CN104966244B - The Spearman rank correlation adaptive classification methods of the multi-disciplinary monitor control index of electric system - Google Patents
The Spearman rank correlation adaptive classification methods of the multi-disciplinary monitor control index of electric system Download PDFInfo
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- CN104966244B CN104966244B CN201510318900.5A CN201510318900A CN104966244B CN 104966244 B CN104966244 B CN 104966244B CN 201510318900 A CN201510318900 A CN 201510318900A CN 104966244 B CN104966244 B CN 104966244B
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- 230000003044 adaptive Effects 0.000 title claims abstract description 13
- 238000003646 Spearman's rank correlation coefficient Methods 0.000 claims abstract description 10
- 230000001808 coupling Effects 0.000 claims description 12
- 238000010168 coupling process Methods 0.000 claims description 12
- 238000005859 coupling reaction Methods 0.000 claims description 12
- 241001269238 Data Species 0.000 claims description 4
- 241000039077 Copula Species 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 description 6
- 230000000694 effects Effects 0.000 description 2
- 230000002452 interceptive Effects 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 206010010254 Concussion Diseases 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000001419 dependent Effects 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
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Abstract
A kind of Spearman rank correlation adaptive classification methods of the multi-disciplinary monitor control index of electric system, it is calculated using Spearman rank correlation coefficients, data between trans-departmental are calculated and analyzed, and classified according to classification ranking, calculate the threshold values of the related coefficient of all indexs pair, screening is more than all indexs pair of threshold values, the representative multi-disciplinary index pair of automatable acquisition.The present invention provide it is a kind of effectively analyze it is trans-departmental between data, the Spearman rank correlation adaptive classification methods of the multi-disciplinary monitor control index of the electric system of maximizing the benefits.
Description
Technical field
The present invention relates to electric power supervisory control field, the Spearman of especially a kind of multi-disciplinary monitor control index of electric system
Rank correlation adaptive classification method.
Background technology
With the quick variation of management environment outside grid company, power grid enterprises are faced with the decline of society's electricity consumption amount speedup,
The unfavorable situation that income increase is slowed down.Therefore power grid enterprises are needed from the visual angle of company's sustainable development, to the operation shape of company
Condition carries out of overall importance, comprehensive analysis, finds ability short slab present in company operation, policymaker is enable to formulate accordingly
Strategy eliminates ability short slab.It is also desirable to during daily dynamic operation, can continuously, the hair of agility
Unusual fluctuation present in existing company operation, traces reason, enables a company to dynamically adjust own operations ability, tackles quick variation
Inside and outside portion's environment.
Provincial Utilities Electric Co. needs to have carried out company operation dynamic the monitoring daily paper of normalization, the monthly operation dynamic of company
Analysis report etc. analyzes work, and preliminary support is formd to the assurance of company operation situation to company leader.Except finding out energy
Decision-making is enough supported, judges the important indicator of operation state, we also want to find the coupling index of multi-disciplinary, this often holds
Easily ignored by people, but really need to be taken seriously.These associations tend to that us is aided in more clearly to get a grip on, because
This analyzes different inter-sectional indexs, and the relevance between finding out just seems abnormal urgent.
The content of the invention
In order to overcome the shortcomings of existing power system monitoring mode can not effectively analyze it is trans-departmental between data, this hair
It is bright provide it is a kind of effectively analyze it is trans-departmental between data, the electric system of maximizing the benefits multi-disciplinary monitor control index
Spearman rank correlation adaptive classification methods.
The technical solution adopted by the present invention to solve the technical problems is：
A kind of Spearman rank correlation adaptive classification methods of the multi-disciplinary monitor control index of electric system, the method bag
Include following steps：
(1) the n achievement data of the same quarter is extracted respectively from the database of m different majors, n represents index quantity
The index total amount of most specialized databases；
(2) classifying and numbering is carried out to the index from different majors, and data is added in into set XS={ xij| i=1,2 ... m
J=1,2 ... n }, xijThat is in i-th of specialty j-th season achievement data；
(3) rank correlation coefficient of multi-disciplinary index pair calculates
(3.1) two specialties e, f are arbitrarily chosen in m specialty first；
(3.2) and then in professional e arbitrarily choose an index and be denoted as a, and a digit synbol is arbitrarily chosen in professional f
Make b；
(3.3) the two Spearman rank correlation coefficients are calculated to selecting the two multi-disciplinary index a come and b, if C (u,
V) function, wherein parameter u and parameter v are calculated all referring to data are marked for Copula rank value, then rank correlation coefficient calculation formulaAnd income value will be calculated and add in set TS={ teafb| e ≠ f=1,2 ... m a ≠ b=1,
2 ... n }, teafbThat is achievement data xeaWith achievement data xfbSpearman rank correlation coefficient values；
(3.4) from step (3.2) start the cycle over operation up in any index in specialty e and specialty f all indexs all into
Spearman rank correlation coefficients of having gone calculate；
(3.5) operation is started the cycle over up to all m specialties are all selected two-by-two from step (3.1)；
(3.6) obtain recording the set TS of the rank correlation coefficient of all indexs pair；
(4) associated index pair is screened
(4.1) descending operation is carried out to set TS, is arranged from big to small by the value of t；
(4.2) quadratic sum of all t in set is taken then to open radical sign, obtained result is denoted as Δ t, i.e. threshold value；
(4.3) all t for being more than threshold value in set TS are taken outeafb, index pair that these rank correlation coefficient subscripts are marked
The multi-disciplinary coupling index pair that i.e. we are found；
(5) coupling index is submitted to data
(5.1) all achievement data x for the multi-disciplinary coupling index pair found out in set XS；
(5.2) by these achievement datas by index to for grouping, and be stored into database.
The present invention technical concept be：The present invention devises a kind of Sperman orders of the multi-disciplinary monitor control index of electric system
Dependent adaptive is classified.During actual analysis, we extract together from the different majors database of different departments respectively
The indicator-specific statistics data of the first quarter, these certain multi-disciplinary data analyses are no longer simple Linear correlative analysis, we adopt
With Spearman rank correlation, what rank correlation reflected is the dull dependence between variable, therefore is kept under Nonlinear Monotone variation
Constant, statistical property is due to linear correlation.Then we obtain the rank correlation coefficient of all multi-disciplinary indexs pair, according to ours
Scheme finds out threshold value, takes all indexs pair more than threshold value, these indexs to be exactly it is considered that multi-disciplinary associated index pair,
And the statistics of these indexs is submitted into database.This invention is calculated with rank correlation coefficient, is calculated between different majors
Index relevance, and by our screening scheme, find out it is considered that associating strong multi-disciplinary index pair.These indexs
Contacting and interacting disclosing different departments, supplement and company to a certain extent are for the assurance of operation, for neck
Conducting shell decision-making provides thinking and direction, effect is contributed to strengthen management, in time adjustment operation, and benefit is realized in concussion of avoiding risk
It maximizes.
Beneficial effects of the present invention are mainly manifested in：It is calculated using Spearman rank correlation coefficients, between trans-departmental
Data are calculated and analyzed, and are classified according to classification ranking, are calculated the threshold value of the related coefficient of all indexs pair, are sieved
Choosing is more than all indexs pair of threshold value, the representative multi-disciplinary index pair of automatable acquisition；Maximizing the benefits, auxiliary
Decision-making is analyzed comprehensively.
Description of the drawings
Fig. 1 is the flow chart of the Spearman rank correlation adaptive classification methods of the multi-disciplinary monitor control index of electric system.
Fig. 2 is the structure of the Spearman rank correlation adaptive classification optimization systems of the multi-disciplinary monitor control index of electric system
Figure.
Specific embodiment
The invention will be further described below in conjunction with the accompanying drawings.
Referring to Figures 1 and 2, the Spearman rank correlation adaptive classification side of the multi-disciplinary monitor control index of a kind of electric system
Method comprises the following steps：
The first step：Extract the n achievement data of the same quarter respectively from the database of m different majors.
Second step：Classifying and numbering is carried out to the index from different majors, and data are added in into set XS={ xij| i=1,
2 ... mj=1,2 ... n }, xijThat is in i-th of specialty j-th season achievement data.
3rd step：Two specialties e, f are arbitrarily chosen in m specialty.
4th step：An optional index a in professional e, an optional index b in professional f.
5th step：Multi-disciplinary two indices are calculated with the calculating of its Spearman rank correlation coefficient, if C (u, v) is
Copula rank value calculates function, wherein parameter u and parameter v all referring to data are marked, then rank correlation coefficient calculation formulaAnd add in set TS={ teafb| e ≠ f=1,2 ... ma ≠ b=1,2 ... n }, teafbI.e. specially
In industry e in index a and specialty f index b Spearman rank correlation coefficient values.
6th step：Judge in specialty e whether any index with all indexs in professional f all carries out Spearman rank correlation system
Number calculates.If so, it carries out in next step.If it is not, return to the 4th step.
7th step：Judge whether m specialty is all selected two-by-two.If so, it carries out in next step.If it is not, then return to the 3rd
Step.
8th step：Descending operation is carried out to set TS, is arranged from big to small by t values.
9th step：The quadratic sum of all t in set is taken then to open radical sign, obtained result is denoted as Δ t, i.e. threshold value.
Tenth step：Take out all t for being more than threshold value in set TSeafb, index that these rank correlation coefficient subscripts are marked
To the multi-disciplinary coupling index pair that i.e. we are found.
11st step：The multi-disciplinary coupling index found out in set XS is to obtaining all achievement datas.
12nd step：By these achievement datas by index to being stored into after grouping in database.
With reference to Fig. 2, the Spearman rank correlation using the multi-disciplinary monitor control index of electric system of this method realization is adaptive
Classified optimization system, mainly includes：The rank correlation coefficient computing module of multi-disciplinary index pair, the associated index of screening to module,
Coupling index is submitted to data module, user interactive module.
(1) the rank correlation coefficient computing module of multi-disciplinary index pair：Spearman order phases are carried out to multi-disciplinary achievement data
Relation number calculates.
(2) associated index is screened to module：All rank correlation coefficients are squared and are opened with radical sign operation, obtains threshold
Value.Take all indexs pair more than threshold value, these indexs, that is, multi-disciplinary coupling index pair.
(3) coupling index is submitted to data module：The data of these indexs pair are found out, data put forward form according to index
Give database.
(4) user interactive module：FTP client FTP configures, index analysis result, and data visualization displaying, index analysis is calculated
Method instrument.
Claims (1)
1. a kind of Spearman rank correlation adaptive classification methods of the multi-disciplinary monitor control index of electric system, it is characterised in that：Institute
The method stated comprises the following steps：
(1) the n achievement data of the same quarter is extracted respectively from the database of m different majors, n represents that index quantity is most
Specialized database index total amount；
(2) classifying and numbering is carried out to the index from different majors, and data is added in into set XS={ xij| i=1,2 ... m j=
1,2 ... n }, xijThat is in i-th of specialty j-th season achievement data；
(3) rank correlation coefficient of multi-disciplinary index pair calculates
(3.1) two specialties e, f are arbitrarily chosen in m specialty first；
(3.2) and then in professional e arbitrarily choose an index and be denoted as a, and arbitrarily choose an index in professional f and be denoted as b；
(3.3) the two Spearman rank correlation coefficients are calculated to selecting the two multi-disciplinary index a come and b, if C (u, v) is
Copula rank value calculates function, wherein parameter u and parameter v all referring to data are marked, then rank correlation coefficient calculation formulaAnd income value will be calculated and add in set TS={ teafb| e ≠ f=1,2 ... m a ≠ b=1,
2 ... n }, teafbThat is achievement data xeaWith achievement data xfbSpearman rank correlation coefficient values；
(3.4) start the cycle over and operated up to all indexs are all carried out in any index in specialty e and specialty f from step (3.2)
Spearman rank correlation coefficients calculate；
(3.5) operation is started the cycle over up to all m specialties are all selected two-by-two from step (3.1)；
(3.6) obtain recording the set TS of the rank correlation coefficient of all indexs pair；
(4) associated index pair is screened
(4.1) descending operation is carried out to set TS, by teafbValue arrange from big to small；
(4.2) all t in set are takeneafbQuadratic sum then open radical sign, obtained result is denoted as Δ t, i.e. threshold value；
(4.3) all t for being more than threshold value in set TS are taken outeafb, the index that these rank correlation coefficient subscripts are marked is to being sought
The multi-disciplinary coupling index pair looked for；
(5) coupling index is submitted to data
(5.1) all achievement data x for the multi-disciplinary coupling index pair found out in set XS；
(5.2) by these achievement datas by index to for grouping, and be stored into database.
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| CN104966244B true CN104966244B (en) | 2018-06-01 |
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103020423A (en) * | 2012-11-21 | 2013-04-03 | 华中科技大学 | Copula-function-based method for acquiring relevant characteristic of wind power plant capacity |
| CN103207944A (en) * | 2013-02-04 | 2013-07-17 | 国家电网公司 | Electric power statistical index relevance analysis method |
| CN104182583A (en) * | 2014-08-22 | 2014-12-03 | 国家电网公司 | Distribution network device status indicator weight analysis method based on conjoint analysis |
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103020423A (en) * | 2012-11-21 | 2013-04-03 | 华中科技大学 | Copula-function-based method for acquiring relevant characteristic of wind power plant capacity |
| CN103207944A (en) * | 2013-02-04 | 2013-07-17 | 国家电网公司 | Electric power statistical index relevance analysis method |
| CN104182583A (en) * | 2014-08-22 | 2014-12-03 | 国家电网公司 | Distribution network device status indicator weight analysis method based on conjoint analysis |
Non-Patent Citations (2)
| Title |
|---|
| Spearman等级相关系数计算公式及其相互关系的探讨;何艳频等;《中国现代药物应用》;20080324;第1卷(第7期);第72-73页 * |
| 电力建设项目经济评价指标分类比较;高金凤等;《能源技术经济》;20100910;第22卷(第8期);第46-49页 * |
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Effective date of registration: 20201112 Address after: 11th floor, donglecheng international, Shuguang Road, Chengguan Street, Dongming County, Heze City, Shandong Province Patentee after: Heze Jianshu Intelligent Technology Co., Ltd Address before: The city Zhaohui six districts Chao Wang Road Hangzhou city Zhejiang province Zhejiang University of Technology No. 18 310014 Patentee before: ZHEJIANG University OF TECHNOLOGY |