CN107329042A - A kind of distribution network line fault localization method based on big data technology - Google Patents

A kind of distribution network line fault localization method based on big data technology Download PDF

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Publication number
CN107329042A
CN107329042A CN201710487549.1A CN201710487549A CN107329042A CN 107329042 A CN107329042 A CN 107329042A CN 201710487549 A CN201710487549 A CN 201710487549A CN 107329042 A CN107329042 A CN 107329042A
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China
Prior art keywords
dit
distribution network
wpcd
devices
matrix
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CN201710487549.1A
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Chinese (zh)
Inventor
陈志坚
何度江
刘云涛
张飞
孟婕
万琪
陈亮亮
李清
余妍
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Honghe Power Supply Bureau of Yunnan Power Grid Co Ltd
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Honghe Power Supply Bureau of Yunnan Power Grid Co Ltd
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Priority to CN201710487549.1A priority Critical patent/CN107329042A/en
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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
    • 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
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02H—EMERGENCY PROTECTIVE CIRCUIT ARRANGEMENTS
    • H02H7/00—Emergency protective circuit arrangements specially adapted for specific types of electric machines or apparatus or for sectionalised protection of cable or line systems, and effecting automatic switching in the event of an undesired change from normal working conditions
    • H02H7/26—Sectionalised protection of cable or line systems, e.g. for disconnecting a section on which a short-circuit, earth fault, or arc discharge has occured

Abstract

The invention discloses a kind of distribution network line fault localization method based on big data technology, including：A, lay DIT according to the topological structure of power distribution network, form big data measurement apparatus；B, required detection zone lay WPCD devices, for receiving each detection zone DIT remote signalling amount MMS.C, WPCD device form the adjacency matrix for characterizing power distribution network topological relation by receiving the remote signalling amount MMS transmitted by each switchyard DIT.D, the computing by adjacency matrix, the reachability matrix of each switchyard DIT maximum protection scopes of WPCD devices formation reflection.E, the maximum protection scope according to each DIT, WPCD devices can determine multiple complete incidence matrixes.F, the computing by complete incidence matrix and electric current column vector, WPCD devices can carry out the 3 wheel current differentials such as above-mentioned master is differential, the differential and remote standby of nearly standby is differential to each DIT and calculate respectively；After failure occurs, the public domain that difference current is more than setting valve is fault zone, you can complete the isolation of failure.

Description

A kind of distribution network line fault localization method based on big data technology
Technical field
The present invention relates to a kind of distribution network line fault localization method based on big data technology.
Background technology
Power distribution network is the network powered to end user, is supplied to user in power system generating, transmission of electricity, distribution, electricity consumption The key link of electricity.Power distribution network is in the end of power system, and Regional Distribution is wide, power network scale is big, device category is more, network connects Connect that the various, method of operation is changeable etc. to make its running state analysis have certain difficulty and complexity.
Radial pattern structure being used the traditional medium voltage distribution network of China, its trend in normal operation is unidirectional in a network more Flowing, adjusting for guard method is relatively simple.DG access not only increases the complicated journey of network structure in intelligent distribution network Degree, also changes the fault characteristic of power distribution network.In addition, new energy class DG power output has certain randomness so that match somebody with somebody The problem of power network has the two-way indefinite trend of regional area in normal operation, this brings to the protection control of intelligent distribution network Greatly challenge.
Now, existing polytype guard method, these methods are more to be used as event using single small sample electric characteristic amount Hinder criterion, adjusting for failure criterion needs the calculating of complexity more, and needs weight after system operational parameters, the method for operation change Newly adjust.Further, since failure criterion is based on single characteristic quantity, there is great risk in the reliability of protection, when sensor or During person's communication abnormality, easily there is the malfunction even tripping protected.Exemplified by acting on behalf of (Agent) protection, when in Agent system more Easily the protection of relevant range is caused to be judged by accident when information errors occurs in a certain Agent, fault-tolerance is poor.
The guard method of current several types is primarily present following defect：
1. for intelligent distribution network, due to having accessed substantial amounts of distributed power source in network, wherein distributed new is sent out Electrical power output has certain randomness, thus distribution network systems are in normal operation, the problem of there is two-way indefinite trend.This Outside, the access of distributed power source changes fault characteristic, and this brings great difficulty to the protection control of power distribution network.
2. needing to carry out complicated adaptive setting the protection control method of current intelligent distribution network, and working as system operation more Parameter, the method for operation and network topology structure need to adjust again after changing, and time-consuming.
3. protection control method instantly is to carry out status monitoring and breakdown judge based on single small sample characteristic quantity mostly, When sensor or communication abnormality, the malfunction easily protected even tripping.
4. most of protection control method is not carried out to intelligent distribution network big data in current intelligent distribution network It is rationally effective to utilize, the resource of preciousness had both been wasted, has been unfavorable for the safe and stable operation of system again.
The content of the invention
In order to solve the above technical problems, the present invention provides a kind of distribution network line fault positioning side based on big data technology Method.
The technical scheme of use is as follows：
A kind of distribution network line fault localization method based on big data technology, it is characterised in that comprise the following steps：A、 DIT is laid, DIT is laid according to the topological structure of power distribution network, DIT can collect remote signalling amount MMS, form big data measurement apparatus, should Big data measurement apparatus feature is that the uniform cloth of DIT is placed on whole power distribution network；
B, placement WPCD devices, lay WPCD devices, for receiving the distant of each detection zone DIT in required detection zone Traffic MMS, and stored；
C, formation adjacency matrix, WPCD devices collect intelligence by receiving the remote signalling amount MMS transmitted by each switchyard DIT The state information that power distribution network is respectively switched, and form the adjacency matrix for characterizing power distribution network topological relation；
D, formation reachability matrix, pass through the computing of adjacency matrix, and each switchyard DIT maximums of WPCD devices formation reflection are protected Protect the reachability matrix of scope；
E, determine complete incidence matrix, according to each DIT maximum protection scope, WPCD devices can determine it is multiple completely Incidence matrix；These complete incidence matrixes reflect the topology pass between each side and each node in the range of each DIT maximum protections System；
F, fault location and isolation, by the computing of complete incidence matrix and electric current column vector, WPCD devices can be distinguished The 3 wheel current differentials such as above-mentioned master is differential, the differential and remote standby of nearly standby is differential are carried out to each DIT to calculate；When failure occurs Afterwards, the public domain that difference current is more than setting valve is fault zone, it is achieved thereby that distribution network failure detection and positioning； DIT of the WPCD devices into the region sends trip signal, you can complete the isolation of failure.
A kind of distribution network line fault localization method based on big data technology as described above, it is characterised in that the WPCD Device is responsible for the adjacency matrix that centrally updated and storage characterizes power distribution network topological structure.
The invention has the advantages that：
The present invention is on the basis of intelligent distribution network big data and network topology incidence relation, it is proposed that one kind is based on big number According to the distribution network line fault localization method of technology.First, this method utilizes power distribution network integrated intelligent terminal device (Distribution network Integrative intelligent Terminal, DIT) receives power distribution network big data, Such as sampled data.Then, the data that each node DIT devices are gathered are pre-processed.WPCD devices pass through each switchyard DIT Transmitted remote signalling amount MMS collects the state information that intelligent distribution network is respectively switched, and forms sign power distribution network topological relation Adjacency matrix.Pass through the computing of adjacency matrix, the reachable square of each switchyard DIT maximum protection scopes of WPCD devices formation reflection Battle array.According to each DIT maximum protection scope, WPCD devices can determine to reflect in the range of the DIT maximum protections each side and each The complete incidence matrix of topological relation between individual node.Hereafter, by the computing of complete incidence matrix, WPCD devices can be right respectively Each DIT lead the 3 wheel current differentials such as the differential and remote standby of differential, near standby is differential and calculated.Finally, when distribution network line is sent out During raw failure, the public domain that difference current is more than setting valve is fault zone, it is achieved thereby that fault location.The present invention has Effect improves the real-time and high efficiency of mass data processing, can make real-time judge according to abundant power distribution network information, believes Breath interaction is comprehensive, to maintaining stability of power system to have good effect.
Brief description of the drawings
Fig. 1 is method implementation process schematic diagram of the invention.
Fig. 2 is the operation with closed ring power distribution network wiring diagram with branch line of the invention.
Fig. 3 is the associated region schematic diagram for often taking turns current differential of the invention.
Embodiment
To make the technical problem to be solved in the present invention, technical scheme and advantage clearer, below in conjunction with accompanying drawing and tool Body embodiment is described in detail.
Distribution network line fault localization method based on big data technology, key step includes：
1. first, laying DIT according to the topological structure of power distribution network, the big data measurement apparatus formed is as shown in Figure 2.Its Feature is that the uniform cloth of DIT is placed on whole power distribution network.
2. laying WPCD devices in required detection zone, for receiving power distribution network big data, such as each detection zone is distant The DIT data such as traffic, and stored.
3.WPCD devices collect what intelligent distribution network was respectively switched by receiving the remote signalling amount MMS transmitted by each switchyard DIT State information, and form the adjacency matrix for characterizing power distribution network topological relation.
4. by the computing of adjacency matrix, the formation of WPCD devices reflects the reachable of each switchyard DIT maximum protection scopes Matrix.
5. according to each DIT maximum protection scope, WPCD devices can determine multiple complete incidence matrixes.These are complete Incidence matrix reflects the topological relation between each side and each node in the range of each DIT maximum protections.
6. according to the malfunction of power distribution network, carry out fault location and isolation.By complete incidence matrix and electric current arrange to The computing of amount, WPCD devices can carry out that above-mentioned master is differential, the differential and remote standby of nearly standby is differential etc. 3 to each DIT respectively Current differential is taken turns to calculate.After failure occurs, the public domain that difference current is more than setting valve is fault zone, so as to realize Distribution network failure detection and position.DIT of the WPCD devices into the region sends trip signal, you can complete failure every From.
The present invention principle be：
1. the reachability matrix formation basic theory based on big data
Distribution network line fault positioning and III section one of partition method and conventional current proposed by the present invention based on big data Sample, each DIT maximum protection scope covers next line end.For the power distribution network that topological structure does not change, Any DIT maximum protection scope is obtained with by intuitively method.But, the topology of power distribution network often changes, So needing a kind of algorithm to correct DIT maximum protection scope in real time.The computing of adjacency matrix can just solve this and ask Topic.
Region WPCD devices are responsible for the adjacency matrix that centrally updated and storage characterizes power distribution network topological structure.Assuming that power distribution network It is made up of the feeder line of 2 times operation with closed ring, as shown in Figure 2.
For the power distribution network shown in Fig. 2, the exponent number of the adjacency matrix of its topological structure is 14 ranks, as follows.
Then, according to adjacency matrix theorem, it may be determined that each switchyard DIT maximum protection scope, that is, reflect maximum The reachability matrix of protection domain, it is as follows.
Reachability matrix P the first row is observed, node n can be obtained1Maximum protection scope include node n1~n3、n5~n8 And n11~n14, it is consistent with intuitively result.
, it is necessary to by the computing of adjacency matrix, redefine reflection each after the topological structure of power distribution network changes The reachability matrix of DIT maximum protection scopes.
The advantage of each switchyard DIT maximum protection scopes is determined by the computing of adjacency matrix is：When breaker is jumped After lock, the topological structure of power distribution network changes.WPCD devices change the element in adjacency matrix, and the fortune for passing through adjacency matrix Calculate, readjust each DIT maximum protection scope.WPCD can be in real time with automatically realizing that these are handled, without very important person It is carefully and neatly done fixed.
2. the complete incidence matrix formation basic theory based on big data
According to each DIT reachability matrix, WPCD devices can also obtain the complete incidence matrix of the DIT, and be deposited Storage.Complete incidence matrix reflects the topological relation of each side and node, can be for forming the associated region of the DIT.
With above-mentioned node n1Exemplified by, for forming the complete incidence matrix M that it leads differential associated region1For：
The formation principle of the differential associated region of nearly standby is on the basis of main differential complete incidence matrix, to merge Interdependent node (eliminates the main differential side for exchanging data), forms new complete incidence matrix.In above-mentioned DIT nodes n1It is complete Fully associative matrix M1On the basis of, such as side e1, in side e1One row only have node n1With n7Corresponding element is not 0, due to Side e1Belong to node n1, so obtaining egress n7Based on differential associated region.Observe node n7A line, it is not 0 element pair to find The side e answered1With e2.From matrix M1Side e can be obtained2Associated node is n7With n2, it is necessary to merge node n7With n2.By to matrix M1N7With n2Row is added, and eliminates node n7, can obtain for forming node n1Nearly standby associated region it is new complete Fully associative matrix M2：
The formation principle of the differential associated region of remote standby is, on the basis of the differential complete incidence matrix of nearly standby, Merge interdependent node (eliminating the differential side for exchanging data of nearly standby), form new complete incidence matrix.Such as above-mentioned DIT sections Point n1Side e1, in the differential complete incidence matrix M of above-mentioned nearly standby2On the basis of, first pass through side e1Find merge node n2,7, observation merge node n2,7, find out matrix M2In the row it is all be 0 side e1、e3And e13.From matrix M2Understand, it is necessary to Merge node n2,7、n8And n13.By to matrix M2N2,7、n8And n13Row is added, and can be obtained for forming node n1's The new complete incidence matrix M of remote standby associated region3：
Switchyard DIT associated region is formed by the computing of complete incidence matrix, both accurately and reliably, can be reduced again The unnecessary traffic.Moreover, after the topological structure of power distribution network changes, region WPCD devices can be automatic according to algorithm The reachability matrix and complete incidence matrix of each DIT maximum protections scope of generation reflection, each DIT of adjust automatically association area Domain, without being modified again to program.
3. the distribution network line fault localization method based on big data
With above-mentioned node n1Side e1Exemplified by.According to complete incidence matrix M1, define electric current column vectorIn side e1In one row, only node n1With n7Corresponding element It is not 0.Because side e1In node n1In, so node n7Based on differential associated region.Extract node n7A line, constitute row to Measure m1=(- 1, -1,0,0,0,0,0,0,0,0,0,0).So, main difference currentIfThen think that failure just occurs in node n7In corresponding element.
Meanwhile, according to complete incidence matrix M2, in side e1In one row, only node n1With n2,7Corresponding element is not 0.Cause For side e1In node n1In, so node n2,7For the differential associated region of nearly standby.Extract node n2,7A line, constitutes row vector m2=[- 1,0,1,0,0,0,0,0,0,0,1,0].So, nearly standby difference currentIfThen failure judgement occurs by node n7With n2The region of composition, i.e., the near differential associated region of standby.
Meanwhile, according to complete incidence matrix M3, in side e1In one row, only node n1With n2,7,8,13Corresponding element is not 0.Because side e1In node n1In, so node n2,7,8,13For the differential associated region of remote standby.Extract node n2,7,8,13A line, Constitute row vector m3=[- 1,0,0, -1,0,0,0,0,0,0,0, -1].So, remote standby difference currentIfThen failure judgement occurs by node n2、n7、n8And n13The area of composition Domain, i.e., the remote differential associated region of standby.
3 wheel current differentials of summary, can obtain the associated region of every wheel current differential, as shown in Figure 3.

Claims (2)

1. a kind of distribution network line fault localization method based on big data technology, it is characterised in that comprise the following steps：A, cloth DIT is put, DIT is laid according to the topological structure of power distribution network, DIT can collect remote signalling amount MMS, form big data measurement apparatus, this is big Data measurement unit feature is that the uniform cloth of DIT is placed on whole power distribution network；
B, placement WPCD devices, lay WPCD devices, for receiving each detection zone DIT remote signalling amount in required detection zone MMS, and stored；
C, formation adjacency matrix, WPCD devices collect intelligent power distribution by receiving the remote signalling amount MMS transmitted by each switchyard DIT The state information of each switch is netted, and forms the adjacency matrix for characterizing power distribution network topological relation；
D, formation reachability matrix, pass through the computing of adjacency matrix, each switchyard DIT maximum protection models of WPCD devices formation reflection The reachability matrix enclosed；
E, complete incidence matrix is determined, according to each DIT maximum protection scope, WPCD devices can determine multiple complete associations Matrix；These complete incidence matrixes reflect the topological relation between each side and each node in the range of each DIT maximum protections；
F, fault location and isolation, by the computing of complete incidence matrix and electric current column vector, WPCD devices can be respectively to every Individual DIT carries out the 3 wheel current differentials such as above-mentioned master is differential, the differential and remote standby of nearly standby is differential and calculated；It is poor after failure occurs The public domain that streaming current is more than setting valve is fault zone, it is achieved thereby that distribution network failure detection and positioning；WPCD is filled The DIT put into the region sends trip signal, you can complete the isolation of failure.
2. a kind of distribution network line fault localization method based on big data technology according to claim 1, it is characterised in that The WPCD devices are responsible for the adjacency matrix that centrally updated and storage characterizes power distribution network topological structure.
CN201710487549.1A 2017-06-23 2017-06-23 A kind of distribution network line fault localization method based on big data technology Pending CN107329042A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111157851A (en) * 2020-02-11 2020-05-15 广东工业大学 Power distribution network fault positioning method and system
CN112014686A (en) * 2020-08-14 2020-12-01 国网河南省电力公司封丘县供电公司 Low-voltage distribution network fault positioning method based on shortest path of adjacency matrix

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103824234A (en) * 2014-03-18 2014-05-28 国家电网公司 Blocking and hierarchical structure based power distribution system reliability evaluation method
CN104483601A (en) * 2014-12-24 2015-04-01 广西大学 Power distribution network fault location method based on fault indicators

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103824234A (en) * 2014-03-18 2014-05-28 国家电网公司 Blocking and hierarchical structure based power distribution system reliability evaluation method
CN104483601A (en) * 2014-12-24 2015-04-01 广西大学 Power distribution network fault location method based on fault indicators

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
邹俊雄: "20kV配电网闭环运行特性优化与保护控制策略研究", 《中国博士学位论文全文数据库 工程科技II辑》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111157851A (en) * 2020-02-11 2020-05-15 广东工业大学 Power distribution network fault positioning method and system
CN112014686A (en) * 2020-08-14 2020-12-01 国网河南省电力公司封丘县供电公司 Low-voltage distribution network fault positioning method based on shortest path of adjacency matrix
CN112014686B (en) * 2020-08-14 2022-07-05 国网河南省电力公司封丘县供电公司 Low-voltage distribution network fault positioning method based on shortest path of adjacency matrix

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