CN108594075A - Based on the power distribution network power-off fault localization method for improving ant group algorithm - Google Patents

Based on the power distribution network power-off fault localization method for improving ant group algorithm Download PDF

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CN108594075A
CN108594075A CN201810400810.4A CN201810400810A CN108594075A CN 108594075 A CN108594075 A CN 108594075A CN 201810400810 A CN201810400810 A CN 201810400810A CN 108594075 A CN108594075 A CN 108594075A
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ant
power
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path
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CN108594075B (en
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江和顺
王宏刚
赵永生
秦浩
甘得志
高方景
张蔚翔
朱军伟
陈慧
张良
姜海辉
武文广
周永真
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BEIMING SOFTWARE Co Ltd
State Grid Anhui Electric Power Co Ltd
NARI Group Corp
NARI Nanjing Control System Co Ltd
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State Grid Anhui Electric Power Co Ltd
NARI Group Corp
NARI Nanjing Control System Co Ltd
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    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/08Locating faults in cables, transmission lines, or networks
    • G01R31/081Locating faults in cables, transmission lines, or networks according to type of conductors
    • G01R31/086Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution networks, i.e. with interconnected conductors
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/08Locating faults in cables, transmission lines, or networks
    • G01R31/088Aspects of digital computing
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    • Y04SSYSTEMS 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
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    • Y04S10/50Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
    • Y04S10/52Outage or fault management, e.g. fault detection or location

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Abstract

The invention discloses the power distribution network power-off fault localization methods based on improvement ant group algorithm, including:Overall path matrix is established according to distribution net topology;Power failure decompression user group is divided into positive ant colony, normal power supply user group is divided into negative sense ant colony;Determine positive Pheromone Matrix and negative sense Pheromone Matrix respectively according to the ant colony after differentiation, positive ant group algorithm is driven for positive Pheromone Matrix, negative sense ant group algorithm is driven for negative sense Pheromone Matrix, carry out target search respectively and calculates the element value in each Pheromone Matrix;It has been judged as end condition with all ants, positive Pheromone Matrix and negative sense Pheromone Matrix is carried out to be added merging, obtain total information prime matrix, element maximum value is power-off fault point in total information prime matrix.The present invention improves speed and the accuracy of fault location, shortens the response time, reduce cost, improve customer satisfaction and system performance measure the case where not increasing hardware input cost.

Description

Based on the power distribution network power-off fault localization method for improving ant group algorithm
Technical field
The present invention relates to a kind of based on the power distribution network power-off fault localization method for improving ant group algorithm, belongs to distribution network technology Field.
Background technology
Since intelligent grid in 2009 proposes, China has pushed forward the construction of intelligent distribution network, the automation of power grid comprehensively Level is promoted successively, while user improves higher requirement, mesolow electricity to electric service reliability and power supply quality The fault location on road also becomes the hot spot of research concern.
For a long time, it for the repair call of Low-side faults information electric company Main Basiss resident, is managed using having a power failure Reason system carries out low pressure and crouches network troubleshooting, and the phone squeezed into after being had a power failure according to user prejudges the position of fall insurance or switch It sets, power failure scale, people power, repairing plan is analyzed, determine repairing priority, calculate the strength that works needed for scene, Recovery time is estimated, and manages work on the spot.
Outage Management Systems are distribution management System Subsystems, and control room carries out the tissue tune of power failure repairing by this system Degree and lower job order.Exist in the way of Outage Management Systems progress troubleshooting following insufficient:First, the accuracy judged It is to be improved;Second is that efficiency is low;Third, with duration, the low-voltage networks such as especially present factory, building and residential area make With a large amount of electric wires or cable to realize that low-voltage electric energy dispenses, but low-voltage customer is numerous, circuit numerous and complicated, and event occurs in circuit It is searched after barrier difficult.
Current adapted power grid has been built and the power information acquisition system (AMI) covered comprehensively and power grid geography information system It unites (GIS), will be helpful to power distribution network power-off fault using AMI systems and generalized information system and quickly study and judge.
Invention content
It is an object of the invention to overcome deficiency in the prior art, provide a kind of based on the power distribution network for improving ant group algorithm Power-off fault localization method, the lookup of power distribution network power-off fault point is difficult in the prior art, efficiency is low, is asked with technologies such as durations for solution Topic.
In order to solve the above technical problems, the technical solution adopted in the present invention is:Based on the power distribution network for improving ant group algorithm Power-off fault localization method, includes the following steps:
Power-off fault positioning function is triggered, determines and calls survey target zone together, power failure decompression user group is screened and normal power supply is used Family group, obtains the distribution net topology called together and survey target zone;
Ant colony is established for power failure decompression user group, normal power supply user group, overall path is established according to distribution net topology Matrix;Ant colony is broken up:Wherein power failure decompression user group is divided into positive ant colony, and normal power supply user group is divided into negative sense Ant colony;Positive Pheromone Matrix and negative sense Pheromone Matrix are determined respectively according to the ant colony after differentiation, for positive pheromones square The positive ant group algorithm of battle array driving, negative sense ant group algorithm is driven for negative sense Pheromone Matrix, is carried out target search respectively and is calculated Element value in each Pheromone Matrix;
It has been judged as end condition with all ants, positive Pheromone Matrix has been added with negative sense Pheromone Matrix Merge, obtain total information prime matrix, element maximum value is power-off fault point in total information prime matrix.
Triggering power-off fault positioning function method include:The active of the automatic trigger of voltage monitoring exception and the alarm that has a power failure Triggering.
The automatic trigger condition of the voltage monitoring exception is:Collection voltages value is 0V to single ammeter twice in succession, or Voltage values more than 2 users of same time is 0V.
It is described have a power failure alarm active trigger condition be:Outage Management Systems receive the power failure repair call of user.
Determine that the method for calling survey target zone together is as follows:
Step 101) judges the 10kV/400V low-tension transformers where triggering user, directly calls together and surveys the low-tension transformer Overlay area;
It is called together at each feeder pillar of step 102) and surveys at least two ammeters;
It is lasting to judge during step 103) fault location, if continuing to occur calling together the user malfunction surveyed outside region, new Region in repeat step 101) and step 102).
The method for screening power failure decompression user group and normal power supply user group is as follows:
The user data called together and surveyed in target zone is obtained using AMI systems, including:User's voltage data, asset number, section The power distribution network location information of point number and place;It is ant user to call together and survey user;
The voltage data of ant user is judged:If user's voltage data is normal, it is classified as negative sense ant colony;If User's voltage data is 0, then is classified as positive ant colony.
Using docked with user generalized information system obtain call together survey target zone distribution net topology, include obtain power distribution network section Point number and user node number.
Establishing overall path matrix, the specific method is as follows:
If overall path matrix is P, it is split as medium voltage network path matrix PHWith low voltage electric network path matrix PL, build respectively Vertical path matrix, it is specific as follows:
Build medium voltage network path matrix PH:If node total number is n, transverse and longitudinal is that all nodes arrange in order, The element of matrix indicates that the path between two nodes, element subscript are the both ends node serial number in the path respectively:
When carrying out pheromones iteration using ant group algorithm, for medium voltage network path matrix PHMiddle Partial Elements correspond to The path being not present in actual electric network, then be set as 0 always by element value;Medium voltage network path matrix PHIn about diagonal line pair Battle array, the symmetrical same path of element representation;
Build low voltage electric network path matrix PL:If node total number is m, transverse and longitudinal is that all nodes arrange in order, The element of matrix indicates that the path between two nodes, element subscript are the both ends node serial number in the path respectively:
When carrying out pheromones iteration using ant group algorithm, for low voltage electric network path matrix PLMiddle Partial Elements correspond to The path being not present in actual electric network, then be set as 0 always by element value;Low voltage electric network path matrix PLIn about diagonal line pair Battle array, the symmetrical same path of element representation.
The method for calculating element value in positive Pheromone Matrix is as follows:
Step 101) is according to distribution voltage class, by positive Pheromone Matrix PPIt is divided intoWithTwo positive pheromones Submatrix, if positive information element sub-matrixWithInitial value is 0;
Step 102) starts to search for target, the walking path of every ant is trend according to the number of positive ant Negative direction runs to the root node for studying and judging range from ant initial position, and the path walked leaves pheromones, i.e., positive letter Cease prime matrixWithCorresponding element+1;
Walking is completed with all positive ants in step 103), as the basis for estimation of end condition, i positive ants User then carries out the i positive iteration of positive Pheromone Matrix.
The method for calculating element value in negative sense Pheromone Matrix is as follows:
Step 201) is according to distribution voltage class, by negative sense Pheromone Matrix PNIt is divided intoWithTwo positive pheromones Submatrix, if negative sense information element sub-matrixWithInitial value is 0;
Step 202) starts to search for target, the walking path of every ant is trend according to the number of negative sense ant Negative direction runs to the root node for studying and judging range from ant initial position, and primary information element is removed in the path walked, i.e., negative To Pheromone MatrixWithCorresponding element -1;
Walking is completed with all negative sense ants in step 203), as the basis for estimation of end condition, j negative sense ant User then carries out j negative sense Pheromone Matrix and bears iteration.
Determine that the specific method is as follows for power-off fault point:
Positive information element sub-matrix and negative sense information element sub-matrix are merged:
Statistical information prime matrix PHAnd PLThe numerical value of middle each element, maximum numerical value is fault point position;
If the corresponding element value in multiple paths is equal in result, judge path downstream for fault point position.
Compared with prior art, the advantageous effect of the invention reached is:It has been built based on current adapted power grid and entirely The power information acquisition system (AMI) and power grid GIS (GIS) of face covering carry out mesolow using ant group algorithm The method for rapidly positioning of power-off fault is studied, the case where not increasing hardware input cost, improve fault location speed and Accuracy shortens the response time, reduces cost, improves customer satisfaction and system performance measure.
Description of the drawings
Fig. 1 is the flow chart of the present invention;
Fig. 2 is the network frame topology figure for the low and medium voltage distribution network that the present invention is applicable in.
Specific implementation mode
The invention will be further described below in conjunction with the accompanying drawings.Following embodiment is only used for clearly illustrating the present invention Technical solution, and not intended to limit the protection scope of the present invention.
As shown in Figure 1, being the flow chart of the present invention, the present invention is with the metric data of AMI systems, user information, GIS systems Based on the low and medium voltage distribution network topology data provided of uniting, carries out route searching using ant group algorithm and target is studied and judged, wrap It is logical to include the triggering of power-off fault positioning function, initial data collection processing, improvement ant colony fault locating analysis process and fault message Know forwarding four processes.Expansion description is carried out respectively below for four processes:
Step 1:Power-off fault positioning function triggers:Function triggering includes automatic trigger and the power failure of voltage monitoring exception The active of alarm triggers.The automatic trigger of voltage monitoring exception is that collection voltages value is 0V, Huo Zhetong to single ammeter twice in succession Voltage value more than one user of time 2 is 0V, triggers fault location module at once;The active triggering alarmed that has a power failure is the pipe that has a power failure Reason system receives the power failure repair call of user, then actively triggers fault location module, trouble-shooting source.
Step 2:Initial data collection processing:Enter initial data collection after the triggering of power-off fault locating module to handle Survey target zone is called in link, including determination together, and carrying out user's voltage data using AMI systems calls survey together, and filters out power failure decompression use Family group and normal power supply user group, docking generalized information system obtains the distribution net topology called together and survey target zone, including obtains power distribution network Node serial number and user node number.
Determine that the method for calling survey target zone together is as follows:
Step 101) judges the 10kV/400V low-tension transformers where triggering user, directly calls together and surveys the low-tension transformer Overlay area;
It is called together at each feeder pillar of step 102) and surveys at least two ammeters;
103) lasting to judge during fault location, if continuing to occur calling together the user malfunction surveyed outside region, in new area Step 101) and step 102) are repeated in domain.
By taking the failure A in Fig. 2 as an example, it is assumed that the power failure decompression user initially triggered is that low-voltage customer 6,18 and middle pressure are big User 18, then are judged using above-mentioned rule, will directly call survey target zone together and are determined as 110kV/10V transformers in Fig. 2 frameworks Root node, it is all users shown in legend to call together and survey user.
The method for screening power failure decompression user group and normal power supply user group is as follows:
The user data called together and surveyed in target zone is obtained using AMI systems, including:User's voltage data, asset number, section The power distribution network location information of point number and place;It is ant user to call together and survey user.
The voltage data of ant user is judged:If user's voltage data is normal, it is classified as negative sense ant colony;If User's voltage data is 0, then is classified as positive ant colony.To reduce the sparsity of matrix, pressed and 400V low pressure nodes in 10kV It is encoded separately.Equally by taking failure A in Fig. 2 as an example, positive ant colony include 2 Middle Voltages 5,7,12 low-voltage customers 5,6,8, 9、11、12、14、15、18、19、21、 22.Negative sense ant colony include 2 Middle Voltages 14,16,20 low-voltage customers 27,28,30, 31、33、 34、36、37、43、44、45、46、48、49、51、52、55、56、58、59。
Step 3:Improve ant colony fault locating analysis process:
The first step is ant colony structure:User and regional power grid are surveyed for all call together, ant colony and overall path matrix is established, wraps Containing following steps:
If overall path matrix is P, P is split as medium voltage network path matrix PHWith low voltage electric network path matrix PL, respectively Establish Pheromone Matrix;
Build medium voltage network path matrix, i.e. Pheromone Matrix PH:If node total number is n, transverse and longitudinal is all sections It presses and is ranked sequentially, the element of matrix indicates that the path between two nodes, element subscript are that two end nodes in the path are compiled respectively Number:
Partial Elements correspond in actual electric network in matrix, and the path is not present, and in order to handle conveniently, are built in matrix In, the element is still listed, when carrying out pheromones iteration using ant group algorithm, which is set as 0, due to the path Always it is not present, pheromones value will not change;
The matrix is poised for battle about diagonal line, the symmetrical same path of element representation, such as ph1-2With ph2-1Indicate same path. By taking failure A as an example, the Pheromone Matrix P that is built for medium voltage networkH, node total number is 16, and transverse and longitudinal is all nodes By being ranked sequentially from 1-16,16*16 Pheromone Matrixes are built into, the element of matrix indicates the path between two nodes respectively.
Build low voltage electric network path matrix, i.e. Pheromone Matrix PL:Node total number is m, and transverse and longitudinal is all nodes It arranges in order, the element of matrix indicates that the path between two nodes, element subscript are the both ends node serial number in the path respectively:
Partial Elements correspond in actual electric network in matrix, and the path is not present, and in order to handle conveniently, are built in matrix In, the element is still listed, when carrying out pheromones iteration using ant group algorithm, which is set as 0, due to the path Always it is not present, pheromones value will not change;
The matrix is poised for battle about diagonal line, the symmetrical same path of element representation, such as pl1-2With pl2-1Indicate same path. By taking failure A as an example, the Pheromone Matrix P that is built for low voltage electric networkL, node total number is 59, and transverse and longitudinal is all nodes By being ranked sequentially from 1-59,59*59 Pheromone Matrixes are built into, the element of matrix indicates the path between two nodes respectively.
Second step is ant colony differentiation:Ant colony is divided into positive ant colony (power failure decompression user) and negative sense ant colony is (normal to supply Electric user), and determine positive Pheromone Matrix PPWith negative sense Pheromone Matrix PN
For positive Pheromone Matrix PP, the number of node, the dimension of matrix, the meaning of element and each element just Initial value is consistent with overall path, is divided into practical judgementWith
For negative sense Pheromone Matrix PN, the number of node, the dimension of matrix, the meaning of element and each element just Initial value is consistent with overall path, is divided into practical judgementWith
In failure A examples, it is the matrix that the first step is established in form to Pheromone Matrix to differentiate come positive and negative Equally, and initial value is 0.
Third step is ant colony search:For positive ant colony (power failure decompression user) and negative sense ant colony (normal power supply user), Positive ant group algorithm and negative sense ant group algorithm is respectively started, carry out target search respectively and calculates the element in each Pheromone Matrix Value, comprises the steps of:
Positive ant group algorithm, i.e. pheromones forward cumulative iterative process, comprise the steps of:
1) positive Pheromone MatrixWithInitial value is 0;
2) according to the number of positive ant, starting to search for target, the walking path of every ant is the negative direction of trend, The root node for studying and judging range is run to from ant initial position, the path walked is intended to leave pheromones, i.e., positive pheromones MatrixWithCorresponding element+1;
3) walking is completed with all positive ants, as the basis for estimation of end condition, i positive ant users, Then carry out the i positive iteration of positive Pheromone Matrix.
By taking failure A as an example, it is contemplated that the versatility of method is listed by taking the relatively small number of medium voltage distribution network of number of nodes as an example Positive Pheromone MatrixDo not mark element value in the matrix is 0:
Negative sense ant group algorithm, as improves ant group algorithm, quotes the thinking that the pheromones in existing ant group algorithm disappear, into Row information element, which disappears to accumulate, bears iterative process, comprises the steps of:
1) negative sense Pheromone MatrixOrInitial value is 0;
2) according to the number of negative sense ant, starting to search for target, the walking path of every ant is the negative direction of trend, The root node for studying and judging range is run to from ant initial position, the path walked is intended to remove primary information element, i.e. negative sense is believed Cease prime matrixOrCorresponding element -1;
3) walking is completed with all negative sense ants, as the basis for estimation of end condition, j negative sense ant user, It then carries out j negative sense Pheromone Matrix and bears iteration.
With in failure A examples, it is contemplated that the versatility of method, by taking the relatively small number of medium voltage distribution network of number of nodes as an example, row Go out negative sense Pheromone MatrixDo not mark element value in the matrix is 0:
4th step is that target determines, is comprised the steps of:
1) positive Pheromone Matrix and negative sense Pheromone Matrix are merged:
2) statistical information prime matrix PHAnd PLThe numerical value of middle each element, maximum numerical value is fault point position.
3) in failure A examples, Pheromone Matrix PHLast numerical value is:
Can determine whether path 1-2 sections from the element value of matrix is the source of trouble.
4) if the corresponding element value in multiple paths is equal in result, judge path downstream for abort situation.
Step 4:Fault message notice forwarding:After abort situation determines and notify forwarding Outage Management Systems to carry out The investigation and telegram in reply of next step.
The method of the present invention is mainly used in low and medium voltage distribution network, and distribution net work structure is radial, the trend of single supply power supply Direction is one direction, and middle pressure is 10kV, low pressure 400V.It has been built based on current adapted power grid and what is covered comprehensively uses telecommunications Acquisition system (AMI) and power grid GIS (GIS) are ceased, using ant group algorithm, carries out the quick of mesolow power-off fault Localization method is studied, and the case where not increasing hardware input cost, is improved speed and the accuracy of fault location, is shortened sound Between seasonable, cost is reduced, customer satisfaction and system performance measure are improved.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art For member, without departing from the technical principles of the invention, several improvement and deformations can also be made, these improvement and deformations Also it should be regarded as protection scope of the present invention.

Claims (11)

1. based on the power distribution network power-off fault localization method for improving ant group algorithm, which is characterized in that include the following steps:
Power-off fault positioning function is triggered, determines and calls survey target zone together, screens power failure decompression user group and normal power supply user group, Obtain the distribution net topology called together and survey target zone;
Ant colony is established for power failure decompression user group, normal power supply user group, overall path matrix is established according to distribution net topology;
Ant colony is broken up:Wherein power failure decompression user group is divided into positive ant colony, and normal power supply user group is divided into negative sense Ant colony;
Positive Pheromone Matrix and negative sense Pheromone Matrix are determined respectively according to the ant colony after differentiation, for positive Pheromone Matrix The positive ant group algorithm of driving, negative sense ant group algorithm is driven for negative sense Pheromone Matrix, is carried out target search respectively and is calculated each Element value in Pheromone Matrix;
It has been judged as end condition with all ants, positive Pheromone Matrix and negative sense Pheromone Matrix is subjected to phase adduction And total information prime matrix is obtained, element maximum value is power-off fault point in total information prime matrix.
2. according to claim 1 based on the power distribution network power-off fault localization method for improving ant group algorithm, which is characterized in that Triggering power-off fault positioning function method include:The active triggering of the automatic trigger of voltage monitoring exception and the alarm that has a power failure.
3. according to claim 2 based on the power distribution network power-off fault localization method for improving ant group algorithm, which is characterized in that The automatic trigger condition of the voltage monitoring exception is:Collection voltages value is 0V or same time 2 to single ammeter twice in succession Voltage value more than a user is 0V.
4. according to claim 2 based on the power distribution network power-off fault localization method for improving ant group algorithm, which is characterized in that It is described have a power failure alarm active trigger condition be:Outage Management Systems receive the power failure repair call of user.
5. according to claim 1 based on the power distribution network power-off fault localization method for improving ant group algorithm, which is characterized in that Determine that the method for calling survey target zone together is as follows:
Step 101) judges the 10kV/400V low-tension transformers where triggering user, directly calls together and surveys the low-tension transformer covering Region;
It is called together at each feeder pillar of step 102) and surveys at least two ammeters;
It is lasting to judge during step 103) fault location, if continuing to occur calling together the user malfunction surveyed outside region, in new area Step 101) and step 102) are repeated in domain.
6. according to claim 1 based on the power distribution network power-off fault localization method for improving ant group algorithm, which is characterized in that The method for screening power failure decompression user group and normal power supply user group is as follows:
The user data called together and surveyed in target zone is obtained using AMI systems, including:User's voltage data, asset number, node are compiled Number and place power distribution network location information;It is ant user to call together and survey user;
The voltage data of ant user is judged:If user's voltage data is normal, it is classified as negative sense ant colony;If user Voltage data is 0, then is classified as positive ant colony.
7. according to claim 1 based on the power distribution network power-off fault localization method for improving ant group algorithm, which is characterized in that Using docked with user generalized information system obtain call together survey target zone distribution net topology, including obtain power distribution network node serial number and User node is numbered.
8. according to claim 1 based on the power distribution network power-off fault localization method for improving ant group algorithm, which is characterized in that Establishing overall path matrix, the specific method is as follows:
If overall path matrix is P, it is split as medium voltage network path matrix PHWith low voltage electric network path matrix PL, road is established respectively Drive matrix, it is specific as follows:
Build medium voltage network path matrix PH:If node total number is n, transverse and longitudinal is that all nodes arrange in order, matrix Element indicates that the path between two nodes, element subscript are the both ends node serial number in the path respectively:
When carrying out pheromones iteration using ant group algorithm, for medium voltage network path matrix PHMiddle Partial Elements correspond to reality The path being not present in power grid, then be set as 0 always by element value;Medium voltage network path matrix PHIn about diagonal line be poised for battle, it is right The same path of element representation of title;
Build low voltage electric network path matrix PL:If node total number is m, transverse and longitudinal is that all nodes arrange in order, matrix Element indicates that the path between two nodes, element subscript are the both ends node serial number in the path respectively:
When carrying out pheromones iteration using ant group algorithm, for low voltage electric network path matrix PLMiddle Partial Elements correspond to reality The path being not present in power grid, then be set as 0 always by element value;Low voltage electric network path matrix PLIn about diagonal line be poised for battle, it is right The same path of element representation of title.
9. according to claim 1 based on the power distribution network power-off fault localization method for improving ant group algorithm, which is characterized in that The method for calculating element value in positive Pheromone Matrix is as follows:
Step 101) is according to distribution network voltage grade, by positive Pheromone Matrix PPIt is divided intoWithTwo positive information sub-prime squares Battle array, if positive Pheromone MatrixWithInitial value is 0;
Step 102) starts to search for target, the walking path of every ant is the negative side of trend according to the number of positive ant To running to the root node for studying and judging range from ant initial position, the path walked leaves pheromones, i.e., positive pheromones MatrixWithCorresponding element+1;
Walking is completed with all positive ants in step 103), and as the basis for estimation of end condition, i only use by positive ant Family then carries out the i positive iteration of positive Pheromone Matrix.
10. according to claim 9 based on the power distribution network power-off fault localization method for improving ant group algorithm, feature exists In the method for calculating element value in negative sense Pheromone Matrix is as follows:
Step 201) is according to distribution network voltage grade, by negative sense Pheromone Matrix PNIt is divided intoWithTwo negative sense information sub-prime squares Battle array, if negative sense information element sub-matrixWithInitial value is 0;
Step 202) starts to search for target, the walking path of every ant is the negative side of trend according to the number of negative sense ant To, the root node for studying and judging range is run to from ant initial position, the path walked remove primary information element, i.e., negative sense believe Cease element sub-matrixWithCorresponding element -1;
Walking is completed with all negative sense ants in step 203), and as the basis for estimation of end condition, j negative sense ant is used Family then carries out j negative sense Pheromone Matrix and bears iteration.
11. according to claim 10 based on the power distribution network power-off fault localization method for improving ant group algorithm, feature exists In determining that the specific method is as follows for power-off fault point:
Positive information element sub-matrix and negative sense information element sub-matrix are merged:
Statistical information prime matrix PHAnd PLThe numerical value of middle each element, maximum numerical value is fault point position;If multiple in result The corresponding element value in path is equal, then judges path downstream for fault point position.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111125694A (en) * 2019-12-20 2020-05-08 杭州安恒信息技术股份有限公司 Threat information analysis method and system based on ant colony algorithm
CN114113948A (en) * 2021-12-03 2022-03-01 福建省宏闽电力工程监理有限公司 Power distribution network fault monitoring method
CN115754578A (en) * 2022-08-30 2023-03-07 国网辽宁省电力有限公司电力科学研究院 Active power distribution network fault positioning method and system based on self-adaptive ant colony algorithm

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7693049B2 (en) * 2004-10-29 2010-04-06 Honeywell International Inc. Self-organization of sensor networks using ant colony optimization
CN102254070A (en) * 2011-07-15 2011-11-23 福州大学 Method for optimally designing electromagnetic valve based on ant colony optimization
CN105067956A (en) * 2015-08-26 2015-11-18 云南电网有限责任公司电力科学研究院 Anti-colony-algorithm-based distribution network fault positioning method
CN106646100A (en) * 2016-09-14 2017-05-10 浙江群力电气有限公司 Incomplete measurement and control power distribution network fault locating method
CN106684869A (en) * 2017-03-17 2017-05-17 燕山大学 Active distribution network failure recovery strategy considering inside and outside games

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7693049B2 (en) * 2004-10-29 2010-04-06 Honeywell International Inc. Self-organization of sensor networks using ant colony optimization
CN102254070A (en) * 2011-07-15 2011-11-23 福州大学 Method for optimally designing electromagnetic valve based on ant colony optimization
CN105067956A (en) * 2015-08-26 2015-11-18 云南电网有限责任公司电力科学研究院 Anti-colony-algorithm-based distribution network fault positioning method
CN106646100A (en) * 2016-09-14 2017-05-10 浙江群力电气有限公司 Incomplete measurement and control power distribution network fault locating method
CN106684869A (en) * 2017-03-17 2017-05-17 燕山大学 Active distribution network failure recovery strategy considering inside and outside games

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
刘学琴 等: "基于蚁群算法的配电网故障恢复重构", 《广东电力》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111125694A (en) * 2019-12-20 2020-05-08 杭州安恒信息技术股份有限公司 Threat information analysis method and system based on ant colony algorithm
CN114113948A (en) * 2021-12-03 2022-03-01 福建省宏闽电力工程监理有限公司 Power distribution network fault monitoring method
CN114113948B (en) * 2021-12-03 2023-10-20 中达安股份有限公司 Power distribution network fault monitoring method
CN115754578A (en) * 2022-08-30 2023-03-07 国网辽宁省电力有限公司电力科学研究院 Active power distribution network fault positioning method and system based on self-adaptive ant colony algorithm

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