CN111413582B - Power distribution network fault accurate positioning method utilizing multiple types of measurement data - Google Patents
Power distribution network fault accurate positioning method utilizing multiple types of measurement data Download PDFInfo
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- CN111413582B CN111413582B CN202010196985.5A CN202010196985A CN111413582B CN 111413582 B CN111413582 B CN 111413582B CN 202010196985 A CN202010196985 A CN 202010196985A CN 111413582 B CN111413582 B CN 111413582B
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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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Abstract
The invention discloses a power distribution network fault accurate positioning method utilizing multiple types of measurement data, which comprises the following steps: step S1: establishing a power distribution network fault positioning model fusing multiple types of data offline; step S2: after the fault occurs, collecting action data of a power distribution network breaker and a fuse, state data of a fault indicator and outage data of an intelligent ammeter on line, and uploading the information to a power distribution operation center; step S3: the power distribution network fault positioning model reads the action data of the circuit breaker from a power distribution network operation center and positions a fault area; step S4: in the fault area, the power distribution network fault positioning model positions a fault section according to the state data of the fault indicator in the power distribution network fault positioning model; the invention has the advantages that: the particle dimension of the section positioning model is greatly reduced due to the participation of the protection data, and the positioning speed is higher; the fault section can be positioned, the fault element can be positioned, and the positioning accuracy is higher.
Description
Technical Field
The invention relates to the technical field of power distribution network fault positioning, isolation and power supply recovery, in particular to the technical field of power distribution network fault positioning methods utilizing multiple types of measurement data.
Background
In extreme environments, such as storm, snow disaster and the like, the elasticity of the power distribution network directly relates to the power supply reliability of the power distribution network, and in order to improve the reliability of the power distribution network in the extreme environments, the elasticity of the power distribution network must be increased, and three stages exist for improving the elasticity of the power distribution network: a strengthening stage before failure, a reasonable regulation stage in failure and a recovery stage after failure; wherein a fast and accurate localization of the fault has an important role in the third phase. With the continuous progress of technology, intelligent devices such as circuit breakers, sectionalizers, reclosers, fault indicators, intelligent electric meters and the like are widely used in power distribution networks, and the devices provide a new research background for fault location of the power distribution networks. Many specialists have studied fault location of distribution networks based on fault indicators, and although some achievements have been achieved, these location methods only use the status information of the fault indicators, resulting in poor reliability and accuracy.
Disclosure of Invention
In order to solve the problems, the invention provides a power distribution network fault accurate positioning method which can utilize multiple types of measurement data in a power distribution network, enables fault positioning to have higher reliability, can position fault elements and has higher positioning accuracy.
The technical solution adopted by the invention for solving the technical problems is as follows:
the accurate positioning method for the faults of the power distribution network by utilizing the multiple types of measurement data is characterized by comprising the following steps of:
step S1: and establishing a power distribution network fault positioning model integrating multiple types of data in an off-line mode, wherein the power distribution network fault positioning model comprises three parts: fault region positioning, fault section positioning and fault element positioning;
step S2: after the fault occurs, collecting action data of a power distribution network breaker and a fuse, state data of a fault indicator and outage data of an intelligent ammeter on line, and uploading the information to a power distribution operation center;
step S3: the power distribution network fault positioning model reads the action data of the circuit breaker from a power distribution network operation center and positions a fault area;
the step of locating the fault area according to the breaker action data comprises:
1) Establishing a breaker and region association matrix C, wherein the element coding principle is as follows: section is within the protection range of the breaker, C i =1, otherwise C i ＝0；
2) Determining an action matrix R according to the collected breaker action data, wherein the element coding principle is as follows: circuit breaker R i Action, R i =1, otherwise R i ＝0；
3) Multiplying the correlation matrix C by the action matrix R to obtain a fault area matrix A.
Step S4: in the fault area, the power distribution network fault positioning model positions a fault section according to the state data of the fault indicator in the power distribution network fault positioning model;
the method of locating the faulty section based on the fault indicator status data within it is as follows: the fault indicator state data in the fault area is imported into the following section positioning model, CPLEX is utilized to solve the section positioning model, and the solved result comprises a fault section matrix, a node missing report matrix and a node false report matrix;
s.t.y i∈B -x j∈A ≥0
-------------------------------------
y 1 +y 2 +…+y k∈Bi -y i∈B ≥0
y i∈B -y k∈Bi ≥0
-------------------------------------
-------------------------------------
1-x i∈A -x j∈A,j≠i ≥0
-------------------------------------
1-m i∈B -f i∈B ≥0
wherein N is A Representing the number of segments within the failure area a, B representing the set of nodes within the failure area a, bi representing the set of nodes downstream of node i, x i 、f i 、m i Respectively representing node states, node missing report and node false report, wherein the variables are decision variables, y i 、As intermediate variable, z i And the node state data actually received by the power distribution operation center.
Step S5: and in the fault section, the power distribution network fault positioning model positions a fault element according to the fuse action data and the power failure data of the intelligent ammeter.
The step of determining the fault element by using the fuse action data, the power failure data of the intelligent ammeter and the power distribution network fault location model comprises the following steps:
1) Establishing a fuse and intelligent ammeter and fault element association matrix E; the element coding principle is as follows: the faulty element being downstream of the fuse, E i =1, otherwise E i =0; the faulty element is upstream of the smart meter, E i =1, otherwise E i ＝0；
2) Determining an action matrix T according to the collected fuse action data and the power-off data of the intelligent ammeter; the element coding principle is as follows: fuse T i Action T i ＝1Otherwise T i =0; smart electric meter SM i Power-off, T i =1, otherwise T i ＝0；
3) Multiplying the correlation matrix E by the action matrix T to obtain a fault element matrix S.
The beneficial effects achieved by adopting the technical proposal of the invention are as follows: according to the method, firstly, faults are positioned to a certain area according to the action data of the circuit breaker; then using the node status data of the fault indicator to locate the fault to a section; then, positioning the fault to a certain element by using the fuse action data and the power-off data of the intelligent ammeter; therefore, multiple types of measurement data in the power distribution network are fused, and fault positioning has higher reliability; the particle dimension of the section positioning model is greatly reduced due to the participation of the protection data, and the positioning speed is higher; the fault section can be positioned, the fault element can be positioned, and the positioning accuracy is higher.
Drawings
FIG. 1 is a block diagram of a 22 node power distribution network;
FIG. 2 is a diagram of a power distribution network fault location model incorporating multiple types of measurement data;
fig. 3 is a power supply side structure view on the section SL 13.
Detailed Description
As shown in fig. 1, a 22-node power distribution network model is used as an embodiment of the present invention, and the model includes 22 fault indicators, namely 22 nodes, and the nodes are denoted by FI1-FI22, wherein switches at FI1, FI3 and FI11 are circuit breakers with overlapping functions, and the three circuit breakers divide the power distribution network into three areas A1, A2 and A3. The node divides the power distribution network into 22 sections, the sections are denoted by SL1-SL22, distributed power sources DG1 and DG2 are connected to the tail ends of the sections SL18 and SL22, the capacities of the DG1 and DG2 are respectively set to be 1.65MW and 1.5MW, and a short circuit is arranged on the power supply side face of the SL 13.
A power distribution network fault accurate positioning method utilizing multiple types of measurement data comprises the following steps:
step S1: and establishing a power distribution network fault positioning model integrating multiple types of data in an off-line mode, wherein the power distribution network fault positioning model comprises three parts: fault region positioning, fault section positioning and fault element positioning;
as shown in fig. 2, the fault positioning model of the power distribution network firstly positions a fault to a certain area by using a=r·c according to the action data of the circuit breaker; then based on the node status data of the fault indicator, utilizeLocating a fault to a section; then, based on the fuse operation data and the power failure data of the smart meter, the fault is located to a certain element by s=e·t.
Step S2: after the transient fault occurs, collecting action data of a circuit breaker and a fuse of the power distribution network, state data of a fault indicator and outage data of an intelligent ammeter on line, and uploading the information to a power distribution operation center;
in this embodiment, the breaker action data R of the power distribution network collected online is:
the fault indicator state data Z collected on line is:
Z＝[SL11～SL18]＝[1111000000111001111011]
the fuse action data and the power-off data T of the intelligent ammeter which are collected on line are as follows:
T＝[FU1,FU2,FU3,SM1,SM2] T ＝[01010] T
step S3: the power distribution network fault positioning model reads the action data of the circuit breaker from a power distribution network operation center and positions a fault area; the step of locating the fault area according to the breaker action data comprises:
1) Establishing a breaker and region (composed of a plurality of sections) association matrix C, wherein the element coding principle is as follows: section is within the protection range of the breaker, C i =1, otherwise C i ＝0；
2) Determining an action matrix R according to the collected breaker action data, wherein the element coding principle is as follows: circuit breaker R i Action, R i =1, otherwise R i ＝0；
3) Multiplying the correlation matrix C by the action matrix R to obtain a fault area matrix A.
In this embodiment, the association matrix of the circuit breaker and the area established according to the topology structure of the power distribution network is:
importing the breaker action data R of the power distribution operation center into a power distribution network fault positioning model, and multiplying the incidence matrix C by the action matrix R to obtain a fault area matrix A;
it can thus be determined that zone three, which contains zones SL11-SL18, is faulty.
Step S4: and in the fault area, the fault section of the power distribution network is positioned by the fault positioning model according to the state data of the fault indicator in the power distribution network, and the specific steps are as follows: the fault indicator state data in the fault area is imported into the following section positioning model, CPLEX is utilized to solve the section positioning model, and the solved result comprises a fault section matrix, a node missing report matrix and a node false report matrix;
s.t.y i∈B -x j∈A ≥0
-------------------------------------
y 1 +y 2 +…+y k∈Bi -y i∈B ≥0
y i∈B -y k∈Bi ≥0
-------------------------------------
-------------------------------------
1-x i∈A -x j∈A,j≠i ≥0
-------------------------------------
1-m i∈B -f i∈B ≥0
wherein N is A Indicating the number of segments within the failure area A, B indicating thatNode set inside barrier region A, bi represents node set downstream of node i, x i 、f i 、m i Respectively representing node states, node missing report and node false report, wherein the variables are decision variables, y i 、As intermediate variable, z i And the node state data actually received by the power distribution operation center.
In this embodiment, the fault indicator status data for the three internal nodes FI11-FI18 of the fault zone are:
Z＝[SL11～SL18]＝[1 1 1 0 0 1 1 1]
leading the fault location model into a power distribution network fault location model, wherein the obtained section location model is as follows:
s.t.y i∈[FI1,...,FI8] -x j∈[SL1,...SL8] ≥0
-------------------------------------
y 1 +y 2 +…+y k∈Bi -y i∈[FI1,...,FI8] ≥0
y i∈[FI1,...,FI8] -y k∈Bi ≥0
-------------------------------------
-------------------------------------
1-x ij∈[SL1,...SL8] -x j∈[SL1,...SL8],j≠i ≥0
-------------------------------------
1-m i∈[FI1,...,FI8] -f i∈[FI1,...,FI8] and (3) solving the section positioning model by CPLEX (complex programmable logic ex) more than or equal to 0, wherein the solving result is as follows:
X＝[x 1 ～x 8 ]＝[00100000]
F＝[f1～f8]＝[00000000]
M＝[m1～m8]＝[00000000]
the section LS13 (x) 3 ) A failure occurs.
Step S5: and in the fault section, the fault positioning model of the power distribution network positions a fault element according to the action data of the fuse and the outage data of the intelligent ammeter, and specifically comprises the following steps:
1) Establishing a fuse and a smart meterA fault element association matrix E; the element coding principle is as follows: the faulty element being downstream of the fuse, E i =1, otherwise E i =0; the faulty element is upstream of the smart meter, E i =1, otherwise E i ＝0；
2) Determining an action matrix T according to the collected fuse action data and the power-off data of the intelligent ammeter; the element coding principle is as follows: fuse T i Action T i =1, otherwise T i =0; smart electric meter SM i Power-off, T i =1, otherwise T i ＝0；
3) Multiplying the correlation matrix E by the action matrix T to obtain a fault element matrix S.
In this embodiment, as shown in fig. 3, the power supply side structure on the section LS13, and the association matrix of the fuse and the smart meter with the fault element inside the section LS13 is:
importing a fuse and an intelligent ammeter action matrix T of a power distribution operation center into a fault positioning model, and multiplying a matrix E by the matrix T to obtain a fault element matrix S:
from the above matrix, it can be judged that the element 4 has failed.
Claims (1)
1. The accurate positioning method for the faults of the power distribution network by utilizing the multiple types of measurement data is characterized by comprising the following steps of:
step S1: and establishing a power distribution network fault positioning model integrating multiple types of data in an off-line mode, wherein the power distribution network fault positioning model comprises three parts: fault region positioning, fault section positioning and fault element positioning;
step S2: after the fault occurs, collecting action data of a power distribution network breaker and a fuse, state data of a fault indicator and outage data of an intelligent ammeter on line, and uploading the information to a power distribution operation center;
step S3: the power distribution network fault positioning model reads the action data of the circuit breaker from a power distribution network operation center and positions a fault area;
the step of locating the fault area according to the breaker action data comprises:
1) Establishing a breaker and region association matrix C, wherein the element coding principle is as follows: section is within the protection range of the breaker, C i =1, otherwise C i ＝0；
2) Determining an action matrix R according to the collected breaker action data, wherein the element coding principle is as follows: circuit breaker R i Action, R i =1, otherwise R i ＝0；
3) Multiplying the incidence matrix C by the action matrix R to obtain a fault area matrix A;
step S4: in the fault area, the power distribution network fault positioning model positions a fault section according to the state data of the fault indicator in the power distribution network fault positioning model;
the method of locating the faulty section based on the fault indicator status data within it is as follows: the fault indicator state data in the fault area is imported into the following section positioning model, CPLEX is utilized to solve the section positioning model, and the solved result comprises a fault section matrix, a node missing report matrix and a node false report matrix;
wherein N is A Representing the number of segments within the failure area a, B representing the set of nodes within the failure area a, bi representing the set of nodes downstream of node i, x i 、f i 、m i Respectively representing node states, node missing report and node false report, wherein the variables are decision variables, y i 、As intermediate variable, z i Node shape actually received by power distribution operation centerStatus data;
step S5: in the fault section, the power distribution network fault positioning model positions a fault element according to the fuse action data and the power-off data of the intelligent ammeter;
the step of determining the fault element by using the fuse action data, the power failure data of the intelligent ammeter and the power distribution network fault location model comprises the following steps:
1) Establishing a fuse and intelligent ammeter and fault element association matrix E; the element coding principle is as follows: the faulty element being downstream of the fuse, E i =1, otherwise E i =0; the faulty element is upstream of the smart meter, E i =1, otherwise E i ＝0；
2) Determining an action matrix T according to the collected fuse action data and the power-off data of the intelligent ammeter; the element coding principle is as follows: fuse T i Action T i =1, otherwise T i =0; smart electric meter SM i Power-off, T i =1, otherwise T i ＝0；
3) Multiplying the correlation matrix E by the action matrix T to obtain a fault element matrix S.
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