242A (en) * | 2020-12-03 | 2021-03-09 | 华润电力技术研究院有限公司 | Thermal power plant operation optimization analysis method, device, equipment and storage medium |
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