CN116660680A - Node power line communication-based power outage event studying and judging method - Google Patents
Node power line communication-based power outage event studying and judging method Download PDFInfo
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- 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
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- H04B3/46—Monitoring; Testing
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B3/00—Line transmission systems
- H04B3/54—Systems for transmission via power distribution lines
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
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Abstract
The invention relates to the technical field of power system electricity consumption information acquisition, and discloses a method for studying and judging a power failure event based on node power line communication, which comprises the following steps: s1: each node communicates independently so as to judge whether each node is communicated or not; s2: the master station receives the node return signal in real time and performs data rearrangement processing on the received data; the data rearrangement directly uses a power line to enable the nodes to communicate with each other; s3: judging the power-off condition of each node by using a SAMME algorithm; s4: judging whether the power failure information is effective fault power failure data or not according to the obtained power failure information; s5: and determining the position of the fault outage according to the fault outage judgment information, and counting the position of the fault outage into a outage database. The invention can quickly find out the fault point, greatly reduce the calculation amount and calculation time for finding out the power failure fault reason step by step, and simultaneously reduce the influence caused by the data error.
Description
Technical Field
The invention relates to the technical field of power system electricity consumption information acquisition, in particular to a method for studying and judging a power failure event based on node power line communication.
Background
The power line communication is called as power line carrier (Power Line Carrier-PLC) communication, and refers to a special communication mode for voice or data transmission by using a high-voltage power line (generally referred to as a voltage class of 35kV or above in the power line carrier field), a medium-voltage power line (referred to as a voltage class of 10 kV) or a low-voltage distribution line (380/220V subscriber line) as an information transmission medium. The Modem is commonly called a Modem for broadband internet access through a power line. The existing power lines and sockets of the home or office are used to build a network to connect PCs, ADSL modems, set-top boxes, audio devices, monitoring devices and other intelligent electrical devices to transmit data, voice and video. The system has the characteristics of plug and play, and can transmit network IP digital signals through a common home power line.
At present, fault outage mainly occurs in a low-voltage branch under a public transformer, the circuit of the low-voltage branch is complex, the difficulty in finding out a fault point by power outage research and judgment is high, the conventional power outage event research and judgment method generally needs to search a first-stage topology for a fault outage reason after a terminal event is reported, and due to the fact that information is delayed and the like, the fault outage type is determined to be slow, so that the system frequently has the conditions of misjudgment, frequent report and the like when judging.
Disclosure of Invention
Aiming at the defects of the existing power failure event research and judgment method in the background technology, the invention provides a node power line communication power failure event research and judgment method, which has the advantages of quickly searching the position of a fault node, greatly reducing the calculation amount and calculation time for searching the fault reason step by step, reducing the influence caused by a data error, and solving the technical problems that the difficulty of finding a fault point in the power failure research and judgment in the background technology is higher, the type of determining the fault power failure is slower and the frequent report of misjudgment frequently occurs in the system judgment.
The invention provides the following technical scheme: a method for studying and judging a power failure event based on node power line communication comprises the following steps: s1: each node communicates independently so as to judge whether each node is communicated or not; s2: the master station receives the node return signal in real time and performs data rearrangement processing on the received data; the data rearrangement directly uses a power line to enable the nodes to communicate with each other; s3: judging the power-off condition of the node by using a SAMME algorithm; s4: judging whether the power failure information is effective fault power failure data or not according to the obtained power failure information; s5: and determining the position of the fault outage according to the fault outage judgment information, and counting the position of the fault outage into a outage database.
Preferably, S1 comprises: each node is communicated with the nodes connected with the node independently, signals are transmitted to each other, and the communication of each node exists independently and is not related to other nodes; when any node fails, the node communication is interrupted, but other nodes are not affected.
Preferably, S2 specifically includes: the data rearrangement directly uses a power line to enable the nodes to communicate with each other; for example: the upper node A sends signals to the lower nodes B1 and B2, the B1 and B2 also send signals to the upper node A, meanwhile, the B1 node and the lower nodes C1 and C2 send signals to each other, when the B1 node fails, the communication of the A, C node and the C2 node which are directly connected with the B1 node is interrupted by taking the B1 node as the center, but the B2 node, the C3 node and the lower nodes which are not connected with the B1 node are not affected, and can still communicate with each other. Each node sends the communication state signal of the node to the master station, and the master station receives the on-off state of each node, and the data needs to be rearranged due to the influence of data delay.
Preferably, the method for rearranging the data is to set the shortest state change time (for example, 10 s) and the maximum state change times (for example, 1) in unit time (for example, 30 s) by using a Flink SQL window function, and then sort the data received by the master station when the original circuit state changes, and restore the data to real data.
Preferably, S3 specifically includes: the method comprises the steps of utilizing a SAMME algorithm to learn and train data contained in each node in a power distribution network, and automatically judging the power-off condition of each node, wherein the power-off condition contains various abnormal data such as electric energy condition, fault node voltage, fault node power value and the like; is provided with k parameters, defines a vector of 1 x k dimensions, any one of whichThe samples can be expressed as (x) i ,y i ) The following steps are:
y i =(y i1 ,y i2 ,y i3 ,…,y ik )
wherein x is i Is an eigenvector, y i Is a sample tag vector;
the components are defined as follows:
using an addition model to mark the classifier as f m (x),f m (x) The method comprises the following steps:
the algorithm loss function uses the traditional Adaboost exponential loss function, and scalar conversion into vector can be performed:
l (y, f (x)) is a loss function, f m (x) Splitting into f m-1 (x)+β m g m (x) Training the result f of the previous round m-1 (x) The sample introduction weight omega is absorbed,
wherein beta is m To change parameters g m (x) The amount of change in the model is determined,
after calculating the inner product results in both cases,
the prediction is correct:
prediction error:
error rate:
wherein r is error Error rate, I is probability;
and finally updating the weight:
ω i =ω i expα m I,(g m ≠y i ),i=1,2,…,N
wherein alpha is m Is a variable parameter.
Preferably, S4 specifically includes: after the power-off information is obtained, the power-off type is matched with the planned power-off and marketing power-off in the existing database and the customer repair power-off; if the power failure condition belongs to one of the above conditions, the power failure data is combined with the power failure data and stored; if the power failure is not one of the conditions, judging that the power failure is caused by effective faults; the power outage types comprise planned power outage, marketing power outage and fault power outage; the planned power outage comprises planned power outage caused by power equipment line maintenance, power scheduling and the like; the marketing outage comprises outage caused by customer arrearages and outage caused by customer default electricity consumption; the fault power failure comprises power failure caused by the power distribution network fault and customer repair power failure.
Preferably, S4 more specifically includes:
s41: knowing the failed node a, if the failed node duration is greater than 15 minutes; if yes, proceeding to the next step; if not, no recording is performed;
s42: matching with the planned power outage to see whether the fault point is in the planned power outage range; if yes, the power failure is classified as planned power failure; if not, S43 is performed;
s43: matching with marketing outage, and checking whether the fault point is in the marketing outage range; if yes, the power failure of the camping pin is included; if not, S44 is performed;
s44: matching with customer service repair power failure, wherein the fault point is in the customer repair power failure range; if yes, the power failure is reported by the clients; if not, the fault is marked as a valid fault power failure.
Preferably, S5 specifically includes: according to the fault outage node information, the specific outage position information is rapidly displayed through a GIS (geographic information system), a fault outage list is generated, and the fault outage list is counted into an outage database.
Preferably, the method for judging whether the high and medium voltage ends are in fault and power failure comprises the following steps: rearranging the data of the receiving columns, searching the nodes which cannot be communicated downwards from the uppermost node to find the nodes which cannot be communicated, and setting the nodes as X 1 From X 1 The node searches downwards, and a node X which can not be communicated is set 2 If with X 2 If none of the connected nodes can communicate, then it can be determined that X 2 Is a failed node.
The invention has the following beneficial effects:
according to the node power line communication power failure event studying and judging method, the power line communication technology is utilized, the position of a power failure fault node can be rapidly determined, one-stage topology is not required to search for the reason of the power failure, the calculation amount and calculation time for searching for the reason of the power failure step by step are greatly reduced, the type of the power failure can be rapidly determined, and meanwhile, the influence caused by a data error is reduced; the accuracy of identifying the power failure fault node can be effectively improved by utilizing the SAMME algorithm, meanwhile, the efficiency of judging the power failure is greatly improved, and the misjudgment rate is also greatly reduced.
Drawings
FIG. 1 is a workflow diagram of the present invention;
FIG. 2 is a schematic diagram of the power line communication between nodes according to the present invention;
FIG. 3 is a flow chart of the invention for judging the failure and power failure of the low voltage end;
fig. 4 is a view operation interface diagram of the GIS electronic map of the planned blackout event.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, a method for studying and judging a power failure event based on node power line communication includes: s1: each node communicates independently so as to judge whether each node is communicated or not; s2: the master station receives the node return signal in real time and performs data rearrangement processing on the received data; s3: judging the power-off condition of the node by using a SAMME algorithm; s4: judging whether the power failure information is effective fault power failure data or not according to the obtained power failure information; s5: and determining the position of the fault outage according to the fault outage judgment information, and counting the position of the fault outage into a outage database.
Specifically, S1 specifically includes: each node is communicated with the nodes connected with the node independently, signals are transmitted to each other, and the communication of each node exists independently and is not related to other nodes; when any node fails, the node communication is interrupted, but other nodes are not affected.
Specifically, as shown in fig. 2, S2 specifically includes: the data rearrangement directly uses a power line to enable the nodes to communicate with each other; for example: the upper node A sends signals to the lower nodes B1 and B2, the B1 and B2 also send signals to the upper node A, meanwhile, the B1 node and the lower nodes C1 and C2 send signals to each other, when the B1 node fails, the communication of the A, C node and the C2 node which are directly connected with the B1 node is interrupted by taking the B1 node as the center, but the B2 node, the C3 node and the lower nodes which are not connected with the B1 node are not affected, and can still communicate with each other. Each node sends the communication state signal of the node to the master station, and the master station receives the on-off state of each node, and the data needs to be rearranged due to the influence of data delay.
Specifically, the method for data rearrangement is to set the shortest state change time (for example, 10 s) and the maximum state change times (for example, 1 time) in unit time (for example, 30 s) by using the Flink SQL window function, and then sort the data received by the master station when the original circuit state changes, and restore the data to real data.
Specifically, S3 specifically includes: the method comprises the steps of utilizing a SAMME algorithm to learn and train data contained in each node in a power distribution network, and automatically judging the power-off condition of each node, wherein the power-off condition contains various abnormal data such as electric energy condition, fault node voltage, fault node power value and the like; there are k parameters defining a vector of dimension 1 x k, any one of which can be expressed as (x i ,y i ) The following steps are:
y i =(y i1 ,y i2 ,y i3 ,…,y ik ),
wherein x is i Is an eigenvector, y i Is a sample tag vector;
the components are defined as follows:
using an addition model to mark the classifier as f m (x),f m (x) The method comprises the following steps:
the algorithm loss function uses the traditional Adaboost exponential loss function, and scalar conversion into vector can be performed:
l (y, f (x)) is a loss function,will f m (x) Splitting into f m-1 (x)+β m g m (x) Training the result f of the previous round m-1 (x) The sample introduction weight omega is absorbed,
wherein beta is m To change parameters g m (x) Model variation;
after calculating the inner product results in both cases,
the prediction is correct:
prediction error:
error rate:
wherein r is error Error rate, I is probability;
and finally updating the weight:
ω i =ω i expα m I,(g m ≠y i ),i=1,2,…,N,
wherein alpha is m Is a variable parameter.
Specifically, S4 specifically includes: the power failure types are classified into fault power failure, planned power failure and marketing power failure, and the fault power failure in the three power failure time needs to be timely researched and judged and the circuit is salvaged. The planned power outage comprises planned power outage caused by power equipment line overhaul, power scheduling and the like; marketing outage comprises outage caused by customer arrearage and outage caused by customer default electricity consumption; the fault outage comprises outage caused by the power distribution network fault and customer repair outage. The customer repair power failure belongs to a known event and does not need to be researched and judged, so that the power failure research and judgment mainly researches and judges the power failure caused by the power distribution network fault. After obtaining the outage information, matching with the planned outage and the marketing outage in the existing database and the customer repair outage; if the power failure condition belongs to one of the above conditions, the power failure data is combined with the power failure data and stored; if the power failure does not belong to any of the above cases, it can be determined that the power failure is valid.
Specifically, as shown in fig. 3, S4 more specifically includes:
s41: knowing the failed node a, if the failed node duration is greater than 15 minutes; if yes, proceeding to the next step; if not, no recording is performed;
s42: matching with the planned power outage to see whether the fault point is in the planned power outage range; if yes, the power failure is classified as planned power failure; if not, S43 is performed;
s43: matching with marketing outage, and checking whether the fault point is in the marketing outage range; if yes, the power failure of the camping pin is included; if not, S44 is performed;
s44: matching with customer service repair power failure, wherein the fault point is in the customer repair power failure range; if yes, the power failure is reported by the clients; if not, the fault is marked as a valid fault power failure.
Specifically, as shown in fig. 4, S5 specifically includes: according to the fault outage node information, the specific outage position information is rapidly displayed through a GIS system, a fault outage list is generated, and the fault outage list is counted into a outage database.
Specifically, the method for judging whether the high and medium voltage ends are in fault and power failure comprises the following steps: rearranging the data of the receiving columns, searching the nodes which cannot be communicated downwards from the uppermost node to find the nodes which cannot be communicated, and setting the nodes as X 1 From X 1 The node searches downwards, and a node which can not be communicated is arrangedPoint X 2 If with X 2 If none of the connected nodes can communicate, then it can be determined that X 2 Is a failed node.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. The method for studying and judging the power failure event based on the node power line communication is characterized by comprising the following steps of:
s1: each node communicates independently so as to judge whether each node is communicated or not;
s2: the master station receives the node return signal in real time and performs data rearrangement processing on the received data; the data rearrangement directly uses a power line to enable the nodes to communicate with each other;
s3: judging the power-off condition of the node by using a SAMME algorithm;
s4: judging whether the power failure information is effective fault power failure data or not according to the obtained power failure information;
s5: and determining the position of the fault outage according to the fault outage judgment information, and counting the position of the fault outage into a outage database.
2. The method for studying and judging a power outage event based on node power line communication according to claim 1, wherein S1 specifically comprises: each node is communicated with the nodes connected with the node independently, signals are transmitted to each other, and the communication of each node exists independently and is not related to other nodes; when any node fails, the node communication is interrupted, but other nodes are not affected.
3. The method for studying and judging a power outage event based on node power line communication according to claim 1, wherein S2 specifically comprises: each node sends the communication state signal of the node to the master station, and the master station receives the on-off state of each node, and the data needs to be rearranged due to the influence of data delay.
4. A data rearrangement according to claim 3, and according to claim 3, wherein the minimum state change time (for example, 10 s) and the maximum state change times (for example, 1 time) per unit time (for example, 30 s) are set by using a flank SQL window function, and then the data received by the master station when the original circuit state is changed is collated and restored to real data.
5. The method for studying and judging a power outage event based on node power line communication according to claim 1, wherein S3 specifically comprises: the method comprises the steps of utilizing a SAMME algorithm to learn and train data contained in each node in a power distribution network, and automatically judging the power-off condition of each node, wherein the power-off condition contains various abnormal data such as electric energy condition, fault node voltage, fault node power value and the like; there are k parameters defining a vector of dimension 1 x k, any one of which can be expressed as (x i ,y i ) The following steps are:
y i =(y i1 ,y i2 ,y i3 ,…,y ik ),
wherein x is i Is an eigenvector, y i Is a sample tag vector;
the components are defined as follows:
using an addition model to mark the classifier as f m (x),f m (x) The method comprises the following steps:
the scalar conversion to a vector may then be performed:
will f m (x) Splitting into f m-1 (x)+β m g m (x) Training the result f of the previous round m-1 (x) Absorbing the sample introduction weight omega, and then:
where L (y, f (x)) is a loss function, β m To change parameters g m (x) Model variation;
after calculating the inner product results in both cases,
the prediction is correct:
prediction error:
error rate:
wherein r is error Error rate, I is probability;
and finally updating the weight:
ω i =ω i expα m I,(g m ≠y i ),i=1,2,…,N,
wherein alpha is m Is a variable parameter.
6. The method for studying and judging a power outage event based on node power line communication of claim 1, wherein S4 specifically comprises: after the power-off information is obtained, the power-off type is matched with the planned power-off and marketing power-off in the existing database and the customer repair power-off; if the power failure condition belongs to one of the above conditions, the power failure data is combined with the power failure data and stored; if the power failure is not one of the conditions, judging that the power failure is effective fault.
7. The power outage type of claim 6, comprising: planning a power outage, marketing a power outage, and a fault power outage; the planned power outage comprises planned power outage caused by power equipment line maintenance, power scheduling and the like; the marketing outage comprises outage caused by customer arrearages and outage caused by customer default electricity consumption; the fault power failure comprises power failure caused by the power distribution network fault and customer repair power failure.
8. The method for studying and judging a power outage event based on node power line communication of claim 6, wherein S4 more specifically comprises:
s41: knowing the failed node a, if the failed node duration is greater than 15 minutes; if yes, proceeding to the next step; if not, no recording is performed;
s42: matching with the planned power outage to see whether the fault point is in the planned power outage range; if yes, the power failure is classified as planned power failure; if not, S43 is performed;
s43: matching with marketing outage, and checking whether the fault point is in the marketing outage range; if yes, the power failure of the camping pin is included; if not, S44 is performed;
s44: matching with customer service repair power failure, wherein the fault point is in the customer repair power failure range; if yes, the power failure is reported by the clients; if not, the fault is marked as a valid fault power failure.
9. The method for studying and judging a power outage event based on node power line communication of claim 1, wherein S5 specifically comprises: according to the fault outage node information, the specific outage position information is rapidly displayed through a GIS (geographic information system), a fault outage list is generated, and the fault outage list is counted into an outage database.
10. The method for studying and judging the power failure event based on the node power line communication according to claim 1, wherein the method for judging the high-voltage end and the medium-voltage end comprises the following steps: after rearranging the data of the received columns, the pair cannot
The node for communication is set as X by searching down from the uppermost node to find out the node which can not complete communication 1 ,
From X 1 The node searches downwards, and a node X which can not be communicated is set 2 If with X 2 None of the connected nodes can communicate with each other,
then X can be determined 2 Is a failed node.
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