CN109408603B - Big data-based method for drawing topological graph of transformer area - Google Patents

Big data-based method for drawing topological graph of transformer area Download PDF

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CN109408603B
CN109408603B CN201811030398.8A CN201811030398A CN109408603B CN 109408603 B CN109408603 B CN 109408603B CN 201811030398 A CN201811030398 A CN 201811030398A CN 109408603 B CN109408603 B CN 109408603B
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赵新贞
李向奎
黄光政
韩为民
杨阳
李�昊
李欣
马运
马桂荣
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State Grid Corp of China SGCC
Jinan Power Supply Co of State Grid Shandong Electric Power Co Ltd
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Abstract

In order to solve the problems in the prior art of the transformer area topological graph drawing, the invention innovatively applies a graph theory and a big data mining technology prior algorithm (apriori algorithm) to the topological graph drawing of a transformer-circuit-meter box-electric energy meter-client in a low-voltage transformer area, realizes the automatic drawing of the transformer area topological graph and the display of a graph with the client key information through a minimum spanning tree algorithm, on one hand, the traditional mode of 'field general measurement and manual maintenance' is changed into the mode of 'automatic drawing and automatic verification', so that the cost is saved, the drawing accuracy, the working efficiency and the operation and distribution consistency rate level of the low-voltage transformer area are improved, and the current situations of non-standard data and non-clear structure at the end of a power grid are effectively solved; on the other hand, a large amount of precious data resources in the marketing system are fully utilized, powerful support is provided for visual accurate service of a distribution room manager, the attribution of the phase sequence of the user list is more definite, and deep application related to split-phase load prediction is fully developed.

Description

Big data-based method for drawing topological graph of transformer area
Technical Field
The invention relates to a method for drawing a topological graph of a transformer area, in particular to a method for drawing a topological graph of a transformer area based on big data.
Background
The low-voltage transformer area is used as the tail end of a power grid, is an important basis of an energy internet and is a key link influencing the power supply service level. With the increasingly deepened power system innovation, the pressure of high-quality service of power companies is continuously improved, how to accurately draw a distribution area topological graph under the existing conditions, realize visualization of emergency repair paths, effectively reduce the emergency repair duration of a power distribution network, reduce the fault outage duration, accurately calculate split-phase loads, continuously optimize a distribution network structure, continuously improve the business expansion quality, shorten the average time for reporting and installing power connection, construct a good operator environment, really realize that the power distribution network structure takes customers as the center, and become the focus of common attention of power supply companies.
The current transformer area topological graph drawing has the main problems that: firstly, a large amount of valuable data resources exist in the marketing system, but no clear 'specific meaning' exists, on one hand, the requirement that client information in the existing marketing system is dispersed and one chart of client key information cannot be displayed is met, on the other hand, a platform area topological graph is not fully applied to client resource positioning results and broadband carrier communication routing data, and powerful support is difficult to provide for visual accurate service of a platform area manager; secondly, the platform-user relationship is identified and maintained by manual site, and a platform area topological graph is drawn manually after being mainly measured on site generally, so that the workload is large and the accuracy is low; thirdly, the attribution of the phase sequence of the household meter is unclear, and the deep application related to the split-phase load prediction cannot be carried out; fourthly, although the high-voltage operation and distribution through level is high, the low-voltage distribution area has many devices, the network structure is complex, the field devices are frequently changed, the improvement difficulty of the operation and distribution consistency level is high, for example, in the south of china, 17378 existing distribution areas in south of china, 240.43 thousands of customers, 256 thousands of running metering meters, 47.67 thousands of metering boxes, more urban villages and old districts and low operation and distribution through level become a weak link of operation and distribution through work.
Disclosure of Invention
In order to solve the problems in the prior art of the drawing of the distribution room topological graph, the invention innovatively applies the graph theory and the prior algorithm (apriori algorithm) of the big data mining technology to the drawing of the topological graph of the low-voltage distribution room transformer-circuit-metering box-electric energy meter-client, realizes the automatic drawing of the distribution room topological graph and the display of a graph with the client key information through the minimum spanning tree algorithm, on one hand, the traditional mode of 'on-site general measurement and manual maintenance' is changed into the mode of 'automatic drawing and automatic verification', thereby saving the cost, improving the drawing accuracy, the working efficiency and the marketing and distribution consistency rate level of the low-voltage distribution room and effectively solving the current situations of non-standard data and non-clear structure at the end of the power grid; on the other hand, a large amount of precious data resources in the marketing system are fully utilized, powerful support is provided for visual accurate service of a distribution room manager, the attribution of the phase sequence of the user list is more definite, and deep application related to split-phase load prediction is fully developed.
The invention provides a large data-based method for drawing a topological graph of a transformer area, which comprises the following steps:
calculating the support degree and the confidence degree of the characteristic attribute of the electric meter and the electric meter in the same metering box through a prior algorithm, and clustering the electric meters in the same metering box into a node;
solving the minimum value of the objective function by using a minimum spanning tree algorithm, taking a transformer as a node, taking the total number of communication relay failures among the nodes as an objective function and taking voltage deviation among the nodes and space distance of the nodes as constraint conditions, wherein the obtained minimum spanning tree is a station area topological graph of a certain phase sequence, and drawing other two-phase station area topological graphs by using the same method to realize automatic drawing of the station area topological graph of 'transformer-line-electric metering box-electric energy meter-client';
and (3) checking the topological anomaly by using a rule that the inter-node carrier communication relay information only occurs on the same branch line, and correcting the related constraint conditions of the topological drawing model when the topology is abnormal until a station area topological graph consistent with the field condition is obtained.
Further, before the a priori algorithm calculation, the method further comprises: and (3) constructing a big data integration platform based on hadoop (a distributed system infrastructure) cloud computing, integrating data resources and realizing automatic collection of big data information.
Further, the step of establishing a hadoop cloud computing-based big data integration platform to integrate data resources and realize automatic collection of big data information specifically comprises the following steps:
a big data integration platform based on hadoop cloud computing is established, data resources such as a marketing service application System, an electricity consumption Information acquisition System, a marketing GIS (Geographic Information System) System, a PMS (power production management System) System and the like are integrated, and multidimensional data resources are fused;
the method comprises the steps of designing static attributes and dynamic variables in a comprehensive mode, transversely containing client information and data categories such as electrical quantity, abnormal events and geographic positions of equipment assets, longitudinally constructing a client resource record table with space dimensions and time dimensions, and achieving automatic collection of big data information.
Further, the method for drawing the station area topological graph based on the big data further includes: and combining the obtained distribution area topological graph consistent with the field situation with the customer electricity utilization information, and performing visual display on the same chart.
Further, the support degree and confidence degree calculation formula is as follows:
the support degree is P (n is a certain characteristic attribute of the electric meter in a certain measuring tank), represents the probability that a certain characteristic attribute of the electric meter and the electric meter occur at the same time in the same measuring tank,
the confidence P (the meter is in a certain characteristic property of the meter), which represents the probability that the meter will occur simultaneously in the same meter box in the event of a certain characteristic property of the meter,
the method comprises the steps of obtaining the degree of closeness of a certain characteristic attribute of an electric meter and the corresponding incidence relation of the electric meter in the same measuring box through calculation of support degree and confidence degree, wherein the support degree and the confidence degree are both larger than 75% to indicate that the certain characteristic attribute of the electric meter and the corresponding incidence relation of the electric meter in the same measuring box are close, taking intersection of the certain characteristic attribute of the electric meter with the close incidence relation and the set of the electric meters obtained by the association rule of the electric meter in the same measuring box, namely accurate box-meter relation, and clustering the electric meters in the same measuring box into a node.
Further, the association rule of a certain characteristic attribute of the electric meter and the association relation of the electric meter in the same measuring box is specifically as follows:
if the power failure time of the electric meters is the same, the electric meters are in the same metering box;
if the voltage fluctuation of the electric meters is the same, the electric meters are in the same metering box;
if the electricity consumption addresses of the electricity meters are similar, the electricity meters are in the same metering box;
if the box-meter relations of the electric meter marketing system are the same, the electric meters are in the same metering box;
if the periodic rotation time of the electric meters is the same, the electric meters are in the same metering box;
if the electricity consumption properties of the electric meters are the same, the electric meters are in the same metering box;
if the types of the electric meters in the industry are the same, the electric meters are in the same metering box.
Further, the minimum spanning tree algorithm is used, the transformer is used as a node, the total number of times of communication relay failure between the nodes is used as an objective function, voltage deviation between the nodes and node space distance are used as constraint conditions, the minimum value of the objective function is solved, and the obtained minimum spanning tree is a station area topological graph of a certain phase sequence:
applying a minimum spanning tree algorithm, taking a transformer as a node 1, and taking the relay failure times of the broadband carrier between a node i and a node j as cijIntroduction of an integer variable x of 0 to 1ijIf xij1, and i ≠ j denotes that the edge from i to j is in the tree, xijIf the number of the communication relay failures between the nodes is 0, the edge is not in the tree, and the total number z of the communication relay failures between the nodes is an objective function, wherein the expression of z is as follows:
Figure BDA0001789596470000041
the method comprises the steps of solving the minimum value of an objective function by taking the voltage deviation between nodes and the space distance of the nodes as constraint conditions, wherein n in an objective function expression is a positive integer, obtaining a topological graph of a certain phase sequence of a transformer area by using an obtained minimum spanning tree, and obtaining topological graphs of other two phases of the transformer area by using the same method.
Further, the constraint conditions in the minimum spanning tree algorithm are as follows:
in addition to node 1, each point has and only has one pass through, its expression:
Figure BDA0001789596470000051
at least one line exits from node 1, with the expression:
Figure BDA0001789596470000052
the voltage deviation between nodes does not exceed 3V, and the expression is as follows:
|ui-uj|≤3V,i＝2,3,......,n,j＝2,3,......,n；
the relay failure times between nodes are not less than 0 and not more than 10000, and the expression is as follows:
0≤cij≤10000,i＝2,3,......,n,j＝2,3,......,n；
r is the radius of the earth, XiIs the latitude, Y, of the node iiIs the longitude, X, of node ijIs the latitude, Y, of the node jjFor the longitude of the node j, the spatial distance between the nodes does not exceed 20 meters, and the expression is:
R*arccos[cos(Yi)*cos(Yj)*cos(Xi-Xj)+sin(Yi)*sin(Yj)]≤20,
wherein i 2,3, a.
N in the constraint condition expression is a positive integer, and the obtained minimum spanning tree is a topological graph of a certain phase sequence of the transformer area; and obtaining the topological graphs of the other two phases of the transformer area by using the same method.
Further, the inter-node carrier communication relay information is checked for topology abnormality only according to a rule that the relay information is generated on the same branch line, and relevant constraint conditions of a topology drawing model are corrected when the topology is abnormal until a station area topological graph consistent with a field situation is obtained, specifically:
if a certain node electric meter on the same branch line and any electric meter on the branch line node where the node electric meter is located do not have a relay in the distribution area topological graph, the electric meter is not located on the branch line;
and when the topology is abnormal, the field check is needed, relevant data of the ammeter is extracted again for redrawing, relevant constraint conditions of a topology drawing model are corrected, wherein the adjustment range of voltage deviation between nodes is 0.5V-5V, the adjustment range of relay failure times between nodes is 9000 times and 10000 times, and the adjustment range of space distance between nodes is 15 meters-30 meters until a station area topological graph consistent with the field condition is obtained.
The technical scheme adopted by the invention comprises the following technical effects:
in order to solve the problems in the prior art of the transformer area topological graph drawing, the invention innovatively applies the graph theory and the prior algorithm (apriori algorithm) of the big data mining technology to the topological graph drawing of the transformer-circuit-metering box-electric energy meter-client in the low-voltage transformer area, realizes the automatic drawing of the transformer area topological graph and the display of a graph of key information of the client through the minimum spanning tree algorithm, and changes the traditional mode of 'field general measurement and manual maintenance' into the mode of 'automatic drawing and automatic verification', thereby reducing the cost, and improving the drawing accuracy, the working efficiency and the operation and distribution consistency rate level of the low-voltage transformer area.
The invention innovatively adopts a prior algorithm in big data mining, accurately mines the association rule of other data information of the electric meters and the electric meters in a certain metering box, clusters the electric meters in the same metering box into a node after taking the intersection of the association rules, realizes the simplification of the power grid structure of the distribution room, effectively solves the current situations of non-standard data and unclear structure at the tail end of the power grid, and ensures the deepened application of various services based on the topology of the distribution room in a company.
According to the method, a large amount of precious data resources in a marketing system are fully utilized, the phase sequence attribution of the household meter is more definite, deep application related to split-phase load prediction is fully developed, the power utilization information of the transformer area users and visual topological display of equipment assets are performed, the fault first-aid repair speed is accelerated, the distribution trend of the transformer area power grid lines in the business expansion and installation process is effectively guided to be continuously optimized, and the average time of the installation and power connection is effectively shortened.
According to the three-phase topological graph of the transformer area, the system automatically calculates the load of the client carried by each phase, the power supply management unit adjusts the client carried by each phase on site according to the A, B, C three-phase load unbalance condition, or distributes the load to one phase with smaller load as much as possible according to the load condition carried by the three phases when the expansion scheme is made, and the problem of three-phase unbalance of the transformer area is effectively prevented and treated by accurately identifying the phase sequence of the client assets according to the topological graph of the transformer area.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without any creative effort.
FIG. 1 is a schematic process flow diagram of a first embodiment of the process of the present invention;
FIG. 2 is a schematic diagram illustrating an intersection of association rules in the solution of the present invention;
FIG. 3 is a schematic process flow diagram of a second embodiment of the process of the present invention;
FIG. 4 is a schematic process flow diagram of a third embodiment of the process of the present invention;
fig. 5 is a schematic flow chart of a method of a fourth embodiment of the method of the present invention.
Detailed Description
In order to clearly explain the technical features of the present invention, the following detailed description of the present invention is provided with reference to the accompanying drawings. The following disclosure provides many different embodiments, or examples, for implementing different features of the invention. To simplify the disclosure of the present invention, the components and arrangements of specific examples are described below. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. It should be noted that the components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and procedures are omitted so as to not unnecessarily limit the invention.
Example one
As shown in fig. 1, a method for drawing a platform area topological graph based on big data in the technical solution of the present invention includes the following steps:
and S1, calculating the support degree and the confidence degree of the characteristic attribute of the electric meter and the electric meter in the same metering box through a prior algorithm, and clustering the electric meters in the same metering box into a node.
S2, solving the minimum value of the objective function by using a minimum spanning tree algorithm, taking the transformer as a node, taking the total number of communication relay failures among the nodes as an objective function and taking voltage deviation among the nodes and space distance of the nodes as constraint conditions, obtaining the minimum spanning tree which is a station area topological graph of a certain phase sequence, and drawing other two-phase station area topological graphs by using the same method to realize automatic drawing of the station area topological graph of 'transformer-line-electric metering box-electric energy meter-client'.
And S3, checking topology abnormity by using a rule that the relay information of the inter-node carrier communication only occurs on the same branch line, and correcting related constraint conditions of the topology drawing model when the topology is abnormal until a distribution area topological graph consistent with the field situation is obtained.
In step S1, the support degree and the confidence degree of the characteristic attribute of the electric meter and the electric meter in the same measuring box are calculated by a prior algorithm, and clustering the electric meters in the same measuring box into a node specifically includes:
mining data resources by adopting a prior algorithm, wherein the data resources comprise the following characteristic attributes of the electric meter: the method comprises the following steps that the electric quantity (such as voltage and current) measured by the electric meter, an abnormal event (such as power failure time), customer electricity consumption property corresponding to the electric meter, customer electricity consumption address, number of a metering box where the electric meter is located and the like are found, and the support degree and confidence degree of a certain characteristic attribute of the electric meter and the electric meter in the same metering box are found, wherein a calculation formula of the support degree and the confidence degree is as follows:
the support degree is P (n is a certain characteristic attribute of the electric meter in a certain measuring tank), represents the probability that a certain characteristic attribute of the electric meter and the electric meter occur at the same time in the same measuring tank,
the confidence P (the meter is in a certain characteristic property of the meter), which represents the probability that the meter will occur simultaneously in the same meter box in the event of a certain characteristic property of the meter,
the incidence relation between a certain characteristic attribute of the electric meter and the electric meter in the same metering box can be obtained through calculation of the support degree and the confidence degree, the support degree and the confidence degree are both larger than 75% and indicate that the incidence relation between the certain characteristic attribute of the electric meter and the electric meter in the same metering box is tight, namely when the certain characteristic attribute of the electric meter is obtained, the probability of the electric meter in the same metering box is high, the intersection is taken between the certain characteristic attribute of the electric meter with the tight incidence relation and the set of the electric meters obtained by the association rule of the electric meter in the same metering box, namely the accurate box-meter relation is obtained, and the electric meters in the same metering box are clustered into a node.
Wherein, the association rule of a certain characteristic attribute of the electric meter and the electric meter in the association relationship of the same measuring box is as follows:
rule A: if the power failure time of the electric meters is the same, the electric meters are in the same metering box;
rule B: if the voltage fluctuation of the electric meters is the same, the electric meters are in the same metering box;
rule C: if the electricity consumption addresses of the electricity meters are similar, the electricity meters are in the same metering box;
rule D: if the box-meter relations of the electric meter marketing system are the same, the electric meters are in the same metering box;
rule E: if the periodic rotation time of the electric meters is the same, the electric meters are in the same metering box;
rule D: if the electricity consumption properties of the electric meters are the same, the electric meters are in the same metering box;
rule F: if the types of the electric meters in the industry are the same, the electric meters are in the same metering box.
And (3) taking an intersection of a certain characteristic attribute of the electric meter with the close association relation and the set of the electric meters obtained by the association rule of the electric meter in the same metering box, namely obtaining an accurate metering box relation, wherein the obtained association rule schematic diagram is shown in FIG. 2, and the intersection is the overlapped part of seven circles in FIG. 2. And clustering the electric meters in the same metering box into a node after the electric meters are subjected to the prior algorithm.
In step S2, using a minimum spanning tree algorithm, with a transformer as a node, and with the total number of communication relay failures between nodes as an objective function, and voltage deviation between nodes and a node spatial distance as constraint conditions, solving the minimum value of the objective function, and obtaining a minimum spanning tree, which is a station area topological graph of a certain phase sequence, and using the same method to obtain a station area topological graph of other two phases, so as to realize automatic drawing of a "transformer-line-electricity metering box-electricity meter-client" station area topological graph specifically:
the minimum spanning tree algorithm in the graph theory is applied, a transformer is taken as a node 1, and the relay failure times of the broadband carrier wave between a node i and a node j are cijIntroduction of an integer variable x of 0 to 1ijIf xij1 (and i ≠ j) indicates that the edge from i to j is in the tree, xij0 indicates that the edge is not in the tree;
taking the total times z of communication relay failures among all nodes as an objective function, wherein the expression of z is as follows:
Figure BDA0001789596470000103
the method comprises the following steps that n in an objective function expression is a positive integer, the minimum value of an objective function is solved by taking voltage deviation between nodes and node space distance as constraint conditions, and an obtained minimum spanning tree is a topological graph of a certain phase sequence of a transformer area; and obtaining the topological graphs of the other two phases of the transformer area by using the same method.
The constraint conditions in the minimum spanning tree algorithm are as follows:
in addition to node 1, each point has and only has one pass through, its expression:
Figure BDA0001789596470000101
at least one line exits from node 1, with the expression:
Figure BDA0001789596470000102
the voltage deviation between nodes does not exceed 3V, and the expression is as follows:
|ui-uj|≤3V,i＝2,3,......,n,j＝2,3,......,n；
the relay failure times between nodes are not less than 0 and not more than 10000, and the expression is as follows:
0≤cij≤10000,i＝2,3,......,n,j＝2,3,......,n；
r is the radius of the earth, XiIs the latitude, Y, of the node iiIs the longitude, X, of node ijIs the latitude, Y, of the node jjFor the longitude of the node j, the spatial distance between the nodes does not exceed 20 meters, and the expression is:
R*arccos[cos(Yi)*cos(Yj)*cos(Xi-Xj)+sin(Yi)*sin(Yj)]≤20,
where i is 2,3, … …, n, j is 2,3, … …, n.
Wherein n in the constraint conditional expression is a positive integer.
In step S3, the topology anomaly check is performed according to the rule that the relay information of inter-node carrier communication is only generated on the same branch line, and the constraint conditions related to the topology drawing model are modified when the topology is abnormal until a distribution room topology consistent with the field situation is obtained, specifically:
if a certain node electric meter on the same branch line and any electric meter on the branch line node where the node electric meter is located do not have a relay in the distribution area topological graph, the electric meter is not located on the branch line;
and when the topology is abnormal, the field check is needed, relevant data of the ammeter is extracted again for redrawing, relevant constraint conditions of a topology drawing model are corrected, wherein the adjustment range of voltage deviation between nodes is 0.5V-5V, the adjustment range of relay failure times between nodes is 9000 times and 10000 times, and the adjustment range of space distance between nodes is 15 meters-30 meters until a station area topological graph consistent with the field condition is obtained.
It should be noted that, in the present embodiment, after the station area topological graph drawn in step S2 needs to be subjected to field check, if the drawn station area topological graph is consistent with the field condition, it is indicated that the drawing of the station area topological graph is completed; and if the drawn region topological graph is inconsistent with the field situation, continuously modifying the constraint condition, trying to model, and regenerating the region topological graph until the drawn region topological graph is consistent with the field situation, so that the region topological graph is drawn completely. The constraint conditions in the scheme are that the voltage deviation between nodes does not exceed 3V, the relay failure times between nodes do not exceed 10000 times, and the space distance range between nodes does not exceed 20 meters, and the general optimal condition is summarized by experience in the continuous actual trial process.
Example two
As shown in fig. 3, a method for drawing a platform area topological graph based on big data in the technical solution of the present invention includes the following steps:
and S1, constructing a hadoop cloud computing-based big data integration platform, integrating data resources, and realizing automatic collection of big data information.
And S2, calculating the support degree and the confidence degree of the characteristic attribute of the electric meter and the electric meter in the same metering box through a prior algorithm, and clustering the electric meters in the same metering box into a node.
S3, solving the minimum value of the objective function by using a minimum spanning tree algorithm, taking the transformer as a node, taking the total number of communication relay failures among the nodes as an objective function and taking voltage deviation among the nodes and space distance of the nodes as constraint conditions, obtaining the minimum spanning tree which is a station area topological graph of a certain phase sequence, and drawing other two-phase station area topological graphs by using the same method to realize automatic drawing of the station area topological graph of 'transformer-line-electric metering box-electric energy meter-client'.
And S4, checking topology abnormity by using a rule that the relay information of the inter-node carrier communication only occurs on the same branch line, and correcting related constraint conditions of the topology drawing model when the topology is abnormal until a distribution area topological graph consistent with the field situation is obtained.
In step S1, a hadoop cloud computing-based big data integration platform is established, data resources are integrated, and automatic collection of big data information is specifically:
a big data integration platform based on hadoop cloud computing is established, data resources such as a marketing business application system, a power utilization information acquisition system, a marketing GIS system and a PMS system are integrated, and multidimensional data resources are fused;
and designing static attributes and dynamic variables in a comprehensive manner, transversely containing data categories such as client information and electrical quantity, abnormal events, geographic positions and the like of equipment assets, and longitudinally constructing a client resource record table with space dimensions and time dimensions.
The big data integration platform is completed by collecting customer information (house number, house name, address, user classification, industry classification and electricity price execution), metering equipment information (longitude and latitude of a metering box, position of rows and columns of an electric meter), power supply information, meter reading information (daily frozen electric quantity, voltage, current, abnormal events, broadband carrier wave meter reading routing information) and the like.
EXAMPLE III
As shown in fig. 4, a method for drawing a platform area topological graph based on big data in the technical solution of the present invention includes the following steps:
and S1, calculating the support degree and the confidence degree of the characteristic attribute of the electric meter and the electric meter in the same metering box through a prior algorithm, and clustering the electric meters in the same metering box into a node.
S2, solving the minimum value of the objective function by using a minimum spanning tree algorithm, taking the transformer as a node, taking the total number of communication relay failures among the nodes as an objective function and taking voltage deviation among the nodes and space distance of the nodes as constraint conditions, obtaining the minimum spanning tree which is a station area topological graph of a certain phase sequence, and drawing other two-phase station area topological graphs by using the same method to realize automatic drawing of the station area topological graph of 'transformer-line-electric metering box-electric energy meter-client'.
And S3, checking topology abnormity by using a rule that the relay information of the inter-node carrier communication only occurs on the same branch line, and correcting related constraint conditions of the topology drawing model when the topology is abnormal until a distribution area topological graph consistent with the field situation is obtained. .
And S4, combining the obtained distribution room topological graph consistent with the field situation with the customer electricity utilization information, and performing visual display on the same graph.
Example four
As shown in fig. 5, a method for drawing a platform area topological graph based on big data in the technical solution of the present invention includes the following steps:
and S1, constructing a hadoop cloud computing-based big data integration platform, integrating data resources, and realizing automatic collection of big data information.
And S2, calculating the support degree and the confidence degree of the characteristic attribute of the electric meter and the electric meter in the same metering box through a prior algorithm, and clustering the electric meters in the same metering box into a node.
S3, solving the minimum value of the objective function by using a minimum spanning tree algorithm, taking the transformer as a node, taking the total number of communication relay failures among the nodes as an objective function and taking voltage deviation among the nodes and space distance of the nodes as constraint conditions, obtaining the minimum spanning tree which is a station area topological graph of a certain phase sequence, and drawing other two-phase station area topological graphs by using the same method to realize automatic drawing of the station area topological graph of 'transformer-line-electric metering box-electric energy meter-client'.
And S4, checking topology abnormity by using a rule that the relay information of the inter-node carrier communication only occurs on the same branch line, and correcting related constraint conditions of the topology drawing model when the topology is abnormal until a distribution area topological graph consistent with the field situation is obtained. .
And S5, combining the obtained distribution room topological graph consistent with the field situation with the customer electricity utilization information, and performing visual display on the same graph.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.

Claims (9)

1. A method for drawing a zone topological graph based on big data is characterized by comprising the following steps:
calculating the support degree and the confidence degree of the characteristic attribute of the electric meter and the electric meter in the same metering box through a prior algorithm, and clustering the electric meters in the same metering box into a node;
solving the minimum value of the objective function by using a minimum spanning tree algorithm, taking a transformer as a node, taking the total number of communication relay failures among the nodes as an objective function and taking voltage deviation among the nodes and space distance of the nodes as constraint conditions, wherein the obtained minimum spanning tree is a station area topological graph of a certain phase sequence, and drawing other two-phase station area topological graphs by using the same method to realize automatic drawing of the station area topological graph of 'transformer-line-electric metering box-electric energy meter-client';
and (3) checking the topological anomaly by using a rule that the inter-node carrier communication relay information only occurs on the same branch line, and correcting the related constraint conditions of the topological drawing model when the topology is abnormal until a station area topological graph consistent with the field condition is obtained.
2. The big-data-based region topology map drawing method according to claim 1, further comprising, before said a priori algorithm calculation: and a big data integration platform based on hadoop cloud computing is established, data resources are integrated, and automatic collection of big data information is realized.
3. The big data based region topological graph drawing method according to claim 2, wherein the step of building a big data integration platform based on hadoop cloud computing to integrate data resources and realize automatic collection of big data information specifically comprises the steps of:
a big data integration platform based on hadoop cloud computing is established, data resources of a marketing service application system, a power utilization information acquisition system, a marketing GIS system and a PMS system are integrated, and multidimensional data resources are fused;
the method comprises the steps of designing static attributes and dynamic variables in a comprehensive mode, transversely containing client information and data categories such as electrical quantity, abnormal events and geographic positions of equipment assets, longitudinally constructing a client resource record table with space dimensions and time dimensions, and achieving automatic collection of big data information.
4. The big data-based region topology drawing method according to claim 1 or 2, further comprising: and combining the obtained distribution area topological graph consistent with the field situation with the customer electricity utilization information, and performing visual display on the same chart.
5. The big-data-based region topology drawing method according to claim 1, wherein said support and confidence calculation formula is as follows:
the support degree is P (a certain characteristic attribute of the electric meter is n, the electric meter is in a certain measuring tank), the probability that a certain characteristic attribute of the electric meter and the electric meter occur at the same measuring tank simultaneously is represented, the confidence degree is P (the electric meter is in a certain measuring tank | a certain characteristic attribute of the electric meter), the probability that the electric meter occurs at the same measuring tank simultaneously in the event of the certain characteristic attribute of the electric meter is represented, the method comprises the steps of obtaining the degree of closeness of a certain characteristic attribute of an electric meter and the corresponding incidence relation of the electric meter in the same measuring box through calculation of support degree and confidence degree, wherein the support degree and the confidence degree are both larger than 75% to indicate that the certain characteristic attribute of the electric meter and the corresponding incidence relation of the electric meter in the same measuring box are close, taking intersection of the certain characteristic attribute of the electric meter with the close incidence relation and the set of the electric meters obtained by the association rule of the electric meter in the same measuring box, namely accurate box-meter relation, and clustering the electric meters in the same measuring box into a node.
6. The method for drawing the topological graph of the distribution room based on the big data as claimed in claim 5, wherein the association rule of the characteristic attribute of the electric meter and the electric meter in the association relationship of the same metering box is specifically as follows:
if the power failure time of the electric meters is the same, the electric meters are in the same metering box;
if the voltage fluctuation of the electric meters is the same, the electric meters are in the same metering box;
if the electricity consumption addresses of the electricity meters are similar, the electricity meters are in the same metering box;
if the box-meter relations of the electric meter marketing system are the same, the electric meters are in the same metering box;
if the periodic rotation time of the electric meters is the same, the electric meters are in the same metering box;
if the electricity consumption properties of the electric meters are the same, the electric meters are in the same metering box;
if the types of the electric meters in the industry are the same, the electric meters are in the same metering box.
7. The big-data-based district topology drawing method according to claim 1, wherein the minimum spanning tree algorithm is used, a transformer is used as a node, the total number of communication relay failures between nodes is used as an objective function, the voltage deviation between nodes and the node space distance are used as constraint conditions, the minimum value of the objective function is solved, and the obtained minimum spanning tree is a district topology drawing of a certain phase sequence:
applying a minimum spanning tree algorithm, taking a transformer as a node 1, and taking the relay failure times of the broadband carrier between a node i and a node j as CijIntroduction of an integer variable x of 0 to 1ijIf xij1, and i ≠ j denotes that the edge from i to j is in the tree, xijIf the number of the communication relay failures between the nodes is 0, the edge is not in the tree, and the total number z of the communication relay failures between the nodes is an objective function, wherein the expression of z is as follows:
Figure FDA0003087670990000031
and solving the minimum value of the objective function by taking the voltage deviation between the nodes and the node space distance as constraint conditions, wherein n in the objective function expression is a positive integer, the obtained minimum spanning tree is a topological graph of a certain phase sequence of the transformer area, and the topological graphs of other two phases of the transformer area are obtained by using the same method.
8. The big-data-based region topology drawing method according to claim 7, wherein the constraint conditions in the minimum spanning tree algorithm are:
in addition to node 1, each point has and only has one line to go, its expression:
Figure FDA0003087670990000032
at least one line exits from node 1, with the expression:
Figure FDA0003087670990000033
the voltage deviation between nodes does not exceed 3V, and the expression is as follows:
|ui-uji ≦ 3V, i ≦ 2, 3.·, n, j ═ 2, 3.. ·, n; wherein u isiRepresenting the voltage at node i, ujRepresents the voltage at node j;
the relay failure times between nodes are not less than 0 and not more than 10000, and the expression is as follows:
0≤cij≤10000,i＝2,3,......,n,j＝2,3,......,n；
r is the radius of the earth, XiIs the latitude, Y, of the node iiIs the longitude, X, of node ijIs the latitude, Y, of the node jjFor the longitude of the node j, the spatial distance between the nodes does not exceed 20 meters, and the expression is:
Figure FDA0003087670990000041
wherein i 2,3, a.
N in the constraint condition expression is a positive integer, and the obtained minimum spanning tree is a topological graph of a certain phase sequence of the transformer area; and obtaining the topological graphs of the other two phases of the transformer area by using the same method.
9. The method for drawing the topology map of the distribution room based on the big data as claimed in claim 1 or 8, wherein the checking of the topology abnormality is performed only by a rule that the relay information of the inter-node carrier communication occurs on the same branch line, and the constraint condition related to the topology drawing model is modified when the topology is abnormal until the topology map of the distribution room consistent with the field situation is obtained, specifically:
if a certain node electric meter on the same branch line and any electric meter on the branch line node where the node electric meter is located do not have a relay in the distribution area topological graph, the electric meter is not located on the branch line;
and when the topology is abnormal, the field check is needed, relevant data of the ammeter is extracted again for redrawing, relevant constraint conditions of a topology drawing model are corrected, wherein the adjustment range of voltage deviation between nodes is 0.5V-5V, the adjustment range of relay failure times between nodes is 9000 times and 10000 times, and the adjustment range of space distance between nodes is 15 meters-30 meters until a station area topological graph consistent with the field condition is obtained.
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CN112910696A (en) * 2021-01-22 2021-06-04 上海三零卫士信息安全有限公司 Automatic modeling analysis method for network topology
CN115296295B (en) * 2022-08-10 2023-08-22 国网湖南省电力有限公司 Low-voltage distribution transformer area topology identification method and system based on cluster analysis and graph theory
CN115221979B (en) * 2022-09-15 2023-04-28 国网江西省电力有限公司电力科学研究院 Distribution area topology identification method and system based on minimum spanning tree
CN117639280B (en) * 2024-01-25 2024-04-12 国网四川省电力公司天府新区供电公司 Cloud computing-based intelligent power grid fault monitoring system

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012139658A2 (en) * 2011-04-15 2012-10-18 Siemens Aktiengesellschaft Low-voltage distribution system and method for operating the same
CN104573853A (en) * 2014-12-19 2015-04-29 华南理工大学 Systematic solution for voltage quality evaluation and optimization of low-voltage transformer area distribution networks
CN104852470A (en) * 2015-05-11 2015-08-19 国家电网公司 End user selection method based on graphical topology
CN106779168A (en) * 2016-11-23 2017-05-31 国网山东省电力公司威海供电公司 A kind of distribution transformer addressing and low pressure rack plan optimization method
CN106772499A (en) * 2016-11-16 2017-05-31 湖南华烨智能通信技术股份有限公司 A kind of method and system of automatic acquisition platform area topological diagram
CA2915674A1 (en) * 2015-12-17 2017-06-17 Francois Leonard Update of the topology of a distribution network by successive reattribution of counters
CN107196801A (en) * 2017-05-27 2017-09-22 深圳市均方根科技有限公司 A kind of platform area topological automatic identification system
CN107394897A (en) * 2017-08-21 2017-11-24 国网山东省电力公司济南供电公司 A kind of power distribution network intelligence self-healing method and system based on topological diagram

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012139658A2 (en) * 2011-04-15 2012-10-18 Siemens Aktiengesellschaft Low-voltage distribution system and method for operating the same
CN104573853A (en) * 2014-12-19 2015-04-29 华南理工大学 Systematic solution for voltage quality evaluation and optimization of low-voltage transformer area distribution networks
CN104852470A (en) * 2015-05-11 2015-08-19 国家电网公司 End user selection method based on graphical topology
CA2915674A1 (en) * 2015-12-17 2017-06-17 Francois Leonard Update of the topology of a distribution network by successive reattribution of counters
CN106772499A (en) * 2016-11-16 2017-05-31 湖南华烨智能通信技术股份有限公司 A kind of method and system of automatic acquisition platform area topological diagram
CN106779168A (en) * 2016-11-23 2017-05-31 国网山东省电力公司威海供电公司 A kind of distribution transformer addressing and low pressure rack plan optimization method
CN107196801A (en) * 2017-05-27 2017-09-22 深圳市均方根科技有限公司 A kind of platform area topological automatic identification system
CN107394897A (en) * 2017-08-21 2017-11-24 国网山东省电力公司济南供电公司 A kind of power distribution network intelligence self-healing method and system based on topological diagram

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
Application of geographic information system to distribution information support;Whei-Min Lin 等;《IEEE Transactions on Power Systems》;19960331;第190-197页 *
复杂网络拓扑图的自动绘制;王桐;《2011 2nd Asia-Pacific Conference on Wearable Computing Systems》;20110319;第126-129页 *

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