CN111899127B - Hierarchical fault sweep tree modeling method, model and application method thereof - Google Patents
Hierarchical fault sweep tree modeling method, model and application method thereof Download PDFInfo
- Publication number
- CN111899127B CN111899127B CN202010885297.XA CN202010885297A CN111899127B CN 111899127 B CN111899127 B CN 111899127B CN 202010885297 A CN202010885297 A CN 202010885297A CN 111899127 B CN111899127 B CN 111899127B
- Authority
- CN
- China
- Prior art keywords
- fault
- sweep
- nodes
- tree
- branch
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 54
- 230000004224 protection Effects 0.000 claims abstract description 52
- 238000004458 analytical method Methods 0.000 claims abstract description 27
- 230000009471 action Effects 0.000 claims description 16
- 238000004364 calculation method Methods 0.000 claims description 16
- 238000010586 diagram Methods 0.000 claims description 12
- 230000008859 change Effects 0.000 claims description 8
- 230000002159 abnormal effect Effects 0.000 claims description 7
- 238000012544 monitoring process Methods 0.000 claims description 7
- 238000010183 spectrum analysis Methods 0.000 claims description 7
- 238000010187 selection method Methods 0.000 claims description 6
- 238000003745 diagnosis Methods 0.000 claims description 5
- 238000011156 evaluation Methods 0.000 claims description 5
- 230000000007 visual effect Effects 0.000 claims description 4
- 230000006399 behavior Effects 0.000 abstract description 6
- 230000002093 peripheral effect Effects 0.000 abstract description 4
- 238000005065 mining Methods 0.000 description 3
- 238000007689 inspection Methods 0.000 description 2
- 238000012800 visualization Methods 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 239000012212 insulator Substances 0.000 description 1
- 230000007257 malfunction Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Educational Administration (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a layering-based fault sweep tree modeling method, a layering-based fault sweep tree model and an application method thereof, relates to the field of power grid fault information analysis, and solves the problem that the sweep and sweep degree of protection connected with a fault point cannot be determined when a power grid is in fault. According to the method, N nodes with the distance of 1 from the node K are respectively used as starting points of N fault sweep tree models, the N fault sweep tree models are built, the hierarchy expansion is carried out downwards according to the method step of S1 based on the connection relation of the branch parameter tables corresponding to the N nodes, the method step of S1 is circulated until all branches are found, the N nodes are simultaneously used as second layers of the fault sweep tree models to be displayed, and the layers of the rest nodes and the branches are gradually increased. The invention forms a layered fault sweep network through the sweep connecting lines, thereby better analyzing the influence behaviors of fault points on peripheral protection.
Description
Technical Field
The invention relates to the field of power grid fault information analysis, in particular to a hierarchical fault sweep tree modeling method, a model and an application method thereof.
Background
The analysis and modeling of relay protection fault information of the intelligent power grid are insufficient, the analysis and modeling research of fault data are mostly performed based on protection of fault point actions, local fault information is often considered, the requirements of data mining application cannot be met, the information utilization of non-fault elements is insufficient, the safety margin analysis is insufficient, and the information mining of fault elements is far insufficient. In the field, when fault information of various protection systems is utilized, the fault is rapidly diagnosed by collecting data, the action behaviors of action elements are analyzed, analysis results are provided for a dispatcher to make decisions, but the faults affect the degree, the starting behaviors of the faults are protected by the affected unoperated actions, whether sampling matching is abnormal or not, the backup protection matching conditions and the like cannot be mined and analyzed, and a method for mining and analyzing the data is also lacking.
The current fault tree method is used for wind turbine generator system state monitoring and health evaluation, the electric energy meter fault diagnosis method, the GIS supports insulator fault analysis, the substation inspection robot fault analysis and autonomous special inspection system, the power transformer fault analysis and the like, and is rarely used for relay protection fault analysis during power grid faults.
As described above, the existing relay protection fault information modeling main method has the following main disadvantages:
1) The existing relay protection fault information modeling method mainly adopts waveform analysis tools and the like for analyzing relay protection action time sequences, fault information display and analysis are limited to action protection elements, and big data and visual analysis methods are not easy to apply.
2) The existing information flow modeling of relay protection faults does not model fault information, fault analysis depends on an alarm system and a wave recording system, network diagram modeling cannot be formed, and intelligent algorithms cannot be adopted for analysis.
3) The existing relay protection information flow modeling can not well apply the visualization technology of the network diagram to carry out the visualization analysis and mining of fault information.
Disclosure of Invention
The invention solves the problem that the protection connected with the fault point is possibly affected and affected when the power grid is in fault, establishes the fault affected network related to the fault point, establishes a layering fault affected tree model for evaluating the influence of the protection different from the fault point in distance, and forms the layering fault affected network through the affected connecting lines, thereby better analyzing the influence behavior of the fault point on the peripheral protection.
The content analyzed by the invention is as follows: in order to analyze which protection connected with a fault point is possible to be affected and the extent of the affected protection when the power grid is in fault, a fault affected network associated with the fault point is established, and in order to evaluate the influence of protection different from the fault point in distance, a fault affected tree model is established to better analyze the influence behaviors of the fault point on the peripheral protection. The method comprises the steps of analyzing and evaluating the power grid fault sweep tree according to the power grid fault sweep tree.
The building of the fault sweep tree model takes a fault point as a starting point, directly adjacent nodes are first stages, other nodes connected with the first stages are second stages, and the like. The actual fault only needs to consider that protection can be started, so the affected node takes the protection of the node as a node of the affected node and does not count the fault affected tree if the node does not reach the starting value.
The invention is realized by the following technical scheme:
The modeling method of fault sweep tree based on layering comprises the following steps:
S1, for a fault point K, N nodes with the distance of 1 from the node K are searched and arranged from a node table containing the node K, and meanwhile, the fault point K is used as a first layer of a fault sweep tree model to be displayed;
S2, respectively taking N nodes with a distance of1 from the node K as starting points of N fault sweep tree models, building the N fault sweep tree models, carrying out level expansion downwards according to the method step of S1 based on the connection relation of the branch parameter tables corresponding to the N nodes, circulating the method step of S1 until all branches are found, simultaneously displaying the N nodes as a second layer of the fault sweep tree models, and gradually increasing the layers of the rest nodes and the branches.
Further, when the number of branches connected with the N nodes is the same, selecting N nodes with large connection current values from the N nodes as starting points of N fault sweep tree models based on a node table and a branch parameter table of the N nodes;
Otherwise, when the numbers of the branches connected with the N nodes are different, two nodes of the N nodes, two positions before the number of the branches connected with the N nodes, are selected to serve as starting points of two fault sweep tree models based on the connection relation between the node tables of the N nodes and the branch parameter tables.
Further, the connection selection method of the model branch circuit comprises the following steps:
s2.1, firstly, regarding the starting points of n fault sweep tree models of n nodes as a second layer display, referring to the connection relation of a branch parameter table, selecting a first connection branch with more branches as n nodes in n nodes adjacent to the nodes to be connected preferentially;
s2.2, the number of connecting branches of n adjacent nodes is the same, adjacent nodes with large connecting current values are used as second connecting branches for preferential connection, and adjacent nodes with small connecting current values are used as sweep connecting lines to be connected into a fault sweep tree model;
And S2.3, finally, the priority connection branch selection method of the S2.1 and the S2.2 is circulated to perform branch connection selection and branch connection until all the branches are found out.
Further, the method also comprises the step of selecting the tree support node of the layer to be connected with the node of the upper layer of the layer simultaneously so as to be used as a main connection branch with high connection power.
Further, in 2.2, when two sub-nodes in the layer respectively belong to different fault root nodes, that is, the fault sweep tree model starting points corresponding to the two sub-nodes in the layer respectively are different, the two sub-nodes in the layer are connected, and a connecting line between the two sub-nodes is a fault sweep tie line of the fault sweep tree.
Further, the method further comprises the steps of importing the starting branch information, the fault node voltage and the branch current information recorded by the fault recorder into the fault wave and tree model, performing power calculation, calculating the average steady state quantity during fault, judging the branch direction, and expanding the hierarchy until all branches are found.
Further, the method also comprises the following steps:
Step A, power calculation is carried out according to the starting branch circuit recorded by the fault recorder and the fault node voltage and the branch circuit current: calculating by considering the average steady-state quantity in the fault;
for negative sequence power and zero sequence power:
The calculated data comprises a node voltage U2, a branch current I2 and a phase difference (phi 2-phi 1), wherein the phase difference (phi 2-phi 1) is the phase difference between the phase phi 2 of the node voltage and a reference phase phi 1, and the calculation formula of any negative sequence power or zero sequence power P2 is as follows: p2=u2×i2×sin (Φ2- Φ1), for the negative sequence power point and the zero sequence power point, the reference phase Φ1 based on is the same;
For fault delta power:
the calculation data comprise fault phase voltage U3, branch fault current I3 and phase difference phi 3-phi 1-180 degrees, the voltage amplitude of the abrupt change is (1-U3), and the calculation formula is the abrupt change power P3: p3= (1-U3) ×i3×sin (Φ3- Φ1-180);
and B, judging the direction of the branch: c, judging according to the sign of the power calculated in the step A and the branch node sequence of the nodes, and judging the direction among the branches of the model;
For the non-fault branch, the power of the non-fault branch flows in from one side and flows out from the other side, the original numbers of the branch nodes are i and J, the power of two sides of the branch is calculated respectively, and if the calculated power of the i side is positive and the power of the J side branch is negative, the number direction of the branch nodes is kept unchanged and is i-J; if the i-side calculated power is negative and the J-side calculated power is negative, modifying the node number to be J-i;
For the fault branch, the calculated power of the ik side and the jk side is negative, and two branches ik-jk and jk-ik are established;
step C, obtaining the topological connection relation between each substation node and each branch and the connection topological relation between the node and each branch according to the network information of the fault recorder or the monitoring system;
And D, converting the model into a model for analysis according to the network topological relation obtained in the step C and the branch power direction information obtained in the step B, and the fault sweep tree supplementary information of the 1+m layer, wherein m is 1,2, 3 and … … until all branches of the model are reached.
Based on the layering fault sweep tree model and the model built based on the layering fault sweep tree modeling method, the model is used for carrying out network topology analysis and network spectrum analysis by combining fault recorder or monitoring network information.
The application method based on the layering fault sweep tree model is based on the model built based on the layering fault sweep tree modeling method, a layering fault sweep tree model is built, a visual fault sweep degree and range diagram is intuitively obtained, and meanwhile the fault sweep tree model is also used for positioning a fault source;
The fault sweep tree model is further used for analyzing, excavating and judging whether the starting of the non-action element is normal or not by combining the network topology analysis method and the network spectrum analysis method, the measuring element is abnormal or not in cooperation, the potential safety risk level of the sweep tie line is further evaluated, and the fault sweep tree model is further used for diagnosis suggestion and situation evaluation of faults; the method is also used for analyzing data in a clustering mode according to the size, the degree of the sweep, the number of protection influences, the distribution characteristics of power points of the sweep tree of the fault and the distribution characteristics of sweep connecting lines, and also analyzing the association relation and the correlation degree between parameters of the sweep tree diagram of the fault; the sweep degree is the number of actions of the starting element.
Further, the node quantity is the starting voltage quantity and the node average current starting quantity, and the branch quantity is the branch average power;
Further, constructing a fault sweep tree model from the top according to the fault points from near to far, constructing fault sweep connecting lines, and carrying out hierarchical layout by adopting a force guiding algorithm;
The invention has the following advantages and beneficial effects:
The invention can not only visually visualize the extent and range of fault sweep and locate fault sources by establishing the hierarchical fault sweep tree, but also analyze and mine whether the starting of the non-action element is normal or not by combining the network topology analysis method and the network spectrum analysis method through the network model, and measure whether the element is abnormal or not in cooperation, the potential safety risk of sweep connecting lines and the like, thereby further giving diagnosis suggestions and situation evaluation of faults.
Drawings
The accompanying drawings, which are included to provide a further understanding of embodiments of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the drawings:
Fig. 1 is a network diagram of a grid fault of the present invention.
FIG. 2 is a fault sweep tree diagram of the present invention.
FIG. 3 is a hierarchical diagram of a fault sweep tree of the present invention.
Fig. 4 is a tree diagram of the fault sweep of branch 1 of the present invention.
Detailed Description
Before any embodiments of the invention are explained in detail, it is to be understood that the invention is not limited in its application to the details of construction set forth in the following description or illustrated in the drawings. The invention is capable of other embodiments and of being practiced or of being carried out in various ways. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive improvements, are intended to fall within the scope of the invention.
The content analyzed by the invention is as follows: in order to analyze which protection connected with a fault point is possible to be affected and the extent of the affected protection when the power grid is in fault, a fault affected network associated with the fault point is established, and in order to evaluate the influence of protection different from the fault point in distance, a fault affected tree model is established to better analyze the influence behaviors of the fault point on the peripheral protection. The method comprises the steps of analyzing and evaluating the power grid fault sweep tree according to the power grid fault sweep tree.
The building of the fault sweep tree model takes a fault point as a starting point, directly adjacent nodes are first stages, other nodes connected with the first stages are second stages, and the like. The actual fault only needs to consider that protection can be started, so the affected node takes the protection of the node as a node of the affected node and does not count the fault affected tree if the node does not reach the starting value.
The invention is realized by the following technical scheme:
The modeling method of fault sweep tree based on layering comprises the following steps:
S1, for a fault point K, N nodes with the distance of 1 from the node K are searched and arranged from a node table containing the node K, and meanwhile, the fault point K is used as a first layer of a fault sweep tree model to be displayed;
S2, respectively taking N nodes with a distance of1 from the node K as starting points of N fault sweep tree models, building the N fault sweep tree models, carrying out level expansion downwards according to the method step of S1 based on the connection relation of the branch parameter tables corresponding to the N nodes, circulating the method step of S1 until all branches are found, simultaneously displaying the N nodes as a second layer of the fault sweep tree models, and gradually increasing the layers of the rest nodes and the branches.
Further, when the number of branches connected with the N nodes is the same, selecting N nodes with large connection current values from the N nodes as starting points of N fault sweep tree models based on a node table and a branch parameter table of the N nodes;
Otherwise, when the numbers of the branches connected with the N nodes are different, two nodes of the N nodes, two positions before the number of the branches connected with the N nodes, are selected to serve as starting points of two fault sweep tree models based on the connection relation between the node tables of the N nodes and the branch parameter tables.
Further, the connection selection method of the model branch circuit comprises the following steps:
s2.1, firstly, regarding the starting points of n fault sweep tree models of n nodes as a second layer display, referring to the connection relation of a branch parameter table, selecting a first connection branch with more branches as n nodes in n nodes adjacent to the nodes to be connected preferentially;
s2.2, the number of connecting branches of n adjacent nodes is the same, adjacent nodes with large connecting current values are used as second connecting branches for preferential connection, and adjacent nodes with small connecting current values are used as sweep connecting lines to be connected into a fault sweep tree model;
And S2.3, finally, the priority connection branch selection method of the S2.1 and the S2.2 is circulated to perform branch connection selection and branch connection until all the branches are found out.
Further, the method also comprises the step of selecting the tree support node of the layer to be connected with the node of the upper layer of the layer simultaneously so as to be used as a main connection branch with high connection power.
Further, in 2.2, when two sub-nodes in the layer respectively belong to different fault root nodes, that is, the fault sweep tree model starting points corresponding to the two sub-nodes in the layer respectively are different, the two sub-nodes in the layer are connected, and a connecting line between the two sub-nodes is a fault sweep tie line of the fault sweep tree.
Further, the method further comprises the steps of importing the starting branch information, the fault node voltage and the branch current information recorded by the fault recorder into the fault wave and tree model, performing power calculation, calculating the average steady state quantity during fault, judging the branch direction, and expanding the hierarchy until all branches are found.
Further, the method also comprises the following steps:
Step A, power calculation is carried out according to the starting branch circuit recorded by the fault recorder and the fault node voltage and the branch circuit current: calculating by considering the average steady-state quantity in the fault;
for negative sequence power and zero sequence power:
The calculated data comprises a node voltage U2, a branch current I2 and a phase difference (phi 2-phi 1), wherein the phase difference (phi 2-phi 1) is the phase difference between the phase phi 2 of the node voltage and a reference phase phi 1, and the calculation formula of any negative sequence power or zero sequence power P2 is as follows: p2=u2×i2×sin (Φ2- Φ1), for the negative sequence power point and the zero sequence power point, the reference phase Φ1 based on is the same;
For fault delta power:
the calculation data comprise fault phase voltage U3, branch fault current I3 and phase difference phi 3-phi 1-180 degrees, the voltage amplitude of the abrupt change is (1-U3), and the calculation formula is the abrupt change power P3: p3= (1-U3) ×i3×sin (Φ3- Φ1-180);
and B, judging the direction of the branch: c, judging according to the sign of the power calculated in the step A and the branch node sequence of the nodes, and judging the direction among the branches of the model;
For the non-fault branch, the power of the non-fault branch flows in from one side and flows out from the other side, the original numbers of the branch nodes are i and J, the power of two sides of the branch is calculated respectively, and if the calculated power of the i side is positive and the power of the J side branch is negative, the number direction of the branch nodes is kept unchanged and is i-J; if the i-side calculated power is negative and the J-side calculated power is negative, modifying the node number to be J-i;
For the fault branch, the calculated power of the ik side and the jk side is negative, and two branches ik-jk and jk-ik are established;
step C, obtaining the topological connection relation between each substation node and each branch and the connection topological relation between the node and each branch according to the network information of the fault recorder or the monitoring system;
And D, converting the model into a model for analysis according to the network topological relation obtained in the step C and the branch power direction information obtained in the step B, and the fault sweep tree supplementary information of the 1+m layer, wherein m is 1,2, 3 and … … until all branches of the model are reached.
Based on the layering fault sweep tree model and the model built based on the layering fault sweep tree modeling method, the model is used for carrying out network topology analysis and network spectrum analysis by combining fault recorder or monitoring network information.
The application method based on the layering fault sweep tree model is based on the model built based on the layering fault sweep tree modeling method, a layering fault sweep tree model is built, a visual fault sweep degree and range diagram is intuitively obtained, and meanwhile the fault sweep tree model is also used for positioning a fault source;
The fault sweep tree model is further used for analyzing, excavating and judging whether the starting of the non-action element is normal or not by combining the network topology analysis method and the network spectrum analysis method, the measuring element is abnormal or not in cooperation, the potential safety risk level of the sweep tie line is further evaluated, and the fault sweep tree model is further used for diagnosis suggestion and situation evaluation of faults; the method is also used for analyzing data in a clustering mode according to the size, the degree of the sweep, the number of protection influences, the distribution characteristics of power points of the sweep tree of the fault and the distribution characteristics of sweep connecting lines, and also analyzing the association relation and the correlation degree between parameters of the sweep tree diagram of the fault; the sweep degree is the number of actions of the starting element.
Further, the node quantity is the starting voltage quantity and the node average current starting quantity, and the branch quantity is the branch average power;
Further, constructing a fault sweep tree model from the top according to the fault points from near to far, constructing fault sweep connecting lines, and carrying out hierarchical layout by adopting a force guiding algorithm;
example 1, as shown in fig. 1-3:
The algorithm comprises the following basic steps:
1. for the K-point fault, the two largest values 1,2 of the node are found from the node table as the starting point.
2. And according to the connection of the branch parameter table, searching nodes connected with the 1 and the 2 from the 1 and the 2 respectively, and displaying the nodes as a second layer. If the node is connected with 1,2 at the same time, the node has more priority with 1,2 connection branches. If the number of the connection branches is the same as that of the connection branches 1 and 2, the connection branches with large connection current values are used as sweep connection lines with small connection current.
3. Finding all branches according to the rule.
As shown in fig. 1, the network has 11 nodes, 12 branches, and associated protection 19. Where branches 10 and 11 are equivalent system power supplies.
The fault sweep network and fault sweep tree corresponding to the K points are shown in the above figure. In order to better analyze the influence of a fault point and protect the change condition of network information after tripping, a fault point is added to a fault sweep network, and two branches are added to the fault point.
1) The network has two fault sweep trees, if the T node branch is adjacent to the fault point, three fault sweep trees are provided, the starting point of each fault sweep tree is the fault point, and the first stage is a node directly connected with the fault point.
2) The maximum influence depth of each sweep tree is the depth of the tree, the sweep tree is swept through the network once by faults, 4 layers are swept when the fault occurs at the point, and nodes (substations) swept at the first layer are 1 and 2 nodes; the second layer has 5 nodes, 9 nodes are equivalent power supply nodes of the system, 8 nodes are terminal station nodes (the nodes cannot be started); the third layer has 3 nodes 6,7 and 8, wherein 6 nodes are terminal nodes, and the nodes cannot be started; the last layer of nodes are 11 nodes and power supply points.
3) The two trees are connected through the connecting lines between the 3,4 and 4,5, and when one side of the connecting line is protected and tripped, the fault quantity felt by the related protection changes, and the protection misoperation can be caused. The influence degree of the wave-connected lines of different networks is different, and the wave-connected lines have the greatest influence (double-circuit lines) when in the first layer; the smaller the loop impedance of the wave-link connection is, the larger the influence is; if the wire belongs to different voltage classes, the cross-region wire may cause malfunction when the different voltage classes fail.
4) According to the fault wave-and-tree, the fault information of the node needs to be analyzed in different operation modes, the change condition of the circuit breaker after the circuit breaker is tripped, whether the circuit breaker is abnormal or not and the like, and whether abnormal data exist or not can be analyzed by setting a calculation network and comparing and analyzing actual fault wave-recording data and comparing fault quantity sensed by double protection.
Example 2:
To represent the distance relation between each protection and the fault point, a fault sweep tree of each protection as shown in fig. 4 is established.
1) The sweep tree is similar to the fault sweep tree, and two sweep trees exist, so that the relation of faults to protection is reflected. The first level is protection 1 and 2, the directly related protection 19,3,8,12,17 is the second level, and the protection is the protection in the opposite direction of the protection action, and the protection belongs to a transformer substation, so the protection belongs to a first layer of sweep layer. A similar sweep layer 2 includes a sweep stage 3 that senses the forward direction and a sweep stage 4 that senses the reverse direction, the sweep layer 3 has two protections, 14 is terminal protections, no action, 16 is plant protections, and is swept.
2) The fault sweep tree of the protection can be used for analyzing the action conditions of the related protection, including starting conditions, measuring element sensitivity matching conditions, differential flow and safety margin conditions, double protection comparison condition analysis and the like.
When short circuit fault occurs, fault abrupt power, negative sequence power and zero sequence power flow from fault point to other parts, so that a directed graph can be established according to power flow direction. The direction protection itself is also adaptive to the power direction.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (7)
1. The modeling method of the fault sweep tree based on layering is characterized by comprising the following steps of:
S1, for a fault point K, N nodes with the distance of 1 from the node K are searched and arranged from a node table containing the node K, and meanwhile, the fault point K is used as a first layer of a fault sweep tree model to be displayed;
S2, respectively taking N nodes with a distance of 1 from a node K as starting points of N fault sweep tree models, building the N fault sweep tree models, carrying out level expansion downwards according to the method step of S1 based on the connection relation of the branch parameter tables corresponding to the N nodes, circulating the method step of S1 until all branches are found, simultaneously, displaying the N nodes as a second layer of the fault sweep tree models, and gradually increasing the layer numbers of the rest nodes and the branches;
When the number of branches connected with N nodes is the same, selecting N nodes with large connection current values from the N nodes as starting points of N fault sweep tree models based on a node table and a branch parameter table of the N nodes;
Otherwise, when the numbers of the branches connected with the N nodes are different, two nodes of the N nodes, two positions before the number of the branches connected with the N nodes, are selected to serve as starting points of two fault sweep tree models based on the connection relation between the node tables of the N nodes and the branch parameter tables.
2. The hierarchical fault sweep tree modeling method of claim 1, further comprising the connection selection method steps of model legs as follows:
S2.1, firstly, regarding the starting points of n fault sweep tree models of n nodes as a second layer display, referring to the connection relation of a branch parameter table, selecting a first connection branch with more branches as n nodes in n nodes adjacent to the nodes to be connected preferentially;
S2.2, the number of connecting branches of n adjacent nodes is the same, adjacent nodes with large connecting current values are used as second connecting branches for preferential connection, and adjacent nodes with small connecting current values are used as sweep connecting lines to be connected into a fault sweep tree model;
And S2.3, finally, the priority connection branch selection method of the S2.1 and the S2.2 is circulated to perform branch connection selection and branch connection until all the branches are found out.
3. The hierarchy-based fault sweep tree modeling method of claim 2, further comprising selecting as a primary connection leg when a tree support node of a layer is simultaneously connected to a node of an upper layer of the layer that is high in connection power.
4. The hierarchical fault sweep tree modeling method according to claim 2, wherein in S2.2, when two sub-nodes in a layer respectively belong to different fault root nodes, that is, two sub-nodes in the layer respectively correspond to different fault sweep tree model starting points, the two sub-nodes in the layer are connected, and a connecting line between the two sub-nodes is a fault sweep tie line of a fault sweep tree.
5. The hierarchical fault sweep tree modeling method according to claim 4, further comprising the steps of introducing the starting branch information, fault node voltage and branch current information recorded by the fault recorder into the fault sweep tree model, performing power calculation, calculating an average steady state quantity during fault, judging the branch direction, and expanding the hierarchy until all branches are found.
6. The hierarchical fault sweep tree modeling method of claim 4, further comprising the steps of modeling and computing the method as follows:
Step A, power calculation is carried out according to the starting branch circuit recorded by the fault recorder and the fault node voltage and the branch circuit current: calculating by considering the average steady-state quantity in the fault;
for negative sequence power and zero sequence power:
The calculated data comprises a node voltage U2, a branch current I2 and a phase difference (phi 2-phi 1), wherein the phase difference (phi 2-phi 1) is the phase difference between the phase phi 2 of the node voltage and a reference phase phi 1, and the calculation formula of any negative sequence power or zero sequence power P2 is as follows: p2=u2×i2×sin (Φ2- Φ1), for the negative sequence power point and the zero sequence power point, the reference phase Φ1 based on is the same;
For fault delta power:
the calculation data comprise fault phase voltage U3, branch fault current I3 and phase difference phi 3-phi 1-180 degrees, the voltage amplitude of the abrupt change is (1-U3), and the calculation formula is the abrupt change power P3: p3= (1-U3) ×i3×sin (Φ3- Φ1-180);
and B, judging the direction of the branch: c, judging according to the sign of the power calculated in the step A and the branch node sequence of the nodes, and judging the direction among the branches of the model;
For the non-fault branch, the power of the non-fault branch flows in from one side and flows out from the other side, the original numbers of the branch nodes are i and j, the power of two sides of the branch is calculated respectively, and if the calculated power of the i side is positive and the power of the j side is negative, the number direction of the branch nodes is kept unchanged and is i-j; if the i-side calculated power is negative and the j-side calculated power is negative, modifying the node number to be j-i;
For the fault branch, the calculated power of the ik side and the jk side is negative, and two branches ik-jk and jk-ik are established;
step C, obtaining the topological connection relation between each substation node and each branch and the connection topological relation between the node and each branch according to the network information of the fault recorder or the monitoring system;
And D, converting the model into a model for analysis according to the network topological relation obtained in the step C and the branch power direction information obtained in the step B, and the fault sweep tree supplementary information of the 1+m layer, wherein m is 1,2, 3 and … … until all branches of the model are reached.
7. An application method based on a hierarchical fault sweep tree model is characterized in that the model built based on the hierarchical fault sweep tree modeling method according to any one of claims 1-6;
Visual fault sweep degree and range diagrams are intuitively obtained by establishing a hierarchical fault sweep tree model, wherein the fault sweep tree model is used for carrying out network topology analysis and network spectrum analysis by combining fault oscillographs or monitoring network information, and meanwhile, the fault sweep tree model is also used for positioning fault sources;
The fault sweep tree model is further used for analyzing, excavating and judging whether the starting of the non-action element is normal or not by combining the network topology analysis method and the network spectrum analysis method, the measuring element is abnormal or not in cooperation, the potential safety risk level of the sweep tie line is further evaluated, and the fault sweep tree model is further used for diagnosis suggestion and situation evaluation of faults;
The method is also used for analyzing data in a clustering mode according to the size, the degree of the sweep, the number of protection influences, the distribution characteristics of power points of the sweep tree of the fault and the distribution characteristics of sweep connecting lines, and also analyzing the association relation and the correlation degree between parameters of the sweep tree diagram of the fault;
The sweep degree is the number of actions of the starting element.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010885297.XA CN111899127B (en) | 2020-08-28 | 2020-08-28 | Hierarchical fault sweep tree modeling method, model and application method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010885297.XA CN111899127B (en) | 2020-08-28 | 2020-08-28 | Hierarchical fault sweep tree modeling method, model and application method thereof |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111899127A CN111899127A (en) | 2020-11-06 |
| CN111899127B true CN111899127B (en) | 2024-04-23 |
Family
ID=73224890
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010885297.XA Active CN111899127B (en) | 2020-08-28 | 2020-08-28 | Hierarchical fault sweep tree modeling method, model and application method thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111899127B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112488337B (en) * | 2020-12-11 | 2023-07-25 | 广东电力通信科技有限公司 | Intelligent auxiliary overhaul flow analysis method and system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH09146627A (en) * | 1995-11-24 | 1997-06-06 | Kawasaki Steel Corp | Device for hiearchizing fault diagnostic knowledge tree |
| CN104123407A (en) * | 2014-06-19 | 2014-10-29 | 电子科技大学 | Automatic testability model building method based on circuit simulation |
| CN105067959A (en) * | 2015-09-15 | 2015-11-18 | 长沙威胜信息技术有限公司 | Fault positioning method under ring network power supply condition |
| CN106021596A (en) * | 2016-06-07 | 2016-10-12 | 国网江苏省电力公司电力科学研究院 | Analyzing method of grid fault current shock topological graph |
| CN107516896A (en) * | 2017-08-28 | 2017-12-26 | 国网江苏省电力公司技能培训中心 | A kind of load restoration scheme generation method based on decision tree pruning algorithms |
| CN110348690A (en) * | 2019-06-12 | 2019-10-18 | 国网江苏省电力有限公司金湖县供电分公司 | Result queries menu power grid accident aid decision-making system and method based on tree search |
-
2020
- 2020-08-28 CN CN202010885297.XA patent/CN111899127B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH09146627A (en) * | 1995-11-24 | 1997-06-06 | Kawasaki Steel Corp | Device for hiearchizing fault diagnostic knowledge tree |
| CN104123407A (en) * | 2014-06-19 | 2014-10-29 | 电子科技大学 | Automatic testability model building method based on circuit simulation |
| CN105067959A (en) * | 2015-09-15 | 2015-11-18 | 长沙威胜信息技术有限公司 | Fault positioning method under ring network power supply condition |
| CN106021596A (en) * | 2016-06-07 | 2016-10-12 | 国网江苏省电力公司电力科学研究院 | Analyzing method of grid fault current shock topological graph |
| CN107516896A (en) * | 2017-08-28 | 2017-12-26 | 国网江苏省电力公司技能培训中心 | A kind of load restoration scheme generation method based on decision tree pruning algorithms |
| CN110348690A (en) * | 2019-06-12 | 2019-10-18 | 国网江苏省电力有限公司金湖县供电分公司 | Result queries menu power grid accident aid decision-making system and method based on tree search |
Non-Patent Citations (3)
| Title |
|---|
| 基于网络通路的区域电网故障行波定位方法;杜林;陈宏业;陈伟根;吴彬;;电力系统自动化(第24期);全文 * |
| 机房供电系统故障影响区域分析定位的实现;林惊雷;刘向东;;油气田地面工程(第06期);全文 * |
| 配电网负荷转带方法的研究;严凤, 陈志业, 春祥, 李鹏;华北电力大学学报(第02期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111899127A (en) | 2020-11-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Gholami et al. | Detecting the location of short-circuit faults in active distribution network using PMU-based state estimation | |
| CN101968525B (en) | Fault positioning method for power distribution network by combining simulation calculation and real-time monitoring | |
| CN106019084B (en) | Medium-voltage power distribution network disconnection fault diagnosis method based on power distribution and utilization data correlation | |
| CN102967780B (en) | Modeling method for substation intelligent alarm | |
| WO2016007217A1 (en) | Decision support system for outage management and automated crew dispatch | |
| WO2020162937A1 (en) | Automated model validation system for electrical grid | |
| CN108521123B (en) | Visual multi-contact-point power distribution network fault section association method | |
| CN112117763A (en) | Low-voltage distribution network topology identification and parameter estimation method | |
| WO2020171814A1 (en) | Event selection for power grid disturbance | |
| CN108206522B (en) | Power equipment state monitoring method and system | |
| CN110348114A (en) | A kind of non-precision fault recognition method of power grid completeness status information reconstruct | |
| CN111899127B (en) | Hierarchical fault sweep tree modeling method, model and application method thereof | |
| Sodin et al. | Precise PMU-based localization and classification of short-circuit faults in power distribution systems | |
| Mohamed et al. | A multi-agent system for fault location and service restoration in power distribution systems | |
| Janssen et al. | Monitoring, protection and fault location in power distribution networks using system-wide measurements | |
| Khare et al. | Optimal PMU placement using matrix modification based integer linear programming | |
| CN113009279B (en) | Neo4 j-based power distribution network voltage sag fault positioning and visualization system | |
| CN108521124B (en) | Visual distribution network fault section division method | |
| US20220284156A1 (en) | Real-time update of power system models for dynamic security assessment | |
| Li et al. | Phasor measurements-aided decision trees for power system security assessment | |
| Mekkanen et al. | IEC 61850-7-420 data object modeling for Smart control islanding detection | |
| CN115078920B (en) | Multi-information fusion active power distribution network single-phase earth fault line selection method and system | |
| Hoshyarzadeh et al. | The impact of CLOD load model parameters on dynamic simulation of large power systems | |
| Cruzat et al. | Reliability evaluation of ICT used on dynamic line rating for power system flexibility | |
| CN116359674B (en) | Active power distribution network fault positioning method and system based on fault transient signals |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |