CN107563665A - A kind of electric power facility distribution and power network resources quality testing method - Google Patents
A kind of electric power facility distribution and power network resources quality testing method Download PDFInfo
- Publication number
- CN107563665A CN107563665A CN201710840748.6A CN201710840748A CN107563665A CN 107563665 A CN107563665 A CN 107563665A CN 201710840748 A CN201710840748 A CN 201710840748A CN 107563665 A CN107563665 A CN 107563665A
- Authority
- CN
- China
- Prior art keywords
- data
- facility
- electric power
- resource
- evaluation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a kind of distribution of electric power facility and power network resources quality testing method, it is related to power equipment and managing power network resources technical field.Including following process：SS01 gathers evaluating data；SS02 facilities and resource points data target distributed model；SS03 establishes facility total amount and derives model；SS04 establishes electric power gallery course confidence level computation model；SS05 establishes evaluation index.The present invention is by big data cluster analysis mode, and depth excavates the relation factor of electric power gallery and facility resource data quality problems, focus issues, dissects reason, there is provided a kind of key issue of rapidly locating quality, and the method for gradual perfection quality evaluation.
Description
Technical field
The invention belongs to Power Communication Resources assessment technique field, is provided more particularly to a kind of distribution of electric power facility with power network
Source data quality evaluating method.
Background technology
Communication equipment is divided into pipe rod road network, cable system, cable network, computer room space by traditional communication resource management system
With device resource, and transmission network, access network, switching network, data network, dynamic environment, clock are further subdivided on this basis
Synchronization, microwave etc., this is determined by the network size of conventional telecommunications operator, business scale and business model.
Power telecom network is similar with traditional communication net, can also be classified in the way described above, but to electric power enterprise and
Speech, because the network size and operational mode of communication network have differences with conventional telecommunications operator, and specific business demand
Also there is larger difference, so, with reference to the practical application feature of electric power enterprise, power telecom network can be divided into supporting network, optical cable
Net, station equipment, light path, circuit, it is other temporarily regardless of also without subdivision.
The shortcomings that market similar system：On quality evaluating method, evaluation on the market it is more in the form of conventional statistic based on,
Common statistical method is (wrong data/data total amount) × 100%, and the quality for ignoring a variety of latitudes of same category of device or angle is commented
Valency, ignore quality of data analysis of Influential Factors, without can assistant analysis, positioning emphasis data problem ability；
In functions of modules, common statistics pie chart, block diagram with (wrong data/data total amount) index result is shown as
It is main, omit the most concerned key quality problem of user, and the analysis performance to quality association influence factor.
The content of the invention
It is an object of the invention to provide a kind of distribution of electric power facility and power network resources quality testing method.
In order to solve the above technical problems, the present invention is achieved by the following technical solutions：
The present invention is a kind of distribution of electric power facility and power network resources quality testing method, including following process：
SS01 gathers evaluating data；
SS02 facilities and resource points data target distributed model；
SS03 establishes facility total amount and derives model：Using the clustering algorithm in data mining, evaluation same class facility is not
The quality weighing factor of same source data system, the source data quality for drawing similar facility by high arrangement on earth according to weighing factor arrange
Table, establish the measures of dispersion per a kind of facility, analog quantity, equal amount and handle model；
SS04 establishes electric power gallery course confidence level computation model, judges cable louding when that can not use power technology means
On the premise of, the credibility according to business datum drafting electric power gallery route contact；
SS05 establishes evaluation index；
SS06 draws evaluation result.
Further, evaluating data includes facility data, resource data and path data in the SS01；
Wherein, the facility data includes transformer station, switching station, ring main unit, public change, high voltage customer, shaft tower, Gong Jing；
Wherein, the resource data connects position, work well casing hole resource including interval resource, shaft tower loop and T；
Wherein, the path data includes power transmission and distribution supply path line topological.
Further, the SS04 establishes electric power gallery course confidence level computation model, with reference to GIS application demands and data
Multidimensional index Environmental Evaluation Model it is specific as follows：
The evaluating data established according to SS01：
A paths interconnection data reliability, i.e. the GIS electric power gallery line route degree of accuracy；
B electric power facilities and resource points data reliability, including accuracy, logicality, information integrity, normalization；
C coverage rates；
By analyzing accuracy, logicality, information integrity, normalization, the coverage rate of electric power facility and resource data, with
And the GIS electric power gallery line routes degree of accuracy totally 6 latitudes, each latitude according to business scenario to data value demand not
Together, evaluation index is established.
Further, it is as follows to establish facility total amount derivation model detailed process by the SS03：
A1 obtains evaluating data；
A2 assesses the weighing factor of A1 such data by big data cluster analysis；
B1 judges whether it is standardized data
If standardized data, then
Step 1, evaluating data is compareed between multi-source system；
Step 2, it is control foundation with the operation numbering of standardization, analyzes identical, similar, difference facility；
Step 3, merged using measures of dispersion, analog quantity according to cluster preferentially, equal amount superposition method, derive total quantity；
If not standardized data part, then
Step 1, quantity is lacked using business rule fuzzy inference；
Step 2, the fuzzy value is with quantity sum in system as derivation total quantity.
Further, the multi-source system includes PMS systems, the main distribution of Scada systems, Electric Energy Acquisition System, battalion
Pin system.
Further, the SS04 establishes electric power gallery course confidence level computation model and specifically includes following process：
C01, establish electric power facility contact data；
C02, calculated using shortest path；
Arterial highway, major trunk roads, subsidiary road, branch road priority principle, move towards calculate；
The preferential calculating principle of pipe well；
Cable route nameplate data record；
Shaft tower loop data；
C03, optimal degree of conformity algorithm extraction；
C04, believable line route.
Further, the SS05 establish evaluation result include facility and resource interconnection data evaluation result, facility with
Resource points data evaluation result, facility coverage rate result, Key Quality analysis of Influential Factors result；The facility is got in touch with resource
Line number generates integrated data quality evaluation point according to evaluation result, facility and resource points data evaluation result, facility coverage rate result
Analysis report；The Key Quality analysis of Influential Factors result generation critical factor analysis report.
The present invention principle be：The object of quality testing is gallery systematic electricity facility and resource data, contact (road
Footpath, topology) data, Appreciation gist is every traffic criteria, the technical standard of data application, and overall assessment method is marked by items
The overall assessment index and corresponding ratio that standard is formulated reassemble into, by some analysis means of big data, by multi-level, multidimensional
Quality evaluation, management and control Hefei electric company electric power gallery and facility and its resource base data, contact (path, topology) number
According to, ensure data accuracy, normalization, integrality, provide technology branch for management works such as Electric Power Network Planning, resource distribution applications
Support.
The invention has the advantages that：
1. the present invention is according to business scenario, the clearly demand to business datum, the value using business demand data is leads
To, by quantifying data quality standard, assess the quality of data, so as to aid in user grasp the key link data quality problems simultaneously
Specific aim solves.
2. the present invention excavates electric power gallery and facility resource data quality problems by big data cluster analysis mode, depth
Relation factor, focus issues, dissect reason, there is provided a kind of key issue of rapidly locating quality, and gradual perfection matter
The method for measuring evaluation.
Certainly, any product for implementing the present invention it is not absolutely required to reach all the above advantage simultaneously.
Brief description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, used required for being described below to embodiment
Accompanying drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the present invention, for ability
For the those of ordinary skill of domain, on the premise of not paying creative work, it can also be obtained according to these accompanying drawings other attached
Figure.
Fig. 1 is a kind of distribution of electric power facility and the power network resources quality testing method frame figure of the present invention；
Fig. 2 is that facility total amount derives model flow figure；
Fig. 3 is electric power gallery confidence level computation model figure.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, rather than whole embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art are obtained all other under the premise of creative work is not made
Embodiment, belong to the scope of protection of the invention.
Embodiment one
The present invention is a kind of distribution of electric power facility and power network resources quality testing method, including following process：
SS01 gathers evaluating data；Evaluating data includes facility data, resource data and path data；Wherein, facility number
According to including transformer station, switching station, ring main unit, public change, high voltage customer, shaft tower, Gong Jing；Resource data includes interval resource, shaft tower
Loop connects position, work well casing hole resource with T；Path data includes power transmission and distribution supply path line topological.
SS02 establishes facility and resource points data target distributed model；
SS03 establishes facility total amount and derives model：Using the clustering algorithm in data mining, evaluation same class facility is not
The quality weighing factor of same source data system, the source data quality for drawing similar facility by high arrangement on earth according to weighing factor arrange
Table, establish the measures of dispersion per a kind of facility, analog quantity, equal amount and handle model；
SS04 establishes electric power gallery course confidence level computation model, judges cable louding when that can not use power technology means
On the premise of, the credibility according to business datum drafting electric power gallery route contact；
SS05 establishes evaluation index；
SS06 draws evaluation result.
Refer to shown in Fig. 1, establish and introduce GIS electric power gallery routes trust evaluation, with reference to GIS application demands and data
Multidimensional index Environmental Evaluation Model it is specific as follows：
The evaluating data established according to SS01 is established：
A paths interconnection data reliability, i.e. the GIS electric power gallery line route degree of accuracy；
B electric power facilities and resource points data reliability, including accuracy, logicality, information integrity, normalization；
C coverage rates；
By analyzing accuracy, logicality, information integrity, normalization, the coverage rate of electric power facility and resource data, with
And the GIS electric power gallery line routes degree of accuracy totally 6 latitudes, each latitude according to business scenario to data value demand not
Together, evaluation index is established.
Each latitude is according to industry such as resources configuration management, planning application, engineering management, operational program management, O＆M maintenance
Scene of being engaged in is to the difference of data value demand, in transformer station and interval and bus, opening and closing interval and bus in one's power, ring main unit and
Every and bus, public affairs become, high voltage customer, shaft tower, work well, major network circuit, the title of distribution line etc. facility and resource, numbering,
GIS coordinates, T contacts, capacity, communication relationship, contact (path, topology), CT no-load voltage ratios, voltage class, resource type, money between facility
There is different evaluation emphasis on the more category informations of source state etc..The model realizes that data value identifies by business scenario,
So as to realize quality evaluation and high value priority ordering to different business value data.
Refer to shown in Fig. 2, it is as follows to establish facility total amount derivation model detailed process：
A1 obtains evaluating data；
A2 assesses the weighing factor of A1 such data by big data cluster analysis；
B1 judges whether it is standardized data
If standardized data, then
Step 1, evaluating data is compareed between multi-source system；Wherein, multi-source system include PMS systems,
The main distribution of Scada systems, Electric Energy Acquisition System, marketing system.
Step 2, it is control foundation with the operation numbering of standardization, analyzes identical, similar, difference facility；
Step 3, merged using measures of dispersion, analog quantity according to cluster preferentially, equal amount superposition method, derive total quantity；
If not standardized data part, then
Step 1, quantity is lacked using business rule fuzzy inference；Such as identify that the length of every section of bar line is in reasonable model
In enclosing, or recognize whether not cross the suspension circuit of shaft tower, that is, think that shaft tower does not lack, otherwise think to have shaft tower in the presence of scarce
Lose, with reference to the average distance theoretical value of bar line, fuzzy inference missing quantity；
Step 2, the fuzzy value is with quantity sum in system as derivation total quantity.
SS04 establishes electric power gallery course confidence level computation model, judges cable louding that can not use power technology means
On the premise of, it is directly used in the credibility that the contact of electric power gallery route is drawn in evaluation only in accordance with business datum；
Refer to shown in Fig. 3, establish the electric power gallery route confidence level computation model based on GIS and specifically include mistake as follows
Journey：
C01, establish electric power facility contact data；
C02, calculated using shortest path；
Arterial highway, major trunk roads, subsidiary road, branch road priority principle, move towards calculate；
The preferential calculating principle of pipe well；
Cable route nameplate data record；
Shaft tower loop data；
C03, optimal degree of conformity algorithm extraction；
C04, believable line route.
SS05 establishes evaluation result.Establish evaluation result include facility and resource interconnection data evaluation result, facility with
Resource points data evaluation result, facility coverage rate result, Key Quality analysis of Influential Factors result；The facility is got in touch with resource
Line number generates integrated data quality evaluation point according to evaluation result, facility and resource points data evaluation result, facility coverage rate result
Analysis report；The Key Quality analysis of Influential Factors result generation critical factor analysis report.
The present invention principle be：The object of quality testing is gallery systematic electricity facility and resource data, contact (road
Footpath, topology) data, Appreciation gist is every traffic criteria, the technical standard of data application, and overall assessment method is marked by items
The overall assessment index and corresponding ratio that standard is formulated reassemble into, by some analysis means of big data, by multi-level, multidimensional
Quality evaluation, management and control Hefei electric company electric power gallery and facility and its resource base data, contact (path, topology) number
According to, ensure data accuracy, normalization, integrality, provide technology branch for management works such as Electric Power Network Planning, resource distribution applications
Support.
Embodiment two
Evaluation object is divided into two major classes, is respectively：Electric power facility and resource data, get in touch with (path, topology) data.
Multiple systems simultaneously from high to low, with the data where mark I come by when containing facilities information, I, II, III expression priority
Source is standard.
(1) electric power facility evaluation object be divided into transformer station, switching station, ring main unit, public change, high voltage customer, shaft tower, Gong Jing,
Major network circuit, distribution line totally nine class；Resource data object is that interval resource, shaft tower loop and T connect position, work well casing hole money
Source.
(2) it is power transmission and distribution supply path, line topological to get in touch with (path, topology) data evaluation object.
Evaluation index is divided into three major types, respectively coverage rate, facility and resource points data reliability, and path contact data can
Reliability.Coverage rate evaluates facility and the level of coverage of resource；Electric power facility and resource points data reliability accuracy, logic
Property, information integrity, normative common evaluation；The credibility of path contact data trust evaluation contact (path, topology),
And comprehensive evaluation value is provided according to weight.
All kinds of facility total amounts fail grasp objective value in the case of, using integrated evaluating method evaluate coverage rate etc.
Level distribution, finally using coverage rate grade point evaluation coverage rate.
Distribution of grades is：
| Grade point | Grade explanation |
| 1 grade | 0%<=,<10% |
| 2 grades | 10%<=,<20% |
| 3 grades | 20%<=,<30% |
| 4 grades | 30%<=,<40% |
| 5 grades | 40%<=,<50% |
| 6 grades | 50%<=,<60% |
| 7 grades | 60%<=,<70% |
| 8 grades | 70%<=,<80% |
| 9 grades | 80%<=,<90% |
| 10 grades | 90%<=,<=100% |
Coverage rate=(quantity of typing of any sort electric power facility or resource/facility derives total quantity in system) ×
100%, or=1- (derivation missing quantity/facility of any sort electric power facility or resource derives total quantity in system) ×
100%.
According to the distribution of grades of coverage rate, the grade point of coverage rate is provided.Trust evaluation index classification content is as follows：
In the evaluation index, it is as follows to derive missing quantity, the method for derivation facility total quantity：
Facility and resource points data reliability evaluation index categorised content are as follows：
Index calculating method：
Facility and resource points data reliability=(accuracy rate × 0.40+ logicalities rate × 0.40+ message completion rates ×
0.10+ normalizations rate × 0.10) × 100%.
(index object mistake bar number add up to × is commented by accuracy rate, logicality rate, information integrity rate, normative rate=1-
Valency weight/index object total quantity).
(3) path contact data confidence level target computational methods are as follows：
Path contact data confidence level=credible circuit number/circuit sum.
(4) indexes weight design：
In summary index calculating method, design objective calculate weight and are：Electric power facility data, resource data evaluation index
In, the evaluation weight of significant data problem quality and general data problem quality is 0.8:0.2；Electric power facility data, number of resources
It is 0.8 according to evaluation index and contact (path, topology) data evaluation index weights ratio:0.2.
Quantity (the significant data element question and general of evaluation procedure data, electric power facility and resource metrics classification problem
Data Elements problem uses X/Y forms) and derivation total quantity：
Wherein, accuracy=1- (2 × 0.8+0 × 0.2+0 × 0.8+3 × 0.2+0 × 0.8+1 × 0.2+2 × 0.8+0 ×
0.2+0×0.8+3×0.2+0×0.8+1×0.2+2×0.8+0×0.2+0×0.8+30×0.2+0×0.8+1×0.2+0
×0.8+130×0.2+10×0.8+0×0.2+0×0.8+0×0.2+11×0.8+0×0.2)/(25+580+46+25+288
+ 3409+598+288+130+1021+330+130+801+8306+890+14+255)=0.92
Logicality=1- (4 × 0.8+0 × 0.2+4 × 0.8+0 × 0.2+4 × 0.8+0 × 0.2+10 × 0.8+0 × 0.2+0
×0.8+210×0.2+0×0.8+20×0.2+20×0.8+0×0.2)/(25+580+46+25+288+3409+598+288+
130+1021+330+130+801+8306+890+14+255)=0.87
Information integrity=1- (0 × 0.8+0 × 0.2+0 × 0.8+10 × 0.2+0 × 0.8+0 × 0.2+0 × 0.8+10 ×
0.2+0×0.8+0×0.2+0×0.8+10×0.2+12×0.8+0×0.2+10×0.8+0×0.2+11×0.8+0×0.2
+0×0.8+0×0.2)/(25+580+46+25+288+3409+598+288+130+1021+330+130+801+8306+890+
14+255)=0.73
Normalization=1- (1 × 0.8+0 × 0.2+30 × 0.8+0 × 0.2+3 × 0.8+0 × 0.2+1 × 0.8+0 × 0.2+
60×0.8+0×0.2+3×0.8+0×0.2+1×0.8+0×0.2+130×0.8+0×0.2+30×0.8+0×0.2+24
×0.8+0×0.2+12×0.8+0×0.2+13×0.8+0×0.2)/(25+580+46+25+288+3409+598+288+
130+1021+330+130+801+8306+890+14+255)=0.69
Confidence level=(accuracy rate × 0.40+ logicalities rate × 0.40+ message completion rates × 0.10+ normalizations rate ×
0.10) × 100%=(0.92 × 0.40+0.87 × 0.40+0.73 × 0.10+0.69 × 0.10) × 100%=85.8%
Coverage rate=(25+580+46+25+288+3409+598+288+130+1021+330+130+801+8306+ 890+
14+255)/(25+580+46+25+288+3409+598+288+130+1021+330+130+801+8306+890+14+255)
=17136/18511=0.9257=10 levels
Electric power gallery and facility and its resource base data, ensure data accuracy, normalization, integrality, advised for power network
Draw, the management work such as resource distribution application provides technical support.
In the description of this specification, the description of reference term " one embodiment ", " example ", " specific example " etc. means
At least one implementation of the present invention is contained in reference to specific features, structure, material or the feature that the embodiment or example describe
In example or example.In this manual, identical embodiment or example are not necessarily referring to the schematic representation of above-mentioned term.
Moreover, specific features, structure, material or the feature of description can close in any one or more embodiments or example
Suitable mode combines.
Present invention disclosed above preferred embodiment is only intended to help and illustrates the present invention.Preferred embodiment is not detailed
All details are described, it is only described embodiment also not limit the invention.Obviously, according to the content of this specification,
It can make many modifications and variations.This specification is chosen and specifically describes these embodiments, is to preferably explain the present invention
Principle and practical application so that skilled artisan can be best understood by and utilize the present invention.The present invention is only
Limited by claims and its four corner and equivalent.
Claims (7)
1. a kind of electric power facility distribution and power network resources quality testing method, it is characterised in that including following process：
SS01 gathers evaluating data；
SS02 facilities and resource points data target distributed model；
SS03 establishes facility total amount and derives model：Using the clustering algorithm in data mining, evaluation same class facility is not homologous
The quality weighing factor of data system, the source data quality list of similar facility is drawn by high arrangement on earth according to weighing factor,
Establish the measures of dispersion per a kind of facility, analog quantity, equal amount and handle model；
SS04 establishes electric power gallery course confidence level computation model, before power technology means can not be used to judge cable louding
Put, the credibility of electric power gallery route contact is drawn according to business datum；
SS05 establishes evaluation index；
SS06 draws evaluation result.
2. a kind of electric power facility distribution according to claim 1 exists with power network resources quality testing method, its feature
In evaluating data includes facility data, resource data and path data in the SS01；
Wherein, the facility data includes transformer station, switching station, ring main unit, public change, high voltage customer, shaft tower, Gong Jing；
Wherein, the resource data connects position, work well casing hole resource including interval resource, shaft tower loop and T；
Wherein, the path data includes power transmission and distribution supply path line topological.
3. a kind of electric power facility distribution according to claim 1 exists with power network resources quality testing method, its feature
In the SS04 establishes electric power gallery course confidence level computation model, with reference to the multidimensional index of GIS application demands and data
Environmental Evaluation Model is specific as follows：
The evaluating data established according to SS01：
A paths interconnection data reliability, i.e. the GIS electric power gallery line route degree of accuracy；
B electric power facilities and resource points data reliability, including accuracy, logicality, information integrity, normalization；
C coverage rates；Wherein
Coverage rate=(quantity of typing of any sort electric power facility or resource/facility derives total quantity in system) × 100%,
Or=1- (derivation missing quantity/facility of any sort electric power facility or resource derives total quantity in system) × 100%；
By analyzing accuracy, logicality, information integrity, normalization, the coverage rate of electric power facility and resource data, and
The GIS electric power gallery line routes degree of accuracy totally 6 latitudes, difference of each latitude according to business scenario to data value demand,
Establish evaluation index.
4. a kind of electric power facility distribution according to claim 1 exists with power network resources quality testing method, its feature
In it is as follows that the SS03 establishes facility total amount derivation model detailed process：
A1 obtains evaluating data；
A2 assesses the weighing factor of A1 such data by big data cluster analysis；
B1 judges whether it is standardized data
If standardized data, then
Step 1, evaluating data is compareed between multi-source system；
Step 2, it is control foundation with the operation numbering of standardization, analyzes identical, similar, difference facility；
Step 3, merged using measures of dispersion, analog quantity according to cluster preferentially, equal amount superposition method, derive total quantity；
If not standardized data part, then
Step 1, quantity is lacked using business rule fuzzy inference；
Step 2, the fuzzy value is with quantity sum in system as derivation total quantity.
5. a kind of electric power facility distribution according to claim 4 exists with power network resources quality testing method, its feature
In the multi-source system includes PMS systems, the main distribution of Scada systems, Electric Energy Acquisition System, marketing system.
6. a kind of electric power facility distribution according to claim 1 exists with power network resources quality testing method, its feature
In the SS04 establishes electric power gallery course confidence level computation model and specifically includes following process：
C01, establish electric power facility contact data；
C02, calculated using shortest path；
Arterial highway, major trunk roads, subsidiary road, branch road priority principle, move towards calculate；
The preferential calculating principle of pipe well；
Cable route nameplate data record；
Shaft tower loop data；
C03, optimal degree of conformity algorithm extraction；
C04, believable line route.
7. a kind of electric power facility distribution according to claim 1 exists with power network resources quality testing method, its feature
In the SS05, which establishes evaluation result, includes facility and resource interconnection data evaluation result, facility and resource points data evaluation
As a result, facility coverage rate result, Key Quality analysis of Influential Factors result；The facility and resource interconnection data evaluation knot
Fruit, facility and resource points data evaluation result, the generation integrated data Quality Evaluation Analysis report of facility coverage rate result；The pass
The generation critical factor analysis report of key influencing factors of quality analysis result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710840748.6A CN107563665A (en) | 2017-09-18 | 2017-09-18 | A kind of electric power facility distribution and power network resources quality testing method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710840748.6A CN107563665A (en) | 2017-09-18 | 2017-09-18 | A kind of electric power facility distribution and power network resources quality testing method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107563665A true CN107563665A (en) | 2018-01-09 |
Family
ID=60981206
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710840748.6A Pending CN107563665A (en) | 2017-09-18 | 2017-09-18 | A kind of electric power facility distribution and power network resources quality testing method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107563665A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108876146A (en) * | 2018-06-14 | 2018-11-23 | 国网山东省电力公司聊城供电公司 | A kind of electric network data class assets management method and system |
| CN108986875A (en) * | 2018-08-01 | 2018-12-11 | 中国人民解放军第二军医大学 | A kind of medical data quality determination method and system |
| CN111080474A (en) * | 2019-12-03 | 2020-04-28 | 江和顺 | Distribution network reliability analysis method based on big data visualization technology |
| CN111208392A (en) * | 2020-04-16 | 2020-05-29 | 武汉格蓝若智能技术有限公司 | Label-free cable collection trend identification method |
| CN112101698A (en) * | 2020-07-23 | 2020-12-18 | 国网浙江省电力有限公司绍兴供电公司 | Power communication optical cable operation capacity assessment method |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040153354A1 (en) * | 2003-02-03 | 2004-08-05 | Hitachi, Ltd. | Method and system for managing project program change |
| CN103632203A (en) * | 2013-09-23 | 2014-03-12 | 国家电网公司 | Distribution network power supply area division method based on comprehensive evaluation |
| CN104700325A (en) * | 2015-03-30 | 2015-06-10 | 国家电网公司 | Power distribution network stability evaluation method |
| CN105512448A (en) * | 2014-09-22 | 2016-04-20 | 国家电网公司 | Power distribution network health index assessment method |
| CN106203867A (en) * | 2016-07-19 | 2016-12-07 | 国家电网公司 | Grid division methods based on power distribution network assessment indicator system and cluster analysis |
| CN106780140A (en) * | 2016-12-15 | 2017-05-31 | 国网浙江省电力公司 | Electric power credit assessment method based on big data |
| CN206312210U (en) * | 2016-08-11 | 2017-07-07 | 中国南方电网有限责任公司电网技术研究中心 | State evaluation system of power distribution network equipment |
-
2017
- 2017-09-18 CN CN201710840748.6A patent/CN107563665A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040153354A1 (en) * | 2003-02-03 | 2004-08-05 | Hitachi, Ltd. | Method and system for managing project program change |
| CN103632203A (en) * | 2013-09-23 | 2014-03-12 | 国家电网公司 | Distribution network power supply area division method based on comprehensive evaluation |
| CN105512448A (en) * | 2014-09-22 | 2016-04-20 | 国家电网公司 | Power distribution network health index assessment method |
| CN104700325A (en) * | 2015-03-30 | 2015-06-10 | 国家电网公司 | Power distribution network stability evaluation method |
| CN106203867A (en) * | 2016-07-19 | 2016-12-07 | 国家电网公司 | Grid division methods based on power distribution network assessment indicator system and cluster analysis |
| CN206312210U (en) * | 2016-08-11 | 2017-07-07 | 中国南方电网有限责任公司电网技术研究中心 | State evaluation system of power distribution network equipment |
| CN106780140A (en) * | 2016-12-15 | 2017-05-31 | 国网浙江省电力公司 | Electric power credit assessment method based on big data |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108876146A (en) * | 2018-06-14 | 2018-11-23 | 国网山东省电力公司聊城供电公司 | A kind of electric network data class assets management method and system |
| CN108986875A (en) * | 2018-08-01 | 2018-12-11 | 中国人民解放军第二军医大学 | A kind of medical data quality determination method and system |
| CN111080474A (en) * | 2019-12-03 | 2020-04-28 | 江和顺 | Distribution network reliability analysis method based on big data visualization technology |
| CN111208392A (en) * | 2020-04-16 | 2020-05-29 | 武汉格蓝若智能技术有限公司 | Label-free cable collection trend identification method |
| CN111208392B (en) * | 2020-04-16 | 2020-07-31 | 武汉格蓝若智能技术有限公司 | Label-free cable collection trend identification method |
| CN112101698A (en) * | 2020-07-23 | 2020-12-18 | 国网浙江省电力有限公司绍兴供电公司 | Power communication optical cable operation capacity assessment method |
| CN112101698B (en) * | 2020-07-23 | 2024-04-05 | 国网浙江省电力有限公司双创中心 | Electric power communication optical cable operation capability assessment method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107563665A (en) | A kind of electric power facility distribution and power network resources quality testing method | |
| WO2023115842A1 (en) | Data-driven offline and online integrated simulation system and method for power distribution network | |
| WO2020147349A1 (en) | Power distribution network operation aided decision-making analysis system and method | |
| CN109635127B (en) | Power equipment portrait knowledge map construction method based on big data technology | |
| CN109408603B (en) | Big data-based method for drawing topological graph of transformer area | |
| CN102947801A (en) | Malicious attack detection and analysis | |
| CN110708116B (en) | Optical path management system and method for rapidly positioning and analyzing same route of optical path | |
| CN102801732A (en) | Power communication backbone network safety risk assessment method based on network topology | |
| CN106408207A (en) | Modeling method and system for secondary virtual loop of intelligent substation | |
| CN106777808A (en) | A kind of Internet resources generation method based on standardization CAD diagram paper | |
| CN110826228B (en) | Regional power grid operation quality limit evaluation method | |
| CN110427392A (en) | Power distribution network grid management information system based on cloud platform | |
| CN105653777A (en) | Intelligent mapping system for general survey of underground power pipeline | |
| CN103489139A (en) | Comprehensive analysis and management system for urban distribution network planning | |
| CN109685684A (en) | A kind of low-voltage network topological structure method of calibration of knowledge based map | |
| CN108256770A (en) | Photo-voltaic power generation station O＆M managing and control system based on mobile application | |
| CN113902583B (en) | Distribution network side operation and maintenance method and system using low-voltage network equipment data | |
| CN114091213A (en) | Power communication network planning scheme evaluation system | |
| CN105914732A (en) | High-voltage power grid theoretical line loss evaluation system | |
| CN106506190B (en) | A kind of communication network operating system and operation method | |
| Zhou et al. | Research and Implementation of Distribution Network Operating Analysis Platform Based on Multi-source Heterogeneous Data | |
| Kazsoki et al. | Formulation of reference network models for the Hungarian medium voltage distribution level | |
| CN114167344A (en) | Medium-high voltage and distribution room general table metering point error analysis system | |
| CN108335231A (en) | A kind of power distribution network data diagnosis method of Auto-matching | |
| Capuder et al. | Visualization of distribution system planning for engineers and decision-makers |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180109 |
|
| RJ01 | Rejection of invention patent application after publication |