CN108038585A - A kind of fast quick-recovery householder method of event of failure based on multi-source data - Google Patents
A kind of fast quick-recovery householder method of event of failure based on multi-source data Download PDFInfo
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- CN108038585A CN108038585A CN201711116827.9A CN201711116827A CN108038585A CN 108038585 A CN108038585 A CN 108038585A CN 201711116827 A CN201711116827 A CN 201711116827A CN 108038585 A CN108038585 A CN 108038585A
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- 238000011084 recovery Methods 0.000 title claims abstract description 30
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- 230000008859 change Effects 0.000 claims abstract description 6
- 230000000052 comparative effect Effects 0.000 claims abstract description 4
- 238000000547 structure data Methods 0.000 claims abstract description 4
- 230000006837 decompression Effects 0.000 claims description 18
- 238000005259 measurement Methods 0.000 claims description 7
- 238000004321 preservation Methods 0.000 claims description 3
- 238000010937 topological data analysis Methods 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 4
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Abstract
The present invention relates to electric network fault analysis field, more particularly, to a kind of fast quick-recovery householder method of event of failure based on multi-source data, comprises the following steps：S1：Fault message is obtained, section where obtaining faulty equipment, obtains key equipment information all in section；S2：Generation scanning result is calculated according to fault message；S3：Contrast displaying and weak link are carried out to the section structure data of generation；S4：The method of operation under Different Strategies is generated, device scan Comparative result in section is shown before and after change.Make dispatcher very clear to the effect of the recovery policy, while a variety of recovery policies can also be set, comparing calculation is carried out to each tactful result, allows dispatcher can be with better choice optimal policy.
Description
Technical field
It is fast more particularly, to a kind of event of failure based on multi-source data the present invention relates to electric network fault analysis field
Quick-recovery householder method.
Background technology
For now, when electric network fault event is handled, various fault message Statistical Criterias are more messy in China,
Standardization and standard system are not formed, and multi-source data information format and information protection system are relatively simple.The risk of power grid still according to
Shown by classical pathway, be unfavorable for the weak link that operation maintenance personnel intuitively understands power grid.Therefore, in order to tackle and handle in time
Electric network fault event is, it is necessary to establish automatic fault recognition system, the countermeasure that trouble-shooting recovers rapidly, to ensure operation of power networks
Security.
After accident generation, disposal process relies on dispatcher's experience, it is impossible to effectively and rapidly formulates recovery policy.Accident
Recovery policy afterwards relies the experience of dispatcher entirely, it is difficult to make judgement promptly and accurately, speed is slow and there are certain risk.
The content of the invention
The present invention is at least one defect overcome described in the above-mentioned prior art, there is provided a kind of failure based on multi-source data
The fast quick-recovery householder method of event, makes dispatcher very clear to the effect of the recovery policy, while can also set a variety of extensive
Multiple strategy, carries out comparing calculation to each tactful result, allows dispatcher can be with better choice optimal policy.
In order to solve the above technical problems, the technical solution adopted by the present invention is：A kind of event of failure based on multi-source data
Fast quick-recovery householder method, comprises the following steps：
S1：Information to be restored is obtained, section where obtaining equipment to be restored, obtains key equipment information all in section；
S2：Generation scanning result is calculated according to fault message；
S3：Contrast displaying and weak link are carried out to the section structure data of generation；
S4：The method of operation under Different Strategies is generated, device scan Comparative result in section is shown before and after change.
Further, in step sl, comprise the following steps：
S11：Choose equipment to be restored in power grid；
S12：Generate recovery policy；
S13：The section where equipment to be restored is obtained by the power grid topology model generated, passes through the power network topology generated
Model and place section obtain all key equipments in the section；
S14：Judge whether to set section.
Further, in step S14, judge whether to set section, if so, S21 is then entered step, if it is not, then entering
Step S22；
Wherein, step S21 is to set power system operating mode to calculate trend according to equipment to be restored；Step S22 is according to be restored
Facility information calculates generation section scanning result.
Further, in step S22, comprise the following steps：
S221：Traversal sets all devices decompression in section；
S222：According to power grid topology model, decompression equipment subordinate equipment is demanded, obtains all decompression equipment；
S223：All decompression equipment are counted, analyze decompression website；
S224：10kv busbares in decompression equipment are counted, statistics institute lossy load and number of users；
S225：Calculated according to accident event judgment rule, generate grade and the preservation of this accident event；
S226：Judge whether equipment in the section that does not travel through also, if then return to step S222；If nothing, enters step
S23。
Further, affiliated step S23 is the scanning result of some section under one section of generation.
Further, in step S224, data acquisition and supervisor control timing push grid measurement data are passed through
10kv bus loads and number of users data are calculated with distribution network systems timing push distribution user data.
Further, in the step s 21, comprise the following steps：
S211：According to strategy setting power system operating mode；
S212：Call trend software；
S213：Obtain trend software calculated value；
S214：Update 10kv bus load values；
S215：Return to step S221；
Wherein, the trend software provides the electric network swim value service that calculates, this software is called by remote service and interacted,
Invoked procedure is to be passed to user's pseudo operation parameter device mark and equipment state, trend software root to trend software by interface
Backward the system, which is calculated, according to parameter returns to the electric network swim value after calculating.
Further, in step s 2, determine whether not travel through section, if so, then return to step S1, if nothing, into
Enter step S3.
Further, in step S1, S2, the common information model data timing of data acquisition and supervisor control pushes away
Generation power grid topology model is sent, topological analysis is carried out by power grid topology model.
Further, in step s3, next recovery policy is determined whether, if so, then return to step S1, if nothing,
Then enter step S4.
Wherein, data acquisition is that computer-based dcs and electric power are automatic with supervisor control
Change monitoring system；In electric system, data acquisition and supervisor control the operational outfit at scene can be carried out monitoring and
Control, to realize data acquisition, equipment control, measurement, parameter regulation and various types of signal alarm various functions.Data acquisition with
Supervisor control provides data below and supports, common information model model, measurement information, user data, failure source information.
Wherein, common information model is an abstract model, describes all main objects of electric power enterprise, particularly with electricity
Power runs related object.Power system resource is represented by providing a kind of relation with object class and attribute and between them
Standard method.By defining a kind of common language based on common information model（That is syntax and semantics）So that these application or
System can access common data and exchange information to realize independent of the internal representation of information.This method is adopted from data
Collection obtains common information model model data with supervisor control, and electric network data is obtained by parsing common information model model
And topological structure of electric.
Compared with prior art, beneficial effect is：After electric network fault, dispatcher by rule of thumb can only recover power grid,
And can not know the precise effects of operation of power networks under the reset mode, and in this way, dispatcher can simulate setting power grid
The method of operation, calculates the N-1 risk informations of the section under the method for operation, allows effect one mesh of the dispatcher to the recovery policy
It is clear, while a variety of recovery policies can also be set, comparing calculation is carried out to each tactful result, makes dispatcher more preferable
Select optimal policy.
Brief description of the drawings
Fig. 1 is present invention overall flow figure in one embodiment；
Fig. 2 is the specific steps in Fig. 1 overall flow figures.
Embodiment
Attached drawing is only for illustration, it is impossible to is interpreted as the limitation to this patent；It is attached in order to more preferably illustrate the present embodiment
Scheme some components to have omission, zoom in or out, do not represent the size of actual product；To those skilled in the art,
Some known features and its explanation may be omitted and will be understood by attached drawing.Being given for example only property of position relationship described in attached drawing
Explanation, it is impossible to be interpreted as the limitation to this patent.
As shown in Figure 1, a kind of fast quick-recovery householder method of event of failure based on multi-source data, comprises the following steps：
S1：Information to be restored is obtained, section where obtaining equipment to be restored, obtains key equipment information all in section；
S2：Generation scanning result is calculated according to fault message；
S3：Contrast displaying and weak link are carried out to the section structure data of generation；
S4：The method of operation under Different Strategies is generated, device scan Comparative result in section is shown before and after change.
In the present embodiment, as shown in Fig. 2, in step sl, comprising the following steps：
S11：Choose equipment to be restored in power grid；
S12：Generate recovery policy；
S13：The section where equipment to be restored is obtained by the power grid topology model generated, passes through the power network topology generated
Model and place section obtain all key equipments in the section；
S14：Judge whether to set section.
In the present embodiment, in step S14, judge whether to set section, if so, S21 is then entered step, if it is not, then
Enter step S22；
Wherein, step S21 is to set power system operating mode to calculate trend according to equipment to be restored；Step S22 is according to be restored
Facility information calculates generation section scanning result.
In the present embodiment, in step S22, comprise the following steps：
S221：Traversal sets all devices decompression in section；
S222：According to power grid topology model, decompression equipment subordinate equipment is demanded, obtains all decompression equipment；
S223：All decompression equipment are counted, analyze decompression website；
S224：10kv busbares in decompression equipment are counted, statistics institute lossy load and number of users；
S225：Calculated according to accident event judgment rule, generate grade and the preservation of this accident event；
S226：Judge whether equipment in the section that does not travel through also, if then return to step S222；If nothing, enters step
S23。
In the present embodiment, affiliated step S23 is the scanning result of some section under one section of generation.
In the present embodiment, in step S224, data acquisition and supervisor control timing push power grid measurement are passed through
10kv bus loads and number of users data are calculated in data and distribution network systems timing push distribution user data.
In the present embodiment, in the step s 21, comprise the following steps：
S211：According to strategy setting power system operating mode；
S212：Call trend software；
S213：Obtain trend software calculated value；
S214：Update 10kv bus load values；
S215：Return to step S221；
Wherein, the trend software provides the electric network swim value service that calculates, this software is called by remote service and interacted,
Invoked procedure is to be passed to user's pseudo operation parameter device mark and equipment state, trend software root to trend software by interface
Backward the system, which is calculated, according to parameter returns to the electric network swim value after calculating.
In the present embodiment, in step s 2, determine whether not travel through section, if so, then return to step S1, if nothing,
Then enter step S3.
In the present embodiment, in step S1, S2, the common information model data of data acquisition and supervisor control are determined
When push generation power grid topology model, topological analysis is carried out by power grid topology model.
In the present embodiment, in step s3, next recovery policy is determined whether, if so, then return to step S1, if
Nothing, then enter step S4.
Wherein, data acquisition is that computer-based dcs and electric power are automatic with supervisor control
Change monitoring system；In electric system, data acquisition and supervisor control the operational outfit at scene can be carried out monitoring and
Control, to realize data acquisition, equipment control, measurement, parameter regulation and various types of signal alarm various functions.Data acquisition with
Supervisor control provides data below and supports, common information model model, measurement information, user data, failure source information.
Wherein, common information model is an abstract model, describes all main objects of electric power enterprise, particularly with electricity
Power runs related object.Power system resource is represented by providing a kind of relation with object class and attribute and between them
Standard method.By defining a kind of common language based on common information model（That is syntax and semantics）So that these application or
System can access common data and exchange information to realize independent of the internal representation of information.This method is adopted from data
Collection obtains common information model model data with supervisor control, and electric network data is obtained by parsing common information model model
And topological structure of electric.
Obviously, the above embodiment of the present invention is only intended to clearly illustrate example of the present invention, and is not pair
The restriction of embodiments of the present invention.For those of ordinary skill in the field, may be used also on the basis of the above description
To make other variations or changes in different ways.There is no necessity and possibility to exhaust all the enbodiments.It is all this
All any modification, equivalent and improvement made within the spirit and principle of invention etc., should be included in the claims in the present invention
Protection domain within.
Claims (10)
1. the fast quick-recovery householder method of a kind of event of failure based on multi-source data, it is characterised in that comprise the following steps：
S1：Information to be restored is obtained, section where obtaining equipment to be restored, obtains key equipment information all in section；
S2：Generation scanning result is calculated according to fault message；
S3：Contrast displaying and weak link are carried out to the section structure data of generation；
S4：The method of operation under Different Strategies is generated, device scan Comparative result in section is shown before and after change.
2. the fast quick-recovery householder method of a kind of event of failure based on multi-source data according to claim 1, its feature exist
In in step sl, comprising the following steps：
S11：Choose equipment to be restored in power grid；
S12：Generate recovery policy；
S13：The section where equipment to be restored is obtained by the power grid topology model generated, passes through the power network topology generated
Model and place section obtain all key equipments in the section；
S14：Judge whether to set section.
3. the fast quick-recovery householder method of a kind of event of failure based on multi-source data according to claim 2, its feature exist
In, in step S14, judge whether set section, if so, S21 is then entered step, if it is not, then entering step S22；
Wherein, step S21 is to set power system operating mode to calculate trend according to equipment to be restored；Step S22 is according to be restored
Facility information calculates generation section scanning result.
4. the fast quick-recovery householder method of a kind of event of failure based on multi-source data according to claim 3, its feature exist
In in step S22, comprising the following steps：
S221：Traversal sets all devices decompression in section；
S222：According to power grid topology model, decompression equipment subordinate equipment is demanded, obtains all decompression equipment；
S223：All decompression equipment are counted, analyze decompression website；
S224：10kv busbares in decompression equipment are counted, statistics institute lossy load and number of users；
S225：Calculated according to accident event judgment rule, generate grade and the preservation of this accident event；
S226：Judge whether equipment in the section that does not travel through also, if then return to step S222；If nothing, enters step
S23。
5. the fast quick-recovery householder method of a kind of event of failure based on multi-source data according to claim 4, its feature exist
In affiliated step S23 is the scanning result of some section under one section of generation.
6. the fast quick-recovery householder method of a kind of event of failure based on multi-source data according to claim 4, its feature exist
In in step S224, passing through data acquisition and supervisor control timing push grid measurement data and distribution network systems timing
10kv bus loads and number of users data are calculated in push distribution user data.
7. the fast quick-recovery householder method of a kind of event of failure based on multi-source data according to claim 3, its feature exist
In in the step s 21, comprising the following steps：
S211：According to strategy setting power system operating mode；
S212：Call trend software；
S213：Obtain trend software calculated value；
S214：Update 10kv bus load values；
S215：Return to step S221；
Wherein, the trend software provides the electric network swim value service that calculates, this software is called by remote service and interacted,
Invoked procedure is to be passed to user's pseudo operation parameter device mark and equipment state, trend software root to trend software by interface
Backward the system, which is calculated, according to parameter returns to the electric network swim value after calculating.
8. the fast quick-recovery householder method of a kind of event of failure based on multi-source data according to claim 1, its feature exist
In in step s 2, determining whether not travel through section, if so, then return to step S1, if nothing, enters step S3.
9. the fast quick-recovery householder method of a kind of event of failure based on multi-source data according to claim 1, its feature exist
In, in step S1, S2, the common information model data timing push generation power network topology of data acquisition and supervisor control
Model, topological analysis is carried out by power grid topology model.
10. the fast quick-recovery householder method of a kind of event of failure based on multi-source data according to claim 1, its feature exist
In in step s3, next recovery policy being determined whether, if so, then return to step S1, if nothing, enters step S4.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109389323A (en) * | 2018-10-31 | 2019-02-26 | 广东电网有限责任公司 | Accident event level determination method, device and intelligent terminal |
| CN112186741A (en) * | 2020-09-10 | 2021-01-05 | 贵州电网有限责任公司 | Power grid operation weak point distinguishing method based on BPA (Business Process analysis) simulation calculation |
| CN114336500A (en) * | 2021-12-30 | 2022-04-12 | 广东电网有限责任公司 | Fault diagnosis and power restoration method, device and equipment for regional power grid |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103036245A (en) * | 2012-11-30 | 2013-04-10 | 中国南方电网有限责任公司 | Novel transmission loss reducing method by alternating current or direct current (AC / DC) synergy used in interconnected network and novel transmission loss reducing system by AC / DC synergy used in interconnected network |
| CN105653764A (en) * | 2015-12-22 | 2016-06-08 | 中国南方电网有限责任公司 | Method for online estimating and pre-warning grid safety accident risk levels |
-
2017
- 2017-11-13 CN CN201711116827.9A patent/CN108038585A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103036245A (en) * | 2012-11-30 | 2013-04-10 | 中国南方电网有限责任公司 | Novel transmission loss reducing method by alternating current or direct current (AC / DC) synergy used in interconnected network and novel transmission loss reducing system by AC / DC synergy used in interconnected network |
| CN105653764A (en) * | 2015-12-22 | 2016-06-08 | 中国南方电网有限责任公司 | Method for online estimating and pre-warning grid safety accident risk levels |
Non-Patent Citations (1)
| Title |
|---|
| 莫祖森 等: "电网事故决策辅助系统的研究", 《城市建设理论研究（电子版）》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109389323A (en) * | 2018-10-31 | 2019-02-26 | 广东电网有限责任公司 | Accident event level determination method, device and intelligent terminal |
| CN112186741A (en) * | 2020-09-10 | 2021-01-05 | 贵州电网有限责任公司 | Power grid operation weak point distinguishing method based on BPA (Business Process analysis) simulation calculation |
| CN112186741B (en) * | 2020-09-10 | 2022-03-22 | 贵州电网有限责任公司 | Power grid operation weak point distinguishing method based on BPA (Business Process analysis) simulation calculation |
| CN114336500A (en) * | 2021-12-30 | 2022-04-12 | 广东电网有限责任公司 | Fault diagnosis and power restoration method, device and equipment for regional power grid |
| CN114336500B (en) * | 2021-12-30 | 2024-05-28 | 广东电网有限责任公司 | Fault diagnosis and power restoration method, device and equipment for regional power grid |
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Application publication date: 20180515 |