CN106841923A - Distribution network line fault localization method based on difference Convolution Analysis method - Google Patents
Distribution network line fault localization method based on difference Convolution Analysis method Download PDFInfo
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- CN106841923A CN106841923A CN201710106533.1A CN201710106533A CN106841923A CN 106841923 A CN106841923 A CN 106841923A CN 201710106533 A CN201710106533 A CN 201710106533A CN 106841923 A CN106841923 A CN 106841923A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/086—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution networks, i.e. with interconnected conductors
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/088—Aspects of digital computing
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- 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
- Y04S10/52—Outage or fault management, e.g. fault detection or location
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- Theoretical Computer Science (AREA)
- Locating Faults (AREA)
Abstract
The invention provides the distribution network line fault localization method based on difference Convolution Analysis method, step includes：Some monitoring points are set in distribution network line first, and distribution network line is divided into multistage by some monitoring points；Wave recording device and sending module are installed in each monitoring point, the three-phase current or three-phase voltage of monitoring point are acquired by wave recording device, and control centre is sent to by sending module；The three-phase current or three-phase voltage recorded according to wave recording device by control centre, extract the differential data before and after trouble point, carry out difference convolution algorithm, judge whether difference convolution algorithm result mutation occurs, according to catastrophe, the topological structure with reference to distribution network line, failure judgement occurs on the circuit between which monitoring point.The present invention is judged trouble point by relatively more adjacent two monitoring points curent change situation, efficiently solve the problems, such as that Fault Identification and location technology of the tradition with absolute value variable quantity as foundation are easily failed to judge, can preferably serve the management and maintenance work of distribution line.
Description
Technical field
The present invention relates to distribution network line fault diagnostic techniques, specially a kind of distribution network line fault localization method.
Background technology
At present, domestic distribution line failure diagnosis is broadly divided into failure line selection and the major class of fault location two.Failure line selection is
After referring to that failure occurs, judge that the specific feeder line of which bar there occurs failure by certain technological means；Fault location
Refer to after failure occurs, to determine which section is failure occur at by certain technological means.Because fault location can more shorten
Trouble shooting time, improves power supply reliability, therefore fault location is the main development direction of distribution network line fault diagnosis.
Currently, the Fault Locating Method of power distribution network mainly relies on FTU (Feeder Terminal Unit) and the class of fault detector two to set
It is standby.This two kind equipment is mainly assigned into distribution network line, when line failure, by FTU or the phase of fault detector
The data for closing sensing equipment collection carry out local analysis.As local phase current there occurs mutation, abrupt transients current value reaches
Electric current is " 0 " more than predetermined threshold value (such as mutation current 600A), and after causing tripping operation with circuit correlation relay protection action
Phenomenon.Be may determine that by the phenomenon, fault current has been flowed through in the monitoring point, trouble point is located at after the monitoring point.
The advantage of above-mentioned conventional mapping methods is simple, and relatively low to the requirement of equipment sampling precision, it is easy to accomplish.Its shortcoming
It is not too obvious failure for fault current change to be, is easily failed to judge.
The content of the invention
The present invention provides the distribution network line fault localization method based on difference Convolution Analysis method, by relatively more adjacent two prison
Measuring point curent change situation judged trouble point, efficiently solves Fault Identification of the tradition with absolute value variable quantity as foundation
And the problem that location technology is easily failed to judge, can preferably serve the management and maintenance work of distribution line.
The present invention is realized using following technical scheme：Distribution network line fault positioning side based on difference Convolution Analysis method
Method, comprises the following steps：
Step 1, some monitoring points are set in distribution network line first, be divided into for distribution network line many by some monitoring points
Section；
Step 2, wave recording device and sending module are installed in each monitoring point, by wave recording device to the three-phase current of monitoring point
Or three-phase voltage is acquired, and control centre is sent to by sending module；
Step 3, the three-phase current or three-phase voltage that are recorded according to wave recording device by control centre, before and after extraction trouble point
Differential data, carry out difference convolution algorithm, judge difference convolution algorithm result whether occur mutation, according to catastrophe, knot
The topological structure of distribution network line is closed, failure judgement occurs on the circuit between which monitoring point.
Preferably, the step 3 carries out difference convolution algorithm process and is：
Every cycle evidence of each differential data is taken, the two neighboring cycle data that differential data is taken respectively carry out related fortune
Calculate, at least take 8 cycle data, 800Hz is not less than per cycle sample rate, the formula of related operation is：
" * " represents convolution algorithm in formula.
Preferably, the differential data principle before and after the step 3 extraction trouble point is：Same electricity is in distribution network line
Flow back to three-phase electricity flow valuve that the two neighboring monitoring point on road gathered or three-phase voltage value is subtracted each other.
Preferably, when the step 1 sets monitoring point, one monitoring point is respectively set in distribution network line head and the tail；Then it is every
Be spaced a distance one monitoring point of setting；If there is T to connect branch line, connect branch line in T and install monitoring point additional, for judging whether
It is branch line failure.
The present invention compared with prior art, has the following advantages that and beneficial effect：
1st, breakdown judge is carried out by relatively more adjacent two monitoring points curent change situation, compared to traditional with absolute value
Variable quantity is the fault verification technology of foundation, and accuracy rate is high, does not result in and fails to judge.
2nd, related operation is carried out to the differential data of monitoring point using convolution integral algorithm, logic is simple, reliable, it is to avoid
The complexity and huge operand of general advanced algorithm.
Brief description of the drawings
Fig. 1 is the model of distribution network line fault localization method；
Fig. 2 is the three-phase current difference convolution oscillogram of monitoring point 1-4 in Fig. 1.
Specific embodiment
With reference to embodiment and accompanying drawing, the present invention is described in further detail, but embodiments of the present invention are not limited
In this.
Embodiment
Distribution network line fault localization method of the present invention, comprises the following steps：
Step 1, some monitoring points are set in distribution network line first, be divided into for distribution network line many by some monitoring points
Section.When setting monitoring point, the actual conditions and capital budgeting that can be run according to circuit are arranged.The general feelings allowed in fund
Under condition, one monitoring point is respectively set in circuit head and the tail；Then one monitoring point is set at interval of 1 km；In addition, running into T
When connecing branch line, monitoring point must be installed additional in branch line, for determining whether branch line failure.The setting of monitoring point is big with load
Small and circuit types is unrelated.
Step 2, wave recording device and wireless sending module are installed in each monitoring point, by wave recording device to the three-phase of monitoring point
Electric current or electric field waveform (i.e. three-phase voltage) are acquired, and are sent directly to control centre by wireless sending module.
Step 3, the three-phase current or three-phase voltage that are recorded according to wave recording device by control centre, before and after extraction trouble point
Differential data, carry out difference convolution algorithm, judge difference convolution algorithm result whether occur mutation, according to catastrophe, knot
The topological structure for closing distribution network line is positioned to failure, i.e., failure judgement occurs on the circuit between which monitoring point.
Wherein wave recording device can be realized using sensor.
For convenience of description, it is now assumed that based under distribution network line structure shown in Fig. 1, there occurs A, B phase fault,
Assuming that trouble point will occur between monitoring point 2 and monitoring point 3.Control centre extracts the differential data before and after trouble point first,
The three-phase current of monitoring point 1 is subtracted using the three-phase current of monitoring point 2, the three-phase current of monitoring point 3 subtracts the three-phase of monitoring point 2
Electric current, the three-phase current of monitoring point 4 subtracts the three-phase current of monitoring point 2, i.e. the selection principle of difference is：In same in circuit
The three-phase electricity flow valuve or three-phase voltage value that the two neighboring monitoring point of current loop is gathered are subtracted each other.
Take every cycle evidence of each differential data, 8 cycles be divided into by the cycle, be respectively 1-2,2-3,3-4,4-5,5-6,
The related operation of 6-7,7-8 cycle, that is, taking the two neighboring cycle of differential data carries out related operation, at least takes 8 cycles, weekly
Ripple sample rate is not less than 800Hz.The formula of related operation is as follows.
" * " represents convolution algorithm in above formula, and oscillogram is referring to Fig. 2, and correlation result is as shown in following table 1-3.
The monitoring point 2 of table 1 and the differential associated processing outcomes of monitoring point 1
The monitoring point 3 of table 2 and the differential associated processing outcomes of monitoring point 2
The monitoring point 4 of table 3 and the differential associated processing outcomes of monitoring point 2
By data above as can be seen that monitoring point 1 is sufficiently close to the current value of monitoring point 2, the phase of the difference of its current value
Pass is worth very little, therefore fixes a breakdown and occur between monitoring point 1 and 2.The A phase currents correlation and B phases of monitoring point 3 and monitoring point 2
Electric current correlation is uprushed after the 3rd cycle.Monitoring point 4 is related to the A phase currents correlation and B phase currents of monitoring point 2
Value is also uprushed after the 3rd cycle, thus can by fault location between monitoring point 2,3 and 2,4 between, by power distribution network
Known to wire topologies, failure occurs at the circuit 2 between monitoring point 2 and monitoring point 3.
Above-described embodiment is the present invention preferably implementation method, but embodiments of the present invention are not by above-described embodiment
Limitation, it is other it is any without departing from Spirit Essence of the invention and the change, modification, replacement made under principle, combine, simplification,
Equivalent substitute mode is should be, is included within protection scope of the present invention.
Claims (6)
1. the distribution network line fault localization method of difference Convolution Analysis method is based on, it is characterised in that comprised the following steps：
Step 1, some monitoring points are set in distribution network line first, distribution network line is divided into multistage by some monitoring points；
Step 2, each monitoring point install wave recording device and sending module, by wave recording device to the three-phase current of monitoring point or three
Phase voltage is acquired, and is sent to control centre by sending module；
Step 3, the three-phase current or three-phase voltage that are recorded according to wave recording device by control centre, extract the difference before and after trouble point
Dynamic data, carry out difference convolution algorithm, judge whether difference convolution algorithm result occurs being mutated, according to catastrophe, with reference to matching somebody with somebody
The topological structure of power network line, failure judgement occurs on the circuit between which monitoring point.
2. the distribution network line fault localization method based on difference Convolution Analysis method according to claim 1, its feature exists
In the step 3 carries out difference convolution algorithm process and is：
Every cycle evidence of each differential data is taken, the two neighboring cycle data that differential data is taken respectively carry out related operation, most
8 cycle data being taken less, 800Hz being not less than per cycle sample rate, the formula of related operation is：
" * " represents convolution algorithm in formula.
3. the distribution network line fault localization method based on difference Convolution Analysis method according to claim 1, its feature exists
In the differential data principle that the step 3 extracts before and after trouble point is：It is adjacent in same current loop in distribution network line
The three-phase electricity flow valuve or three-phase voltage value that two monitoring points are gathered are subtracted each other.
4. the distribution network line fault localization method based on difference Convolution Analysis method according to claim 1, its feature exists
In when the step 1 sets monitoring point, in one monitoring point of each setting of distribution network line head and the tail；Then at interval of a segment distance
One monitoring point is set；If there is T to connect branch line, connect branch line in T and install monitoring point additional, for determining whether branch line event
Barrier.
5. the distribution network line fault localization method based on difference Convolution Analysis method according to claim 1, its feature exists
In the wave recording device is sensor.
6. the distribution network line fault localization method based on difference Convolution Analysis method according to claim 1, its feature exists
In the sending module is wireless sending module.
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Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107390614A (en) * | 2017-09-01 | 2017-11-24 | 泸州能源投资有限公司 | A kind of charging pile communication intelligent management system |
| CN107478941A (en) * | 2017-07-14 | 2017-12-15 | 国网上海市电力公司 | Distribution network failure simulated annealing localization method based on Multipoint synchronous measurement data |
| CN109375057A (en) * | 2018-11-06 | 2019-02-22 | 华中科技大学 | A kind of wire selection method for power distribution network single phase earthing failure based on electric current second differnce |
| CN109387742A (en) * | 2018-11-06 | 2019-02-26 | 华中科技大学 | A kind of line fault recognition methods based on multiple spot active power monitoring and difference |
| CN110346696A (en) * | 2019-07-05 | 2019-10-18 | 杭州西湖电子研究所 | Three-dimensional map expression method for wide-area dielectric loss current difference |
| CN110794254A (en) * | 2018-08-01 | 2020-02-14 | 北京映翰通网络技术股份有限公司 | Power distribution network fault prediction method and system based on reinforcement learning |
| CN111698712A (en) * | 2020-06-16 | 2020-09-22 | 广西大学 | Novel fault indicator based on 5G |
| CN112782528A (en) * | 2020-12-31 | 2021-05-11 | 西安理工大学 | Power distribution network fault section positioning method using PMU |
| CN113238120A (en) * | 2021-05-18 | 2021-08-10 | 国网河北省电力有限公司电力科学研究院 | Power distribution network fault position determining method based on photovoltaic power station and terminal equipment |
| CN113504436A (en) * | 2021-07-23 | 2021-10-15 | 广东电网有限责任公司 | Distribution network line disconnection and phase loss diagnosis method and device based on electrical topology |
| CN113971417A (en) * | 2020-07-23 | 2022-01-25 | 国网天津市电力公司 | 10kV distribution network fault mode identification method and system based on kernel limit learning machine |
| CN115032508A (en) * | 2022-08-12 | 2022-09-09 | 国网山东省电力公司电力科学研究院 | Distributed transmission line fault diagnosis method and system based on target identification |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101666848A (en) * | 2009-10-15 | 2010-03-10 | 北京四方继保自动化股份有限公司 | Fault location method based on travelling wave |
| CN102998593A (en) * | 2012-11-15 | 2013-03-27 | 华北电力大学 | Method for accurately positioning electrical cable faults through interpolation convolution calculating |
| CN103424662A (en) * | 2013-08-05 | 2013-12-04 | 江苏科技大学 | Smart power grid transmission line fault monitoring system and method |
| CN106019081A (en) * | 2016-05-24 | 2016-10-12 | 长沙理工大学 | Accurate detection method for voltage travelling wave of transmission line fault based on waveform inversion |
| CN106203531A (en) * | 2016-07-20 | 2016-12-07 | 清华大学 | A kind of transmission line fault sorting technique based on the sparse autocoder of convolution |
-
2017
- 2017-02-27 CN CN201710106533.1A patent/CN106841923A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101666848A (en) * | 2009-10-15 | 2010-03-10 | 北京四方继保自动化股份有限公司 | Fault location method based on travelling wave |
| CN102998593A (en) * | 2012-11-15 | 2013-03-27 | 华北电力大学 | Method for accurately positioning electrical cable faults through interpolation convolution calculating |
| CN103424662A (en) * | 2013-08-05 | 2013-12-04 | 江苏科技大学 | Smart power grid transmission line fault monitoring system and method |
| CN106019081A (en) * | 2016-05-24 | 2016-10-12 | 长沙理工大学 | Accurate detection method for voltage travelling wave of transmission line fault based on waveform inversion |
| CN106203531A (en) * | 2016-07-20 | 2016-12-07 | 清华大学 | A kind of transmission line fault sorting technique based on the sparse autocoder of convolution |
Non-Patent Citations (2)
| Title |
|---|
| 李瑞 等: "基于物联网信息融合技术的新型配网线路故障诊断方法探析", 《第35届中国控制会议论文集（F）》 * |
| 范国琛 等: "基于Kaiser自卷积窗的相位比较式输电线路故障定位方法", 《电力系统保护与控制》 * |
Cited By (18)
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| CN107478941A (en) * | 2017-07-14 | 2017-12-15 | 国网上海市电力公司 | Distribution network failure simulated annealing localization method based on Multipoint synchronous measurement data |
| CN107478941B (en) * | 2017-07-14 | 2019-08-06 | 国网上海市电力公司 | Distribution network failure simulated annealing localization method based on Multipoint synchronous measurement data |
| CN107390614B (en) * | 2017-09-01 | 2020-02-18 | 泸州能源投资有限公司 | Fill electric pile communication intelligent management system |
| CN107390614A (en) * | 2017-09-01 | 2017-11-24 | 泸州能源投资有限公司 | A kind of charging pile communication intelligent management system |
| CN110794254A (en) * | 2018-08-01 | 2020-02-14 | 北京映翰通网络技术股份有限公司 | Power distribution network fault prediction method and system based on reinforcement learning |
| CN109375057B (en) * | 2018-11-06 | 2021-01-19 | 华中科技大学 | Power distribution network single-phase earth fault line selection method based on current second-order difference |
| CN109375057A (en) * | 2018-11-06 | 2019-02-22 | 华中科技大学 | A kind of wire selection method for power distribution network single phase earthing failure based on electric current second differnce |
| CN109387742A (en) * | 2018-11-06 | 2019-02-26 | 华中科技大学 | A kind of line fault recognition methods based on multiple spot active power monitoring and difference |
| CN110346696A (en) * | 2019-07-05 | 2019-10-18 | 杭州西湖电子研究所 | Three-dimensional map expression method for wide-area dielectric loss current difference |
| CN111698712A (en) * | 2020-06-16 | 2020-09-22 | 广西大学 | Novel fault indicator based on 5G |
| CN111698712B (en) * | 2020-06-16 | 2023-05-09 | 广西大学 | Novel fault indicator based on 5G |
| CN113971417A (en) * | 2020-07-23 | 2022-01-25 | 国网天津市电力公司 | 10kV distribution network fault mode identification method and system based on kernel limit learning machine |
| CN112782528A (en) * | 2020-12-31 | 2021-05-11 | 西安理工大学 | Power distribution network fault section positioning method using PMU |
| CN112782528B (en) * | 2020-12-31 | 2023-07-18 | 西安理工大学 | Power distribution network fault section positioning method by utilizing PMU |
| CN113238120A (en) * | 2021-05-18 | 2021-08-10 | 国网河北省电力有限公司电力科学研究院 | Power distribution network fault position determining method based on photovoltaic power station and terminal equipment |
| CN113504436A (en) * | 2021-07-23 | 2021-10-15 | 广东电网有限责任公司 | Distribution network line disconnection and phase loss diagnosis method and device based on electrical topology |
| CN115032508A (en) * | 2022-08-12 | 2022-09-09 | 国网山东省电力公司电力科学研究院 | Distributed transmission line fault diagnosis method and system based on target identification |
| CN115032508B (en) * | 2022-08-12 | 2022-11-01 | 国网山东省电力公司电力科学研究院 | Distributed transmission line fault diagnosis method and system based on target identification |
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Application publication date: 20170613 |