CN112834867B - Optimized deployment method of wide-area synchronous intelligent sensor - Google Patents

Optimized deployment method of wide-area synchronous intelligent sensor Download PDF

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CN112834867B
CN112834867B CN202110010627.5A CN202110010627A CN112834867B CN 112834867 B CN112834867 B CN 112834867B CN 202110010627 A CN202110010627 A CN 202110010627A CN 112834867 B CN112834867 B CN 112834867B
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CN112834867A (en
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张亮
胡昇
水恒华
陈杰
胡雪峰
李�荣
孙健
傅岳林
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Nanjing Institute of Technology
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    • 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
    • G01R31/081Locating 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

Abstract

The invention discloses an optimized deployment method of a wide-area synchronous intelligent sensor. The optimization deployment method provided by the invention comprises three steps, firstly, GSS configuration is carried out according to whether the line contains sensitive load; secondly, further classifying the non-sensitive load lines according to whether the lines contain intersection points of incoming and outgoing lines to form a sparse matrix of the lines of the intersection points of the incoming and outgoing lines, and completing GSS configuration of the lines of the intersection points of the incoming and outgoing lines by adopting a sparse MRA method; and finally, GSS configuration is carried out on the rest lines according to the minimum principle of the observation blind spots. And forming a GSS deployment strategy for the complex power distribution network, and realizing the optimal quantity of GSS deployment of the complex power distribution network on the basis of considering deployment necessity and scientificity.

Description

Optimized deployment method of wide-area synchronous intelligent sensor
Technical Field
The invention relates to the technical field of fault detection of a complex power distribution network, in particular to an optimized deployment strategy of a wide-area synchronous intelligent sensor for online monitoring of the complex power distribution network.
Background
The rapid development of economy and the rapid progress of science and technology make the structure of a modern power distribution network very complex, the diversity of power sources and loads accessed to the power distribution network causes frequent faults of the power distribution network, and the faults of the power distribution network can influence the loads, particularly sensitive loads, so that the economic growth is influenced. Therefore, the method is particularly important for solving the power distribution network faults, the monitoring of the power distribution network faults is a key step, and the main problem is how to use the minimum monitoring devices to complete the full-line observation of the power distribution network. A wide area synchronous intelligent sensor (GSS) is a miniature measurement terminal for effectively monitoring the state of a power distribution network, and can be used for monitoring power quality events, such as sag, harmonic disturbance, and the like, and also can be used for monitoring faults. The existing optimal configuration methods of the monitoring devices comprise an MRA method and an FL method, wherein the MRA method takes the minimum number of all-area monitoring devices as an objective function and combines algorithms such as an all-network sag observable area matrix and 0-1 planning and the like to perform configuration. The FL method (fault location) utilizes a chord cutting method and a least square method to process the sag amplitude value to estimate the fault position, and then combines a fault location matrix and a 0-1 planning method to determine the configuration scheme of the monitoring device. The MRA method uses a sampling value of a line, has discreteness, does not fully utilize all information of the line, has the problem of more false fault points in the result of the FL method, needs to arrange a large number of terminals, and cannot achieve economy.
Disclosure of Invention
The invention aims to disclose an optimized deployment strategy of a wide-area synchronous intelligent sensor for online monitoring of a complex power distribution network, which adopts a line classification method, adopts different configuration strategies aiming at the specific conditions of different lines, and solves the minimum GSS configuration at a sensitive load position by adopting a sparse MRA method at an intersection point, and solves the minimum GSS configuration at a non-intersection point by adopting a maximum line monitoring method.
An optimized deployment method of a wide-area synchronous intelligent sensor comprises the following steps:
s1: determining the node number m of the complex distribution network lines, and classifying the complex distribution network lines at the same time: according to the load types, dividing the power distribution network into a sensitive load circuit and a common load circuit; according to the node type, further dividing the common load line into a line with an intersection point of an incoming line and an outgoing line and a line without the intersection point of the incoming line and the outgoing line;
s2: if the distribution network line fault monitoring area matrix I with any fault is detected, GSS is installed, and the distribution network line fault monitoring area matrix I with any fault is used s Is set to 0; and performs step S5; if the normal load circuit is detected, executing step S3;
s3: if the circuit containing the intersection point of the incoming and outgoing lines is detected, the section is connectedDistribution network line fault monitorable area matrix I with point storage under any fault s (ii) a And performs step S5;
s4: if no line crossing point line is detected, the line node matrix is stored in the line node matrix without the line crossing point line Ds (ii) a Simultaneously, a distribution network line fault monitorable area matrix I under any fault s Is set to 0; and performs step S5;
s5: distribution network line fault monitorable area matrix I under any fault s Calculating minimum GSS configuration of the intersection line by adopting a sparse MRA method;
s6: for line node matrix D without intersection points of incoming and outgoing lines s And calculating the minimum GSS configuration of the non-intersection line by adopting a line observation blind spot minimum method until the end.
The GSS optimization deployment method provided by the invention comprises three steps, firstly, GSS configuration is carried out according to whether a sensitive load line is contained; secondly, further classifying the non-sensitive load lines according to whether the lines contain intersection points of incoming and outgoing lines to form a sparse matrix of the lines of the intersection points of the incoming and outgoing lines, and completing GSS configuration of the lines of the intersection points of the incoming and outgoing lines by adopting a sparse MRA method; and finally, GSS configuration is carried out on the rest lines according to the minimum principle of line observation blind spots. And forming a GSS deployment strategy for the complex power distribution network, and realizing the optimal quantity of GSS deployment of the complex power distribution network on the basis of considering deployment necessity and scientificity.
Compared with the prior art, the invention has the following beneficial effects: the method adopts a load classification method, adopts different configuration strategies for different load conditions, configures equivalent GSS at sensitive load, solves the minimum GSS configuration by adopting a sparse MRA method on a line containing an intersection point of an incoming line and an outgoing line, and solves the minimum GSS configuration by adopting a line observation blind spot minimum method on a line without the intersection point of the incoming line and the outgoing line, thereby considering the economy and fully utilizing line information.
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In order to more clearly describe the practice of the invention, reference will now be made to the appended drawings, which are required to describe embodiments of the invention.
Fig. 1 is a diagram of a typical complex distribution network model.
FIG. 2 is a schematic flow chart of the present invention.
Fig. 3 is a schematic diagram of a circuit with an intersection point of an incoming line and an outgoing line in a complex power distribution network.
Fig. 4 is a schematic circuit diagram of a complex power distribution network without an intersection point of incoming and outgoing lines.
Detailed description of the invention
The following will more clearly and completely describe the detailed embodiments of the present invention in conjunction with the attached drawings in the examples of the present invention.
Fig. 1 shows a typical complex distribution network model, which includes 1 incoming line and 2 outgoing lines, the power voltage is 110kV, the voltage is reduced to 10kV by a transformer, and the lines contain 3 sensitive loads.
An optimized deployment method of a wide-area synchronous intelligent sensor comprises the following steps:
s1: determining the node number m of the complex distribution network lines, and classifying the complex distribution network lines at the same time: according to the load types, dividing the power distribution network into a sensitive load circuit and a common load circuit; according to the node type, the common load circuit is further divided into a circuit with an intersection point of an incoming line and an outgoing line and a circuit without the intersection point of the incoming line and the outgoing line.
S2: if the distribution network line fault monitoring area matrix I with any fault is detected, GSS is installed, and the distribution network line fault monitoring area matrix I with any fault is used s Is set to 0; and performs step S5;
supposing that a power distribution network line has m nodes, the number of the nodes containing sensitive loads is n sl The number y of GSSs allocated to the line containing the sensitive load 1 As shown in formula (1):
y 1 =n sl (1)。
if the normal load line is detected, step S3 is executed.
S3: if a line containing an intersection point of an incoming line and an outgoing line is detected, the node is stored in a distribution network line fault monitorable area matrix I under any fault s (ii) a And performs step S5.
S4: if no line crossing point line is detected, the line node matrix is stored in the line node matrix without the line crossing point line Ds (ii) a Simultaneously, the distribution network line under any faultFault monitorable area matrix I s Is set to 0; and performs step S5.
S5: distribution network line fault monitorable area matrix I under any fault s Calculating minimum GSS configuration of the intersection line by adopting a sparse MRA method;
the specific process is as follows: after GSS is configured by a line with sensitive load, the residual number of nodes of the line with the intersection point of the incoming and outgoing lines, which need to be configured with GSS, is m-n sl If the number of intersections of the incoming and outgoing lines is n io Then, for distribution network line fault monitorable area matrix I under any fault s Expressed by formula (2):
Figure GDA0003682856170000051
wherein i pq Represented by formula (3):
Figure GDA0003682856170000052
wherein p is 1,2 … m, q is 1,2 … n ,i pq Monitoring conditions of p nodes when a fault or power quality event occurs for q nodes, i pq For 1 representing p node monitoring fault or power quality event, i pq A value of 0 represents that no fault or power quality event is monitored by the p node;
distribution network line fault monitorable area matrix I under any fault s Is the set of all incoming and outgoing line intersection lines, therefore I s Each row of (a) represents the MRA range of the intersection line, a value of 1 represents a fault or power quality event within the monitoring range, and a value of 0 represents a fault or power quality event outside the monitoring range.
The GSS is required to be configured for the line containing the intersection point of the incoming and outgoing lines according to the target function that the number of the GSSs installed on the line containing the intersection point of the incoming and outgoing lines is minimum:
Figure GDA0003682856170000053
wherein q ═1,2…m;x q Representing a wide-area synchronous intelligent sensor deployment state at a node q;
in order to characterize the GSS configuration result by using sparse MRA, the present invention makes the following definitions according to whether the current node of the whole network deploys the GSS, as shown in formulas (5) and (6):
X=[x 1 ,x 2 …x m ] (5)
wherein X is a wide-area synchronous intelligent sensor deployment matrix in a distribution network line;
Figure GDA0003682856170000054
GSS number y comprising line configuration of intersection points of incoming and outgoing lines 2 Comprises the following steps:
y 2 =f (7)。
s6: for line node matrix D without intersection points of incoming and outgoing lines s Calculating the minimum GSS configuration of the non-intersection line by adopting a line observation blind spot minimum method until the end;
the specific process is as follows: firstly, a node matrix without an intersection line of an incoming line and an outgoing line is formulated by utilizing a union set of node terminal deployment matrixes of lines containing sensitive load lines and lines containing intersections of the incoming line and the outgoing line and a complementary set of a node matrix of the whole network, as shown in formula (8):
Figure GDA0003682856170000061
in the formula D s Is a line node matrix without an intersection point of an incoming line and an outgoing line, C represents a complementary set, E 1×m Is an identity matrix with 1 row and m columns,
Figure GDA0003682856170000062
is a matrix I s First column of (S) sl Deploying a matrix for a terminal containing a sensitive load line;
then, defining the head end node number matrix of the line without the intersection point of the incoming and outgoing lines as D s1 The terminal node number matrix of the line without the intersection point of the incoming and outgoing lines is D s2 Middle end of line without intersection point of incoming and outgoing linesThe node numbering matrix is D smid These three matrices can be represented by equations (9) (10) (11):
D s1 =[s1 1 s1 2 … s1 E ] T (9)
D s2 =[s2 1 s2 2 … s2 F ] T (10)
D smid =[smid 1 smid 2 … smid G ] T (11)
wherein E represents a line head end node number matrix D s1 F represents the line end node number matrix D s2 The total number of elements in the line, G represents a terminal node number matrix D in the line smid Total number of elements in (1);
then, the specific method of the line observation blind spot minimum principle is as follows: from line node matrix D without intersection of incoming and outgoing lines s The first node number begins to take the number according to the rule that the node number is added with one, if the (i +1) th node appears D s (1)+i≠D s (i +1), it means that i +1 nodes do not need or have configured GSS, and complete a cycle; respectively setting the first node number and D in the cycle s (i) Number node putting matrix D s1 And D s2 In (1), respectively calculating the circulant matrix D of this time s1 And D s2 The fault proportion S1, S2 of the middle node number, and the GSS configuration decision function of the segment of line can be expressed as equation (12):
Figure GDA0003682856170000071
if the occurrence of S1+ S2 < 1, then the terminal node numbering matrix D in the line smid Newly adding intermediate nodes of the section of line, determining the GSS configuration of the two sections of lines after division by adopting the method, and repeating continuously until the intermediate nodes completely conform to the formula (12); when D of this cycle s1 To D s2 After the circuit configuration is finished, the following step D s The node (i +2) starts to continue to take the number and configure the GSS according to the rule that the node number is added with one;
finally, the process is carried out in a batch,the configuration quantity of the GSS of the line without the intersection point of the incoming and outgoing lines is y 3 Therefore, the GSS number y of the entire distribution network configuration can be expressed as equation (13):
y=y 1 +y 2 +y 3 (13)
in the formula, y is the GSS number of the whole distribution network configuration, y 1 Number of GSSs allocated to a line containing sensitive loads, y 2 Number of GSSs arranged for lines containing intersections of incoming and outgoing lines, y 3 The number of GSSs configured for the line without the intersection of the incoming and outgoing lines.
Fig. 2 shows a flowchart of a wide-area synchronous intelligent sensor deployment method suitable for online monitoring of a complex power distribution network, which mainly includes three steps:
the method comprises the following steps: GSS configuration with sensitive load lines. The sensitive load line must be provided with GSS to achieve the purpose of monitoring the load state in real time. Suppose that the distribution network has m nodes, and the number of the nodes containing sensitive loads is n sl The number y of GSSs allocated to the line containing the sensitive load 1 As shown in formula (1):
y 1 =n sl (1)
step two: GSS configuration including the line of intersection of the incoming and outgoing lines. After the distribution network is configured with the GSS in the step one, the number of the nodes of the step two needing to be configured with the GSS is m-n sl The number of the intersections of the incoming and outgoing lines is n io For distribution network line fault monitorable area matrix I under any fault s Can be represented by formula (2):
Figure GDA0003682856170000081
wherein i pq May be represented by formula (3):
Figure GDA0003682856170000082
wherein p is 1,2m, q is 1,2 … n, i pq P node monitoring conditions for q point fault pq For 1 p node monitoring failure, i pq A value of 0 indicates that no fault has been detected by the p node。
Matrix I s Is the set of all incoming and outgoing line intersection lines, therefore I s Each row of (a) represents the MRA range of the intersection line, a value of 1 indicates that the fault is within the monitoring range, and a value of 0 indicates that the fault is outside the monitoring range.
The invention adopts load classification pretreatment to ensure that the matrix I s Highly sparse, therefore, the present invention utilizes the triangular search chain storage method of sparse technique to store the matrix I s And the GSS configuration efficiency of the line containing the intersection point of the incoming and outgoing lines in the complex distribution network is greatly improved. Compared with the traditional MRA method, the method can reduce the number of times of calculation by m multiplied by n-n by using the sparse technology io Next, the process is carried out.
The objective function of the second step is that the number of GSSs installed on the line containing the intersection point of the incoming and outgoing lines is minimum:
Figure GDA0003682856170000083
wherein q is 1,2 … m.
In order to characterize the GSS configuration result by using sparse MRA, the present invention makes the following definitions according to whether the current node of the whole network deploys the GSS, as shown in formulas (5) and (6):
X=[x 1 ,x 2 …x m ] (5)
Figure GDA0003682856170000091
GSS number y comprising line configuration of intersection points of incoming and outgoing lines 2 Comprises the following steps:
y 2 =f (7)。
step three: GSS configuration without an incoming/outgoing line intersection line. Firstly, a node matrix of a line without an intersection point of an incoming line and an outgoing line is formulated by utilizing a union set of node terminal deployment matrixes in the first step and the second step and a complementary set of a node matrix of the whole network, as shown in a formula (8):
Figure GDA0003682856170000092
in the formula, D s Is a line node matrix without an intersection point of an incoming line and an outgoing line, C represents a complementary set, E 1×m Is an identity matrix with 1 row and m columns,
Figure GDA0003682856170000093
is a matrix I s First column of (S) sl A matrix is deployed for a terminal with a sensitive load line.
Then, defining a line head end node number matrix D s1 Line end node numbering matrix D s2 Terminal node number matrix D in line smid These three matrices can be represented by equations (9) (10) (11):
D s1 =[s1 1 s1 2 … s1 E ] T (9)
D s2 =[s2 1 s2 2 … s2 F ] T (10)
D smid =[smid 1 smid 2 … smid G ] T (11)
in the formula, E represents a matrix D s1 F denotes a matrix D s2 G represents a matrix D smid Total number of elements in (1).
Then, the specific method of the principle of minimum blind spot of line observation is adopted. Slave matrix D s The first node number begins to take the number according to the rule that the node number is added with one, if the (i +1) th node appears D s (1)+i≠D s (i +1), this means that i +1 nodes do not need or have configured GSS, and a cycle is completed. Respectively setting the first node number and D in the cycle s (i) Number node putting matrix D s1 And D s2 In (1), respectively calculating the circulant matrix D of this time s1 And D s2 The fault proportion S1, S2 of the middle node number, and the GSS configuration decision function of the segment of line can be expressed as equation (12):
Figure GDA0003682856170000101
if S1+ S2 < 1 occurs, then at matrix D smid And newly adding intermediate nodes of the section of line, determining the GSS configuration of the two divided sections of lines by adopting the method, and repeating continuously until the intermediate nodes completely conform to the formula (12). When D of this cycle s1 To D s2 After the circuit configuration is finished, the following step D s And (i +2) node begins to continue to take number and configure GSS according to the rule of adding one to the node number.
Finally, the configuration quantity of the line GSS without the intersection point of the incoming line and the outgoing line is y 3 Therefore, the GSS number y of the entire distribution network configuration can be expressed as equation (13):
y=y 1 +y 2 +y 3 (13)
in the formula, y is the GSS number of the whole distribution network configuration, y 1 Number of GSSs allocated to a line containing sensitive loads, y 2 Number of GSSs arranged for lines containing intersections of incoming and outgoing lines, y 3 The number of GSSs configured for the line without the intersection of the incoming and outgoing lines.
Fig. 3 is a schematic diagram of a complex distribution network including an intersection line of an incoming line and an outgoing line. And the node a is an incoming line node, the node b is an outgoing line node, and the GSS configuration at the intersection point needs to be calculated by adopting a sparse MRA method.
Fig. 4 is a schematic diagram of a circuit without an intersection point of an incoming line and an outgoing line in a complex power distribution network. The nodes c, d, e … x are continuous nodes on the same incoming line or outgoing line, and for the GSS configuration of the line, the calculation needs to be performed by adopting a line observation blind spot minimum method.

Claims (1)

1. An optimized deployment method of a wide-area synchronous intelligent sensor is characterized by comprising the following steps:
s1: determining the node number m of the complex distribution network lines, and classifying the complex distribution network lines at the same time: according to the load types, the distribution network lines are divided into sensitive load lines and common load lines; according to the node type, further dividing the common load line into a line with an intersection point of an incoming line and an outgoing line and a line without the intersection point of the incoming line and the outgoing line;
s2: if the line with sensitive load is detected, GSS is installed to monitor the fault of distribution network line under any faultArea measurement matrix I s Is set to 0; and performs step S5; if the normal load circuit is detected, executing step S3;
the GSS configuration of the line containing the sensitive load is specifically as follows:
supposing that a power distribution network line has m nodes, the number of the nodes containing sensitive loads is n sl The number y of GSSs allocated to the line containing the sensitive load 1 As shown in formula (1):
y 1 =n sl (1);
s3: if a line containing an intersection point of an incoming line and an outgoing line is detected, the node is stored in a distribution network line fault monitorable area matrix I under any fault s (ii) a And performs step S5;
s4: if no intersection line of incoming and outgoing lines is detected, the node matrix D of the intersection line of the incoming and outgoing lines is stored s (ii) a Simultaneously, a distribution network line fault monitorable area matrix I under any fault s Is set to 0; and performs step S5;
s5: distribution network line fault monitorable area matrix I under any fault s Calculating minimum GSS configuration of the intersection line by adopting a sparse MRA method;
after GSS is configured by a line with sensitive load, the residual number of nodes of the line with the intersection point of the incoming and outgoing lines, which need to be configured with GSS, is m-n sl If the number of the intersection points of the incoming and outgoing lines is n io Then, for distribution network line fault monitorable area matrix I under any fault s Expressed by formula (2):
Figure FDA0003682856160000021
wherein i pq Represented by formula (3):
Figure FDA0003682856160000022
wherein p is 1,2 … m, q is 1,2 … n, i pq Monitoring conditions of p nodes when a fault or power quality event occurs for q nodes, i pq For 1 representing p node monitoring fault or power quality event, i pq A value of 0 represents that no fault or power quality event is monitored by the p node;
distribution network line fault monitorable area matrix I under any fault s Is the set of all incoming and outgoing line intersection lines, therefore I s Each row of the fault line represents the MRA range of the intersection point line, the value of 1 represents that the fault or the power quality event is in the monitoring range, and the value of 0 represents that the fault or the power quality event is out of the monitoring range;
the GSS is required to be configured for the line containing the intersection point of the incoming and outgoing lines according to the target function that the number of the GSSs installed on the line containing the intersection point of the incoming and outgoing lines is minimum:
Figure FDA0003682856160000023
wherein q is 1,2 … m; x is the number of q Representing a wide-area synchronous intelligent sensor deployment state at a node q;
in order to characterize the GSS configuration result by using sparse MRA, the following definitions are made according to whether the current node of the whole network deploys the GSS, as shown in formulas (5) and (6):
X=[x 1 ,x 2 …x m ] (5)
wherein X is a wide-area synchronous intelligent sensor deployment matrix in a distribution network line;
Figure FDA0003682856160000024
GSS number y comprising line configuration of intersection points of incoming and outgoing lines 2 Comprises the following steps:
y 2 =f (7);
s6: for line node matrix D without intersection points of incoming and outgoing lines s Calculating the minimum GSS configuration of the non-intersection line by adopting a line observation blind spot minimum method until the end;
the specific process is as follows:
firstly, a node matrix without an intersection line of an incoming line and an outgoing line is formulated by utilizing a union set of node terminal deployment matrixes of lines containing sensitive load lines and lines containing intersections of the incoming line and the outgoing line and a complementary set of a node matrix of the whole network, as shown in formula (8):
Figure FDA0003682856160000031
in the formula, D s Is a line node matrix without an intersection point of an incoming line and an outgoing line, C represents a complementary set, E 1×m Is an identity matrix with 1 row and m columns,
Figure FDA0003682856160000032
is a matrix I s First column of (S) sl Deploying a matrix for a terminal containing a sensitive load line;
then, defining the head end node number matrix of the line without the intersection point of the incoming and outgoing lines as D s1 The terminal node number matrix of the line without the intersection point of the incoming and outgoing lines is D s2 The medium-end node number matrix of the line without the intersection point of the incoming and outgoing lines is D smid These three matrices can be represented by equations (9) (10) (11):
D s1 =[s1 1 s1 2 …s1 E ] T (9)
D s2 =[s2 1 s2 2 …s2 F ] T (10)
D smid =[smid 1 smid 2 …smid G ] T (11)
wherein E represents a line head end node number matrix D s1 F represents the line end node number matrix D s2 G represents a terminal node number matrix D in the line smid Total number of elements in (1);
then, the specific method of the line observation blind spot minimum principle is as follows: from line node matrix D without intersection of incoming and outgoing lines s The first node number begins to take number according to the rule that the node number is added with one, if the (i +1) th node appears D s (1)+i≠D s (i +1), it means that i +1 nodes do not need or have configured GSS, and complete a cycle; respectively in the current cycleFirst node number of and D s (i) Number node putting matrix D s1 And D s2 In (1), respectively calculating the circulant matrix D of this time s1 And D s2 The fault proportion S1, S2 of the middle node number, and the GSS configuration decision function of the segment of line can be expressed as equation (12):
Figure FDA0003682856160000041
if the occurrence of S1+ S2 < 1, then at the line intermediate node numbering matrix D smid Newly adding intermediate nodes of the section of line, determining the GSS configuration of the two sections of lines after division by adopting the method, and repeating continuously until the intermediate nodes completely conform to the formula (12); when D of this cycle s1 To D s2 After the circuit configuration is finished, the following step D s The node (i +2) starts to continue to take the number and configure the GSS according to the rule that the node number is added with one;
finally, the configuration quantity of the line GSS without the intersection point of the incoming line and the outgoing line is y 3 Therefore, the GSS number y of the entire distribution network configuration can be expressed as equation (13):
y=y 1 +y 2 +y 3 (13)
in the formula, y is the GSS number of the whole distribution network configuration, y 1 Number of GSSs allocated to a line containing sensitive loads, y 2 Number of GSSs arranged for lines containing intersections of incoming and outgoing lines, y 3 The number of GSSs configured for the line without the intersection of the incoming and outgoing lines.
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