CN112332410A - Regional power utilization consistency accounting system - Google Patents
Regional power utilization consistency accounting system Download PDFInfo
- Publication number
- CN112332410A CN112332410A CN202011146503.1A CN202011146503A CN112332410A CN 112332410 A CN112332410 A CN 112332410A CN 202011146503 A CN202011146503 A CN 202011146503A CN 112332410 A CN112332410 A CN 112332410A
- Authority
- CN
- China
- Prior art keywords
- node
- abnormal
- nodes
- child
- consistency
- 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.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/086—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution networks, i.e. with interconnected conductors
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The invention provides a regional power utilization consistency accounting system, which comprises: the device comprises a meter reading control module, a consistency detection module, an abnormal node pair detection module and a detection result output module. According to the invention, the consistency of the subordinate data of the topological network node is judged through intelligent meter reading, the power utilization abnormity is intelligently detected, and the abnormal terminal is judged based on the prior characteristic of the power utilization of the terminal node, so that the intelligent, timely and fine detection of the power utilization abnormity behavior is realized, and the safety and reliability of the power supply service are greatly improved.
Description
Technical Field
The invention relates to the field of electric power, in particular to a regional power utilization consistency accounting system.
Background
Electric energy is taken as the basic energy of the modern civilian life, permeates to the aspects of social life, and as long as a place where people live has the application demand of electric power, the scientific management of the electric power is important work about the civilian life.
Obviously, the electricity consumption at least comprises safety problems and supply and demand problems, and the electricity service is qualified only under the condition that the supply meets the demand on the premise of safety. Therefore, the consistency of the power consumption between each node of the upstream and downstream nodes in the whole power grid topology needs to be detected, and through the consistency detection, whether the electric leakage problem exists or not can be found, so that potential safety hazards are stopped in time; on the other hand, whether the power stealing behavior exists can be found, so that the power consumption statistical accuracy is improved, and powerful data reference is provided for sufficient power supply.
However, in the existing application, the discovery of the electric leakage problem is completed by way of road patrol and reporting, so that the problems of high maintenance cost, untimely solution of potential safety hazards and the like are caused; for electricity stealing behaviors, the electricity stealing behaviors are judged by detecting the extreme condition of reading of an electricity meter, namely the reading of a certain household does not move for a long time, and the abnormality is considered, so that the method is obviously insufficient in scientificity, the problem finding rate is low, the electricity stealing behaviors are difficult to stop, and finally the civil problem of power failure of a district caused by insufficient power supply due to inaccurate power utilization requirement evaluation is easy to occur.
Therefore, an intelligent regional power utilization consistency accounting system is provided, so that the timeliness and the accuracy of problem detection are improved, and the operation efficiency is improved, which is a problem to be solved in the prior art.
Disclosure of Invention
The invention discloses a regional power utilization consistency accounting system which intelligently detects power utilization abnormity through intelligent meter reading and topology network node dependent data consistency judgment, judges an abnormal terminal based on a terminal node power utilization prior characteristic, realizes intelligent, timely and fine detection of power utilization abnormity behavior, and greatly improves the safety and reliability of power supply service.
The technical scheme adopted by the invention for solving the problems in the prior art is as follows:
the invention provides a regional power utilization consistency accounting system, which comprises: the system comprises a meter reading control module, a consistency detection module, an abnormal node pair detection module and a detection result output module;
the meter reading control module: the module is responsible for controlling each node to report the reading of the electric meter and sending the data to the consistency detection module;
the consistency detection module: the module is responsible for detecting the consistency of the power consumption of the nodes and outputting the results of the consistency of the power consumption of the nodes to a detection result output module, and the abnormal node is used for detecting the module, wherein the results of the consistency of the power consumption of the nodes comprise abnormal root node and child node information thereof;
an abnormal node pair detection module: the module is responsible for detecting abnormal node pairs, performing abnormal grade classification and outputting detection results to a detection result output module;
a detection result output module: the module collects the results input by the consistency detection module and the results input by the terminal abnormity detection module, and then outputs the total abnormal node pair information.
The meter reading control module, the consistency detection module, the abnormal node pair detection module and the detection result output module are matched with each other to carry out regional power utilization consistency accounting, and the method comprises the following steps:
step 1: the meter reading control module controls a total root node, an intermediate node and a terminal node in the power supply network topology to report electric quantity meter reading information;
step 2: the consistency detection module judges the consistency of the subordinate data of each node, if the data are normal, the step 4 is skipped, and if the data are abnormal, the step 3 is skipped;
and step 3: judging whether the child node is abnormal according to the electricity utilization prior characteristic of the child node of the abnormal root node, and outputting abnormal node pair information;
and 4, step 4: and outputting a normal prompt and finishing the consistency accounting of the current round.
Preferably, in the step 1, the meter reading control module sends a meter reading request to the total root node, the intermediate node and the terminal node, and the total root node, the intermediate node and the terminal node report corresponding meter readings, and the control method may adopt any one or two matching modes based on event triggering and periodic reporting; when the event is triggered, namely the meter needs to be read, the meter reading control module sends a meter reading request to each node, and then each node reads the meter and reports the result; the periodic reporting-reading table control module configures the reporting period of each node, and each node is operated according to the configured mode of periodically reporting the reading table result.
Preferably, in the step 2, the determining the consistency of the dependent data of each node is:
step 2.1, taking a power supply as a total root node of a tree, and storing readings of all nodes by adopting a multi-branch tree structure according to a power supply topology, wherein all nodes comprise the total root node, intermediate nodes and terminal nodes, and the intermediate nodes connected with the terminal nodes are also called end nodes; the next-level nodes directly connected with the same node all belong to child nodes of the node; the terminal nodes directly connected with the terminal nodes all belong to child nodes of the terminal nodes; the nodes with child nodes all belong to root nodes;
step 2.2, acquiring any root node which does not finish consistency accounting in the multi-branch tree;
step 2.3, obtaining position information and meter reading information of a root node and child nodes thereof, calculating the distance between each child node and the root node one by one, converting the distance to obtain the electric energy loss of the child nodes based on the relation between the electric energy transmission loss and the distance, adding the meter reading data of each child node to respective electric energy loss value to obtain the meter reading value corrected by each child node, accumulating the meter reading values corrected by each child node to obtain the meter reading total value of each child node under the root node, and finally judging whether the error between the meter reading value of the root node and the meter reading total value of the child nodes is within a preset threshold value 1, if so, considering that the electric energy application between the root node and the child nodes is normal, and if not, considering that the electric energy application between the node and the child nodes is abnormal;
and 2.4, judging whether a root node which does not finish the consistency accounting exists in the multi-branch tree, if so, jumping to the step 2.2, and if not, ending the consistency accounting.
Preferably, in step 2.3, in the case that the root node is the end node, the transmission loss between the root node and the child nodes thereof may be corrected by using an empirical value, and there is no need to check the transmission loss between the end node and each of the end nodes directly connected thereto one by one, so that the transportation accuracy is ensured and the operation efficiency is improved.
Preferably, in step 3, the node pair information with abnormal output includes pairing information of a root node and a child node;
preferably, in step 3, determining whether the child node is abnormal includes:
step 3.1, acquiring any root node which does not finish the judgment of whether the child node is abnormal or not in the abnormal root node;
step 3.2, if the root node is the terminal node, acquiring any child node which is not judged to be abnormal under the root node, and skipping to the step 3.3; if the root node is not the end node, identifying the root node and child nodes thereof as A-level abnormal node pairs, and jumping to the step 3.1;
step 3.3, acquiring characteristic parameters of historical electricity utilization record data of the child nodes and characteristic parameters of the current abnormity;
step 3.4, comparing the historical characteristic parameters with the abnormal characteristic parameters, if the historical characteristic parameters are not consistent with the abnormal characteristic parameters, identifying the root node and the child node pair as an A-level abnormal node pair, and otherwise, identifying the root node and the child node pair as a B-level abnormal node pair; the class a is more likely to represent an anomaly than class B.
Step 3.5, judging whether the child nodes under the root node acquired in the step 3.2 are judged completely, and if so, jumping to the step 3.6; if not, skipping to step 3.2;
step 3.6, judging whether the root node in the step 3.1 is judged to be finished, if so, skipping to the step 3.7; if not, skipping to step 3.1;
and 3.7, finishing judgment and outputting abnormal node pair information.
Preferably, in step 3.3, the characteristic parameter is used to characterize the electricity usage characteristic corresponding to the node, and the characteristic parameter adopts any one or a combination of several of total monthly electricity consumption, standard deviation monthly electricity consumption, and single-day maximum deviation monthly electricity consumption.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, the consistency of the subordinate data of the topological network node is judged through intelligent meter reading, the power utilization abnormity is intelligently detected, and the abnormal terminal is judged based on the prior characteristic of the power utilization of the terminal node, so that the intelligent, timely and fine detection of the power utilization abnormity behavior is realized, and the safety and reliability of the power supply service are greatly improved.
Drawings
FIG. 1 is a schematic flow chart of a regional power utilization consistency accounting method;
FIG. 2 is a system diagram of a regional power usage consistency accounting system;
FIG. 3 is a topological diagram of a regional power usage consistency accounting system.
Detailed Description
In order to make the technical solution and the advantages of the present invention clearer, the following explains embodiments of the present invention in further detail.
As shown in fig. 1 and fig. 2, the present invention provides a regional power consumption consistency accounting system, including: the device comprises a meter reading control module, a consistency detection module, an abnormal node pair detection module and a detection result output module.
The meter reading control module: the module is responsible for controlling each node to report the reading of the electric meter and sending the data to the consistency detection module;
the consistency detection module: the module is responsible for detecting the consistency of the power consumption of the nodes and outputting the results of the consistency of the power consumption of the nodes to a detection result output module, and the abnormal node is used for detecting the module, wherein the results of the consistency of the power consumption of the nodes comprise abnormal root node and child node information thereof;
an abnormal node pair detection module: the module is responsible for detecting abnormal node pairs, performing abnormal grade classification and outputting detection results to a detection result output module;
a detection result output module: the module collects the results input by the consistency detection module and the results input by the terminal abnormity detection module, and then outputs the total abnormal node pair information.
The meter reading control module, the consistency detection module, the abnormal node pair detection module and the detection result output module are matched with each other to carry out regional power utilization consistency accounting, and the method comprises the following steps:
step 1: the meter reading control module controls a total root node, an intermediate node and a terminal node in the power supply network topology to report electric quantity meter reading information;
step 2: the consistency detection module judges the consistency of the subordinate data of each node, if the data are normal, the step 4 is skipped, and if the data are abnormal, the step 3 is skipped;
and step 3: judging whether the child node is abnormal according to the electricity utilization prior characteristic of the child node of the abnormal root node, and outputting abnormal node pair information;
and 4, step 4: and outputting a normal prompt and finishing the consistency accounting of the current round.
The invention also provides a regional power utilization consistency accounting method, which comprises the specific steps of 1-4.
In the step 1, the meter reading control module sends a meter reading request to the total root node, the intermediate node and the terminal node, and the total root node, the intermediate node and the terminal node report corresponding meter readings; when the event is triggered, namely the meter needs to be read, the meter reading control module sends a meter reading request to each node, and then each node reads the meter and reports the result; the periodic reporting-reading table control module configures the reporting period of each node, and each node is operated according to the configured mode of periodically reporting the reading table result.
In step 2, the method for determining the consistency of the dependent data of each node is as follows:
step 2.1, taking a power supply as a total root node of a tree, and storing readings of all nodes by adopting a multi-branch tree structure according to a power supply topology, wherein all nodes comprise the total root node, intermediate nodes and terminal nodes, and the intermediate nodes connected with the terminal nodes are also called end nodes; the next-level nodes directly connected with the same node all belong to child nodes of the node; the terminal nodes directly connected with the terminal nodes all belong to child nodes of the terminal nodes; the nodes with child nodes all belong to root nodes;
step 2.2, acquiring any root node which does not finish consistency accounting in the multi-branch tree;
step 2.3, obtaining position information and meter reading information of a root node and child nodes thereof, calculating the distance between each child node and the root node one by one, converting the distance to obtain the electric energy loss of the child nodes based on the relation between the electric energy transmission loss and the distance, adding the meter reading data of each child node to respective electric energy loss value to obtain the meter reading value corrected by each child node, accumulating the meter reading values corrected by each child node to obtain the meter reading total value of each child node under the root node, and finally judging whether the error between the meter reading value of the root node and the meter reading total value of the child nodes is within a preset threshold value 1, if so, considering that the electric energy application between the root node and the child nodes is normal, and if not, considering that the electric energy application between the node and the child nodes is abnormal;
and 2.4, judging whether a root node which does not finish the consistency accounting exists in the multi-branch tree, if so, jumping to the step 2.2, and if not, ending the consistency accounting.
In step 2.3, for the case that the root node is the end node, the transmission loss between the root node and its child node (at this time, the child node is the terminal node) may be corrected by using an empirical value, and it is not necessary to check the transmission loss between the end node and each terminal node directly connected to the end node one by one, so that the transportation accuracy is ensured and the calculation efficiency is improved.
In the step 3, the node pair information with abnormal output includes pairing information of a root node and a child node;
in step 3, determining whether the child node is abnormal includes:
step 3.1, acquiring any root node which does not finish the judgment of whether the child node is abnormal or not in the abnormal root node;
step 3.2, if the root node is the terminal node, acquiring any child node which is not judged to be abnormal under the root node, and skipping to the step 3.3; if the root node is not the end node, identifying the root node and child nodes thereof as A-level abnormal node pairs, and jumping to the step 3.1;
step 3.3, acquiring characteristic parameters of historical electricity utilization record data of the child nodes and characteristic parameters of the current abnormity;
step 3.4, comparing the historical characteristic parameters with the abnormal characteristic parameters, if the historical characteristic parameters are not consistent with the abnormal characteristic parameters, identifying the root node and the child node pair as an A-level abnormal node pair, and otherwise, identifying the root node and the child node pair as a B-level abnormal node pair; the class a is more likely to represent an anomaly than class B.
Step 3.5, judging whether the child nodes under the root node acquired in the step 3.2 are judged completely, and if so, jumping to the step 3.6; if not, skipping to step 3.2;
step 3.6, judging whether the root node in the step 3.1 is judged to be finished, if so, skipping to the step 3.7; if not, skipping to step 3.1;
and 3.7, finishing judgment and outputting abnormal node pair information.
In the step 3.3, the characteristic parameter is used to represent the electricity usage characteristic corresponding to the node, and typically, the total monthly electricity usage amount, or the standard deviation of the monthly electricity usage, or the maximum deviation of the monthly electricity usage for a single day, and the like may be used, which is not limited specifically.
The following describes a specific implementation of a regional power consumption consistency accounting system by using a specific embodiment:
example (b): as shown in fig. 3, the present power network is composed of a power supply (i.e., a root node), an intermediate node 1_1, an intermediate node 1_2, an intermediate node 1_3, a terminal node 1_1_1, a terminal node 1_2_2, a terminal node 1_2_3, a terminal node 1_2_4, and a terminal node 1_3_ 1. Wherein, the power supply is a total root node; the intermediate node 1_1, the intermediate node 1_2 and the intermediate node 1_3 are final-stage nodes; the power supply, the intermediate node 1_1, the intermediate node 1_2 and the intermediate node 1_3 are root nodes; the intermediate node 1_1, the intermediate node 1_2 and the intermediate node 1_3 are child nodes of the intermediate node 1; the terminal node 1_1_1 is a child node of the intermediate node 1_ 1; the terminal node 1_2_1, the terminal node 1_2_2, the terminal node 1_2_3 and the terminal node 1_2_4 are child nodes of the intermediate node 1_ 2; the terminal node 1_3_1 is a child node of the intermediate node 1_ 3; the topology described above corresponds to the topology of fig. 3.
Firstly, meter reading information and a path loss value (the path loss value is calculated according to the transmission distance between the child node and the root node and the electric energy path loss) of each node are stored in a multi-fork mode, and the storage result is detailed in table 1.
Then, the dependency data consistency of each node is calculated according to the steps 2.1 to 2.4, if the preset threshold value 1 in this embodiment is 10% of the electric energy reading value of the root node, the error between the total root node and the "middle node 1" of the child node is (200- > 190- > 8)/200 is equal to 1%, and therefore, the node is within the threshold range of 10%, that is, the node is normal to the working state; the error of the root node "intermediate node 1" and its child nodes "intermediate node 1_ 1", "intermediate node 1_ 2", "intermediate node 1_ 3" is (190-30-7-80-5-40-3)/190 ═ 13.2, greater than 10% threshold, since the root node "intermediate node 1" is not the end node (corresponding to the condition of the latter half sentence of step 3.2), the root node and all its child nodes are identified as a level a abnormal node pair, i.e., { intermediate node 1, intermediate node 1_2}, { intermediate node 1, intermediate node 1_3} are a level a abnormal node pairs; then, error calculation is performed between the root node "intermediate node 1_ 1" and its child node "terminal node 1_1_ 1", where the error is (30-27-2)/30 ═ 3.3%, and is within the error range; the root node "intermediate node 1_ 2" and its child node "terminal node 1_2_ 1", "terminal node 1_2_ 2", "terminal node 1_2_ 3" and "terminal node 1_2_ 4" have error calculation, the error is (80-10-2-10-3-15-2-20-2)/80 is 20%, and the error range is 10% out, so the root node has a problem in dependency data consistency, because the root node "intermediate node 1_ 2" is the end node, the determination of the abnormal node pair is completed according to step 3.2 to step 3.7, in this embodiment, the determination of A, B abnormal level is performed by using the history mean value and the maximum deviation value as references, for example, the terminal node 1_2_1 has a history mean value of 30 and a maximum deviation value of 5, so if the read table value of the terminal node 1_2_1 is in the range of 25 to 35, the node is considered to be normal, but because the read table value of the terminal node 1_2_1 is 10 and is not in an expected range, the node pair { intermediate node 1_2 and terminal node 1_2_1} is determined as a class a abnormal node pair, abnormal conditions of the root node "intermediate node 1_ 2" and the other three child nodes can be calculated according to the same method, and because the other three child nodes are all in a historical data prediction range, the node pair is determined as a class B abnormal node pair, namely { intermediate node 1_2, terminal node 1_2_2}, { intermediate node 1_2, terminal node 1_2_3}, { intermediate node 1_2 and terminal node 1_2_4} are class B abnormal node pairs, and finally, the abnormal node pair information output by the method is:
a-level abnormal node pair:
{ intermediate node 1, intermediate node 1_2}, and,
{ intermediate node 1, intermediate node 1_2}, and,
{ intermediate node 1, intermediate node 1_3}, and,
{ intermediate node 1_2, terminal node 1_2_1}
B-level abnormal node pair:
{ intermediate node 1_2, terminal node 1_2_2}, and,
{ intermediate node 1_2, terminal node 1_2_3}, and,
{ intermediate node 1_2, end node 1_2_4 }.
Correspondingly, the power grid maintenance personnel can overhaul according to the priority based on the intelligent analysis result of the invention.
TABLE 1
According to the embodiment, the consistency of the subordinate data of the topological network nodes is judged through intelligent meter reading, the power utilization abnormity is intelligently detected, the abnormal terminal is judged based on the prior power utilization characteristic of the terminal node, the intelligent, timely and fine detection of the power utilization abnormity behavior is realized, and the safety and reliability of the power supply service are greatly improved
In summary, the present invention is only a preferred embodiment, and is not intended to limit the scope of the present invention, and various changes and modifications can be made by workers in the light of the above description without departing from the technical spirit of the present invention. The technical scope of the present invention is not limited to the content of the specification, and all equivalent changes and modifications in the shape, structure, characteristics and spirit described in the scope of the claims of the present invention are included in the scope of the claims of the present invention.
Claims (7)
1. A regional power usage consistency accounting system, comprising: the system comprises a meter reading control module, a consistency detection module, an abnormal node pair detection module and a detection result output module;
the meter reading control module: the module is responsible for controlling each node to report the reading of the electric meter and sending the data to the consistency detection module;
the consistency detection module: the module is responsible for detecting the consistency of the power consumption of the nodes and outputting the results of the consistency of the power consumption of the nodes to a detection result output module, and the abnormal node is used for detecting the module, wherein the results of the consistency of the power consumption of the nodes comprise abnormal root node and child node information thereof;
an abnormal node pair detection module: the module is responsible for detecting abnormal node pairs, performing abnormal grade classification and outputting detection results to a detection result output module;
a detection result output module: the module collects the results input by the consistency detection module and the results input by the terminal abnormity detection module and then outputs the total abnormal node pair information;
the meter reading control module, the consistency detection module, the abnormal node pair detection module and the detection result output module are matched with each other to carry out regional power utilization consistency accounting, and the method comprises the following steps:
step 1: the meter reading control module controls a total root node, an intermediate node and a terminal node in the power supply network topology to report electric quantity meter reading information;
step 2: the consistency detection module judges the consistency of the subordinate data of each node, if the data are normal, the step 4 is skipped, and if the data are abnormal, the step 3 is skipped;
and step 3: judging whether the child node is abnormal according to the electricity utilization prior characteristic of the child node of the abnormal root node, and outputting abnormal node pair information;
and 4, step 4: and outputting a normal prompt and finishing the consistency accounting of the current round.
2. The system according to claim 1, wherein:
in the step 1, the meter reading control module sends a meter reading request to the total root node, the intermediate node and the terminal node, and the total root node, the intermediate node and the terminal node report corresponding meter readings; when the event is triggered, namely the meter needs to be read, the meter reading control module sends a meter reading request to each node, and then each node reads the meter and reports the result; the periodic reporting-reading table control module configures the reporting period of each node, and each node is operated according to the configured mode of periodically reporting the reading table result.
3. The system according to claim 1, wherein:
in step 2, the method for determining the consistency of the dependent data of each node is as follows:
step 2.1, taking a power supply as a total root node of a tree, and storing readings of all nodes by adopting a multi-branch tree structure according to a power supply topology, wherein all nodes comprise the total root node, intermediate nodes and terminal nodes, and the intermediate nodes connected with the terminal nodes are also called end nodes; the next-level nodes directly connected with the same node all belong to child nodes of the node; the terminal nodes directly connected with the terminal nodes all belong to child nodes of the terminal nodes; the nodes with child nodes all belong to root nodes;
step 2.2, acquiring any root node which does not finish consistency accounting in the multi-branch tree;
step 2.3, obtaining position information and meter reading information of a root node and child nodes thereof, calculating the distance between each child node and the root node one by one, converting the distance to obtain the electric energy loss of the child nodes based on the relation between the electric energy transmission loss and the distance, adding the meter reading data of each child node to respective electric energy loss value to obtain the meter reading value corrected by each child node, accumulating the meter reading values corrected by each child node to obtain the meter reading total value of each child node under the root node, and finally judging whether the error between the meter reading value of the root node and the meter reading total value of the child nodes is within a preset threshold value 1, if so, considering that the electric energy application between the root node and the child nodes is normal, and if not, considering that the electric energy application between the node and the child nodes is abnormal;
and 2.4, judging whether a root node which does not finish the consistency accounting exists in the multi-branch tree, if so, jumping to the step 2.2, and if not, ending the consistency accounting.
4. The system according to claim 3, wherein:
in step 2.3, for the case that the root node is the end node, the transmission loss between the root node and the child nodes thereof may be corrected by using an empirical value, and it is not necessary to check the transmission loss between the end node and each terminal node directly connected thereto one by one, so as to improve the operation efficiency while ensuring the transportation accuracy.
5. The system according to claim 1, wherein:
in step 3, the node pair information with abnormal output includes pairing information of a root node and a child node.
6. The system according to claim 1, wherein:
in step 3, determining whether the child node is abnormal includes:
step 3.1, acquiring any root node which does not finish the judgment of whether the child node is abnormal or not in the abnormal root node;
step 3.2, if the root node is the terminal node, acquiring any child node which is not judged to be abnormal under the root node, and skipping to the step 3.3; if the root node is not the end node, identifying the root node and child nodes thereof as A-level abnormal node pairs, and jumping to the step 3.1;
step 3.3, acquiring characteristic parameters of historical electricity utilization record data of the child nodes and characteristic parameters of the current abnormity;
step 3.4, comparing the historical characteristic parameters with the abnormal characteristic parameters, if the historical characteristic parameters are not consistent with the abnormal characteristic parameters, identifying the root node and the child node pair as an A-level abnormal node pair, and otherwise, identifying the root node and the child node pair as a B-level abnormal node pair; the class a is more likely to represent an anomaly than class B.
Step 3.5, judging whether the child nodes under the root node acquired in the step 3.2 are judged completely, and if so, jumping to the step 3.6; if not, skipping to step 3.2;
step 3.6, judging whether the root node in the step 3.1 is judged to be finished, if so, skipping to the step 3.7; if not, skipping to step 3.1;
and 3.7, finishing judgment and outputting abnormal node pair information.
7. The system of claim 6, wherein:
in the step 3.3, the characteristic parameters are used for representing the electricity usage characteristics corresponding to the nodes, and the characteristic parameters adopt any one or a combination of more of the total monthly electricity consumption, the standard deviation of the monthly electricity consumption and the single-day maximum deviation value of the monthly electricity consumption.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011146503.1A CN112332410B (en) | 2020-10-23 | 2020-10-23 | Regional power utilization consistency accounting system |
| CN202110842869.0A CN113824109B (en) | 2020-10-23 | 2020-10-23 | Regional topology network power consumption data consistency accounting method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011146503.1A CN112332410B (en) | 2020-10-23 | 2020-10-23 | Regional power utilization consistency accounting system |
Related Child Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110842869.0A Division CN113824109B (en) | 2020-10-23 | 2020-10-23 | Regional topology network power consumption data consistency accounting method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112332410A true CN112332410A (en) | 2021-02-05 |
| CN112332410B CN112332410B (en) | 2021-06-22 |
Family
ID=74312211
Family Applications (2)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110842869.0A Active CN113824109B (en) | 2020-10-23 | 2020-10-23 | Regional topology network power consumption data consistency accounting method |
| CN202011146503.1A Active CN112332410B (en) | 2020-10-23 | 2020-10-23 | Regional power utilization consistency accounting system |
Family Applications Before (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110842869.0A Active CN113824109B (en) | 2020-10-23 | 2020-10-23 | Regional topology network power consumption data consistency accounting method |
Country Status (1)
| Country | Link |
|---|---|
| CN (2) | CN113824109B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115859068B (en) * | 2023-03-03 | 2023-05-16 | 四川三思德科技有限公司 | Environment information sensing method and system for intelligent water conservancy architecture |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104036357A (en) * | 2014-06-12 | 2014-09-10 | 国家电网公司 | Analysis method for electricity stealing behavioral mode of electricity utilization of user |
| CN106291436A (en) * | 2015-05-19 | 2017-01-04 | 中国科学院沈阳自动化研究所 | Intelligent grid neighbours region based on y-bend detection tree malice ammeter detection method |
| CN108123920A (en) * | 2016-11-30 | 2018-06-05 | 中国科学院沈阳自动化研究所 | Intelligent grid proximity network malicious user detection method based on stealing suspicion degree |
| CN108259195A (en) * | 2016-12-28 | 2018-07-06 | 阿里巴巴集团控股有限公司 | The determining method and system of the coverage of anomalous event |
| CN109948877A (en) * | 2018-12-03 | 2019-06-28 | 国网浙江新昌县供电有限公司 | A kind of accurate analysis method of electricity consumption behavior based on anomalous event combination |
| CN110380939A (en) * | 2019-08-08 | 2019-10-25 | 重庆邮电大学 | The conformance test method and system of local communication protocol in a kind of power information acquisition system |
| CN110470902A (en) * | 2019-08-16 | 2019-11-19 | 国网四川省电力公司电力科学研究院 | A kind of exception electricity detecting system and method based on platform area circuit topology relationship |
| CN110865329A (en) * | 2019-12-21 | 2020-03-06 | 国网山东省电力公司泰安供电公司 | Electric energy metering method and system based on big data self-diagnosis |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111366889B (en) * | 2020-04-29 | 2022-01-25 | 云南电网有限责任公司电力科学研究院 | Abnormal electricity utilization detection method for intelligent electric meter |
-
2020
- 2020-10-23 CN CN202110842869.0A patent/CN113824109B/en active Active
- 2020-10-23 CN CN202011146503.1A patent/CN112332410B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104036357A (en) * | 2014-06-12 | 2014-09-10 | 国家电网公司 | Analysis method for electricity stealing behavioral mode of electricity utilization of user |
| CN106291436A (en) * | 2015-05-19 | 2017-01-04 | 中国科学院沈阳自动化研究所 | Intelligent grid neighbours region based on y-bend detection tree malice ammeter detection method |
| CN108123920A (en) * | 2016-11-30 | 2018-06-05 | 中国科学院沈阳自动化研究所 | Intelligent grid proximity network malicious user detection method based on stealing suspicion degree |
| CN108259195A (en) * | 2016-12-28 | 2018-07-06 | 阿里巴巴集团控股有限公司 | The determining method and system of the coverage of anomalous event |
| CN109948877A (en) * | 2018-12-03 | 2019-06-28 | 国网浙江新昌县供电有限公司 | A kind of accurate analysis method of electricity consumption behavior based on anomalous event combination |
| CN110380939A (en) * | 2019-08-08 | 2019-10-25 | 重庆邮电大学 | The conformance test method and system of local communication protocol in a kind of power information acquisition system |
| CN110470902A (en) * | 2019-08-16 | 2019-11-19 | 国网四川省电力公司电力科学研究院 | A kind of exception electricity detecting system and method based on platform area circuit topology relationship |
| CN110865329A (en) * | 2019-12-21 | 2020-03-06 | 国网山东省电力公司泰安供电公司 | Electric energy metering method and system based on big data self-diagnosis |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113824109B (en) | 2023-08-18 |
| CN113824109A (en) | 2021-12-21 |
| CN112332410B (en) | 2021-06-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106802616B (en) | Building energy consumption comprehensive management system and method | |
| CN102637203B (en) | Method for processing electric quantity data and monitoring master station for automatic electric energy metering systems | |
| CN104112345B (en) | data monitoring method of remote wireless meter reading system | |
| CA2869372C (en) | Determining distribution system voltages from remote voltage alarm signals | |
| CN101162247B (en) | Sub-health running status recognition method of electrical device | |
| CN102931625B (en) | Online state maintenance intelligent decision analysis device used for relay protection device, and signal processing method and application thereof | |
| CN110806518B (en) | Transformer area line loss abnormal motion analysis module and operation method thereof | |
| US20140371933A1 (en) | Electric power consumption management system and method | |
| CN102882895A (en) | Method and device for identifying message attack | |
| CN110728836A (en) | Concentrator meter reading abnormity analysis method and system | |
| CN115685050B (en) | Electric energy meter fault detection method and system | |
| US20150025700A1 (en) | Apparatus and method remotely monitoring building state | |
| CN111260087A (en) | Management system for pipe network abnormity | |
| CN103926485B (en) | Power failure event judging method based on electric energy collecting terminal | |
| CN111666273B (en) | Meter reading system data validity analysis method and device | |
| CN112332410B (en) | Regional power utilization consistency accounting system | |
| CN115514100A (en) | Hybrid energy storage system based on multi-element energy storage and control | |
| KR102324783B1 (en) | Apparatus and method for Deep neural network based power demand prediction | |
| CN111080484A (en) | Method and device for monitoring abnormal data of power distribution network | |
| CN106451791B (en) | Power supply and outage information detection method and system | |
| WO2012137304A1 (en) | Remote monitor/control method and system therefor | |
| CN114037113B (en) | Intelligent water meter control method, device and system, storage medium and cloud computing center | |
| CN113438116B (en) | Power communication data management system and method | |
| CN115578017A (en) | Urban carbon disk checking intelligent management system and method | |
| CN107807325A (en) | Based on the theoretical railway track circuit reliability analysis system of multimode and its method |
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 |