CN116187593A - Power distribution network fault prediction processing method, device, equipment and storage medium - Google Patents
Power distribution network fault prediction processing method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention belongs to the technical field of power distribution network fault prediction, and particularly provides a power distribution network fault prediction processing method, a device, equipment and a storage medium, wherein the method comprises the following steps: acquiring node data acquired by each sensor in the power distribution network and performing clock synchronization calibration on the acquired node data; carrying out data analysis on the calibrated effective data, and comparing the analysis result with a set safety threshold range; if the node data is not in the safety threshold range, calculating multiple values of the node data and a preset reference value respectively; substituting the calculated multiple value into a fault probability model to obtain fault probability; and carrying out abnormality judgment according to the fault probability and sending an early warning signal generated by the node data, the node identification number and the positioning information to the power distribution maintenance station. And judging whether the abnormal type belongs to abnormal distribution equipment or line abnormality according to the node data, and sending an early warning signal by combining the abnormal type, so that the judging time of overhaulers is saved, and the timeliness of overhauling the distribution network is improved.
Description
Technical Field
The invention relates to the technical field of power distribution network fault diagnosis, in particular to a power distribution network fault prediction processing method, a device, equipment and a storage medium.
Background
The distribution network refers to a power network that receives electric energy from a power transmission network or a regional power plant, and distributes the electric energy locally or step by step according to voltage through a distribution facility. The power system of the distribution network has a complex structure and is generally composed of overhead lines, cables, towers, distribution transformers, isolating switches, reactive compensators, a plurality of auxiliary facilities and the like, and plays a role in distributing electric energy in the power network. The power distribution network is extremely easy to generate faults caused by equipment or line aging under the influence of severe operation environments. When the power distribution network is damaged, failed and other emergency conditions occur, operation and maintenance personnel often cannot find out in time, and in order to maintain efficient operation of the power distribution network, the power distribution network needs to be overhauled at random.
With the rapid development of power industry, distribution networks are more and more distributed, and due to the fact that the existing distribution network is long in interval span and more in network branches, a traditional scheduled maintenance method is adopted, and due to the fact that maintenance staff cannot know the actual running state of equipment in time, operation blindness is high, and excessive maintenance or insufficient maintenance is easy to cause. In addition, when a worker patrols and examines, the worker needs to carry a plurality of devices and collect circuit data of a plurality of suspicious circuits at the same time, then analysis and judgment are carried out based on all the circuit data, a large amount of manpower, material resources and time are consumed in the process, the requirement of modern power grid patrolling and examining cannot be met, when the power grid breaks down, the maintainer can hardly determine the fault position and the fault type, the maintenance time of a fault point is long, and unnecessary loss is caused to residents, factories and other power consumers along the way.
With the development of information technology, more and more power distribution network fault maintenance technologies are developed to ensure the normal operation of a power system. The information characteristics of the equipment in the running state are obtained through a state maintenance method, whether the equipment has faults or defects or not is determined through analysis and comparison, the positions of the parts with the faults or defects are determined, the setting of the reference value of the fault early warning mode is always a fixed value set according to experience, so that the workload of maintenance personnel is high, and the maintenance cost of the power distribution network is not reduced.
Disclosure of Invention
Aiming at the problems that in the related art, the information characteristics of equipment in the running state are obtained through a state maintenance method, whether the equipment has faults or defects or not is determined through analysis and comparison, the positions of the parts with the faults or defects are determined, the setting of a reference value of a fault early warning mode is always a fixed value set according to experience, so that the workload of maintenance personnel is very large, and the maintenance cost of a power distribution network is not reduced, the invention provides a power distribution network fault prediction processing method, a device, equipment and a storage medium.
The technical scheme of the invention provides a power distribution network fault prediction processing method, wherein a plurality of nodes are arranged in a power distribution network, and a sensor is arranged to collect data of each node, and the method comprises the following steps:
acquiring node data acquired by each sensor in the power distribution network and performing clock synchronization calibration on the acquired node data; the node data comprises current data and temperature data;
carrying out data analysis on the calibrated effective data, and comparing the analysis result with a set safety threshold range;
if the node data is not in the safety threshold range, calculating multiple values of the node data and a preset reference value respectively;
substituting the calculated multiple value into a fault probability model to obtain fault probability;
respectively acquiring node data, a node identification number and positioning information corresponding to nodes with the fault probability larger than a probability threshold value;
judging the abnormal type according to the node identification number;
if the power distribution network is in an abnormal state of the power distribution equipment, sending early warning signals generated by node data, node identification numbers and positioning information corresponding to the power distribution equipment to a power distribution maintenance station; if the power distribution network is in a line abnormal state, sending early warning signals generated by node data, node identification numbers and positioning information corresponding to the towers to a power distribution maintenance station.
In the method provided by the invention, each acquisition unit is subjected to time calibration before data acquisition, and the node data is subjected to time calibration once after the acquisition is finished, so that the accuracy of the acquired data is ensured.
As a further limitation of the technical scheme of the present invention, the step of calculating the multiple value of each node data and the preset reference value includes:
and judging that the node data is not zero, and obtaining a multiple value from the ratio of a larger value to a smaller value in the node data and a preset reference value.
As a further limitation of the technical scheme of the invention, the steps of acquiring the node data acquired by each sensor in the power distribution network and performing clock synchronization calibration on the acquired node data comprise the following steps:
screening the calibrated data;
acquiring effective data, and executing the following steps: carrying out data analysis on the calibrated effective data, and comparing the analysis result with a set safety threshold range;
when the node data is null, generating a sensor fault signal according to the node identification number and the positioning information corresponding to the null, and sending the fault signal to the power distribution maintenance station.
As a further limitation of the technical solution of the present invention, the method further comprises:
according to the received early warning signals or fault signals, scheduling parameters of maintenance personnel to be involved in maintenance are obtained;
and determining maintenance personnel participating in maintenance according to the scheduling parameters.
As a further limitation of the technical scheme of the invention, the scheduling parameters comprise the busy and idle state, the fault distance and the historical maintenance result score of the current maintenance personnel; the fault distance is the distance between the current maintenance personnel and the fault early warning point;
the step of determining maintenance personnel participating in the overhaul according to the scheduling parameters comprises the following steps:
acquiring the fault distance of maintenance personnel in the current idle state according to the scheduling parameters;
and determining that the maintenance personnel with the highest historical maintenance result score among the maintenance personnel with the fault distance smaller than the first threshold value participates in maintenance.
As a further limitation of the technical solution of the present invention, the method further comprises:
if maintenance personnel in the idle state and the fault distance is smaller than the first threshold value are not present, obtaining a historical maintenance result score of maintenance personnel with the minimum fault distance in the current idle state;
and when the score is larger than a set threshold value, determining that a maintainer with the smallest fault distance in the current idle state participates in maintenance.
As a further limitation of the technical solution of the present invention, the method further comprises:
after maintenance personnel finish maintenance, scoring the maintenance of the maintenance personnel according to the early warning type, the maintenance time and the fault maintenance result, and storing the scoring result.
In a second aspect, the technical scheme of the invention also provides a power distribution network fault prediction processing device, wherein a plurality of nodes are arranged in the power distribution network, and a sensor is arranged to collect data of each node;
the acquisition preprocessing module is used for acquiring node data acquired by each sensor in the power distribution network and carrying out clock synchronization calibration on the acquired node data; the node data comprises current data and temperature data;
the data analysis judging module is used for carrying out data analysis on the calibrated effective data and comparing the analysis result with a set safety threshold range;
the multiple value calculation module is used for calculating multiple values of the data of each node and a preset reference value respectively if the multiple values are not in the safety threshold range;
the fault probability acquisition module is used for substituting the calculated multiple value into a fault probability model to obtain fault probability;
the early warning node information acquisition module is used for respectively acquiring node data, a node identification number and positioning information corresponding to nodes with the fault probability larger than a probability threshold value;
the abnormal type judging module is used for judging the abnormal type according to the node identification number;
the early warning information generation module is used for sending early warning signals generated by node data, node identification numbers and positioning information corresponding to the power distribution equipment to a power distribution maintenance station if the power distribution network is in an abnormal state of the power distribution equipment; if the power distribution network is in a line abnormal state, sending early warning signals generated by node data, node identification numbers and positioning information corresponding to the towers to a power distribution maintenance station.
As a further limitation of the technical scheme of the present invention, the multiple value calculating module is specifically configured to determine that the node data is not zero, and obtain the multiple value from the ratio of the larger value to the smaller value in the node data and the preset reference value.
As a further limitation of the technical scheme of the invention, the device also comprises a sensor fault judging module, which is used for generating a sensor fault signal according to the node identification number and the positioning information corresponding to the null value when the node data is the null value and sending the fault signal to the power distribution maintenance station;
the acquisition preprocessing module is also used for screening the calibrated data to obtain effective data.
As a further limitation of the technical scheme of the invention, the device also comprises an overhaul scheduling module which is particularly used for acquiring scheduling parameters of maintenance personnel to be involved in overhaul according to the received early warning signals or fault signals and determining the maintenance personnel to be involved in overhaul according to the scheduling parameters.
As a further limitation of the technical scheme of the invention, the scheduling parameters comprise the busy and idle state, the fault distance and the historical maintenance result score of the current maintenance personnel; the fault distance is the distance between the current maintenance personnel and the fault early warning point;
the overhaul scheduling module comprises a parameter analysis unit and a personnel determination unit;
the parameter analysis unit is used for acquiring the fault distance of the maintenance personnel in the current idle state according to the scheduling parameters; if maintenance personnel in the idle state and the fault distance is smaller than the first threshold value are not present, obtaining a historical maintenance result score of maintenance personnel with the minimum fault distance in the current idle state;
the personnel determining unit is used for determining that the maintenance personnel with the highest historical maintenance result score among the maintenance personnel with the fault distance smaller than the first threshold value participates in maintenance; and when the historical overhaul result score of the maintainer with the minimum fault distance in the current idle state is larger than a set threshold value, determining that the maintainer with the minimum fault distance in the current idle state participates in overhaul.
As a further limitation of the technical scheme of the invention, the device also comprises a maintenance result scoring module which is used for scoring the maintenance of the maintenance personnel according to the early warning type, the maintenance time and the fault maintenance result after the maintenance personnel finish the maintenance, and storing the scoring result.
In a third aspect, the present invention further provides an electronic device, where the electronic device includes: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores computer program instructions executable by the at least one processor to enable the at least one processor to perform the power distribution network fault prediction processing method as described in the first aspect.
In a fourth aspect, the present disclosure provides a non-transitory computer readable storage medium, where the non-transitory computer readable storage medium stores computer instructions, where the computer instructions cause the computer to execute the power distribution network fault prediction processing method according to the first aspect.
From the above technical scheme, the invention has the following advantages:
1. the probability of occurrence of the fault risk of the power distribution equipment is reflected according to the multiple value between the node data collected by the power distribution equipment and the preset value, the fault prediction is carried out, the accuracy of fault early warning of the power distribution network is improved through calculation of the fault probability, and the maintenance cost of the power distribution network is reduced.
2. And analyzing the reasons of the occurrence of the abnormality according to the collected node data, positioning the abnormal power distribution equipment according to the node identification number, and scheduling maintenance personnel to maintain according to positioning information, thereby improving the processing efficiency of the abnormality early warning.
3. And judging whether the abnormal type belongs to abnormal distribution equipment or line abnormality according to the node data, and sending an early warning signal by combining the abnormal type, so that the judging time of overhaulers is saved, and the timeliness of overhauling the distribution network is improved.
4. And scheduling the maintenance personnel when carrying out exception handling by combining the historical maintenance result scores of the maintenance personnel, so that the stable operation of the power distribution network is further ensured.
In addition, the invention has reliable design principle, simple structure and very wide application prospect.
It can be seen that the present invention has outstanding substantial features and significant advances over the prior art, as well as its practical advantages.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a schematic flow chart of a method of one embodiment of the invention.
Fig. 2 is a schematic block diagram of an apparatus of one embodiment of the invention.
Detailed Description
In order to make the technical solution of the present invention better understood by those skilled in the art, the technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
Fig. 1 is a schematic flow chart of a power distribution network fault prediction processing method according to an embodiment of the present invention, in which a plurality of nodes are set in a power distribution network, and a sensor is set to collect data of each node, the method includes the following steps:
step 1: acquiring node data acquired by each sensor in the power distribution network and performing clock synchronization calibration on the acquired node data;
step 2: carrying out data analysis on the calibrated effective data, and comparing the analysis result with a set safety threshold range;
step 3: judging whether the safety threshold value is within the safety threshold value range or not;
if yes, the power distribution network is free of abnormality;
if not, executing the step 4;
step 4: calculating multiple values of the data of each node and a preset reference value respectively;
step 5: substituting the calculated multiple value into a fault probability model to obtain fault probability;
in the embodiment of the invention, a fault probability model
In (1) the->
For fitting error, +.>
Is natural constant (18)>
For the calculated multiplier value +.>
And lambda is a coefficient of the relationship between the multiple value set according to the historical fault probability and the fault probability model.
Step 6: respectively acquiring node data, a node identification number and positioning information corresponding to nodes with the fault probability larger than a probability threshold value;
step 7: judging the abnormal type according to the node identification number;
if the power distribution network is in an abnormal state of the power distribution equipment, executing the step 8; if the power distribution network is in a line abnormal state, executing the step 9;
step 8: sending early warning signals generated by node data, node identification numbers and positioning information corresponding to the power distribution equipment to a power distribution maintenance station;
step 9: and sending early warning signals generated by the node data, the node identification numbers and the positioning information corresponding to the towers to the power distribution maintenance station.
In the embodiment of the invention, the current sensor and the temperature sensor are arranged in the node through which the current passes, so that when one sensor is arranged, the empty value acquired by the node is easy to ignore when the sensor fails, the two sensors are arranged and clock synchronous calibration is performed, and when the failure acquired data of one sensor at the same time point is the empty value, the empty value is easy to find by comparing the data acquired at the same time point of the other sensor arranged at the node; the corresponding node data comprises current data and temperature data; in the method provided by the invention, each acquisition unit is subjected to time calibration before data acquisition, and the node data is subjected to time calibration once after the acquisition is finished, so that the accuracy of the acquired data is ensured. For example, when the acquired data of some nodes are null values, if the time is not calibrated, the null values are likely to be filled by other data, and if the other acquired data of the nodes are null values of corresponding time points after the time is calibrated, the null values can be intuitively displayed.
In step 4, the step of calculating the multiple value of each node data and the preset reference value includes:
and judging that the node data is not zero, and obtaining a multiple value from the ratio of a larger value to a smaller value in the node data and a preset reference value. The safety threshold range of the power distribution network is relatively large in the actual working process, and the preset reference value is generally set to be 1/2 of the maximum value of the safety threshold range in the safety threshold range; the multiple value here is a number greater than 1.
In addition, in the embodiment of the present invention, after the step 1 of acquiring node data acquired by each sensor in the power distribution network and performing clock synchronization calibration on the acquired node data, the method includes:
screening the calibrated data;
acquiring effective data, and executing the following steps: carrying out data analysis on the calibrated effective data, and comparing the analysis result with a set safety threshold range;
screening the data after time calibration, namely acquiring the null value of the node data, deleting the null value of the data center after the null value is acquired, obtaining effective data, generating a sensor fault signal according to the node identification number and the positioning information corresponding to the null value when the node data is the null value, and sending the fault signal to a power distribution maintenance station.
In some embodiments, the method further comprises:
step 10: according to the received early warning signals or fault signals, scheduling parameters of maintenance personnel to be involved in maintenance are obtained;
step 11: and determining maintenance personnel participating in maintenance according to the scheduling parameters.
In the above embodiment, step 10 may be performed after step 8 and step 9;
the scheduling parameters include busy state, fault distance and historical maintenance result score of the current maintenance personnel; the fault distance is the distance between the current maintenance personnel and the fault early warning point;
in step 11, the step of determining maintenance personnel participating in maintenance according to the scheduling parameters includes:
step 111: and acquiring the fault distance of the maintenance personnel in the current idle state according to the scheduling parameters.
Step 121: and determining that the maintenance personnel with the highest historical maintenance result score among the maintenance personnel with the fault distance smaller than the first threshold value participates in maintenance.
Step 122: if maintenance personnel in the idle state and the fault distance is smaller than the first threshold value are not present, historical maintenance result scores of maintenance personnel with the minimum fault distance in the current idle state are obtained.
Step 123: and when the score is larger than a set threshold value, determining that a maintainer with the smallest fault distance in the current idle state participates in maintenance.
It should be noted here that the method further includes:
step 12: after maintenance personnel finish maintenance, scoring the maintenance of the maintenance personnel according to the early warning type, the maintenance time and the fault maintenance result, and storing the scoring result.
As shown in fig. 2, the embodiment of the invention further provides a power distribution network fault prediction processing device, wherein a plurality of nodes are arranged in the power distribution network, and a sensor is arranged to collect data of each node;
the acquisition preprocessing module is used for acquiring node data acquired by each sensor in the power distribution network and carrying out clock synchronization calibration on the acquired node data; the node data comprises current data and temperature data;
the data analysis judging module is used for carrying out data analysis on the calibrated effective data and comparing the analysis result with a set safety threshold range;
the multiple value calculation module is used for calculating multiple values of the data of each node and a preset reference value respectively if the multiple values are not in the safety threshold range;
the fault probability acquisition module is used for substituting the calculated multiple value into a fault probability model to obtain fault probability;
the early warning node information acquisition module is used for respectively acquiring node data, a node identification number and positioning information corresponding to nodes with the fault probability larger than a probability threshold value;
the abnormal type judging module is used for judging the abnormal type according to the node identification number;
the early warning information generation module is used for sending early warning signals generated by node data, node identification numbers and positioning information corresponding to the power distribution equipment to a power distribution maintenance station if the power distribution network is in an abnormal state of the power distribution equipment; if the power distribution network is in a line abnormal state, sending early warning signals generated by node data, node identification numbers and positioning information corresponding to the towers to a power distribution maintenance station.
It should be noted that in the embodiment of the present invention, the multiple value calculation module is specifically configured to determine that the node data is not zero, and obtain the multiple value from the ratio of the larger value to the smaller value in the node data and the preset reference value.
In some embodiments, the device further includes a sensor fault judging module, configured to generate a sensor fault signal according to the node identification number and the positioning information corresponding to the null value when the node data is the null value, and send the fault signal to the power distribution maintenance station.
The acquisition preprocessing module is also used for screening the calibrated data to obtain effective data.
In some embodiments, the device further includes an overhaul scheduling module, which is specifically configured to obtain scheduling parameters of maintenance personnel to be involved in overhaul according to the received early warning signal or the fault signal, and determine the maintenance personnel to participate in overhaul according to the scheduling parameters.
It should be noted that the scheduling parameters include busy and idle states, fault distances and historical maintenance result scores of current maintenance personnel; the fault distance is the distance between the current maintenance personnel and the fault early warning point;
the overhaul scheduling module comprises a parameter analysis unit and a personnel determination unit;
the parameter analysis unit is used for acquiring the fault distance of the maintenance personnel in the current idle state according to the scheduling parameters; if maintenance personnel in the idle state and the fault distance is smaller than the first threshold value are not present, historical maintenance result scores of maintenance personnel with the minimum fault distance in the current idle state are obtained.
The personnel determining unit is used for determining that the maintenance personnel with the highest historical maintenance result score among the maintenance personnel with the fault distance smaller than the first threshold value participates in maintenance; and when the historical overhaul result score of the maintainer with the minimum fault distance in the current idle state is larger than a set threshold value, determining that the maintainer with the minimum fault distance in the current idle state participates in overhaul.
Correspondingly, the device also comprises a maintenance result scoring module which is used for scoring the maintenance of the maintenance personnel according to the early warning type, the maintenance time and the fault maintenance result and storing the scoring result.
The embodiment of the invention also provides electronic equipment, which comprises: the device comprises a processor, a communication interface, a memory and a bus, wherein the processor, the communication interface and the memory are in communication with each other through the bus. The bus may be used for information transfer between the electronic device and the sensor. The processor may call logic instructions in memory to perform the following method: step 1: acquiring node data acquired by each sensor in the power distribution network and performing clock synchronization calibration on the acquired node data; step 2: carrying out data analysis on the calibrated effective data, and comparing the analysis result with a set safety threshold range; step 3: judging whether the safety threshold value is within the safety threshold value range or not; if yes, the power distribution network is free of abnormality; if not, executing the step 4; step 4: calculating multiple values of the data of each node and a preset reference value respectively; step 5: substituting the calculated multiple value into a fault probability model to obtain fault probability; step 6: respectively acquiring node data, a node identification number and positioning information corresponding to nodes with the fault probability larger than a probability threshold value; step 7: judging the abnormal type according to the node identification number; if the power distribution network is in an abnormal state of the power distribution equipment, executing the step 8; if the power distribution network is in a line abnormal state, executing the step 9; step 8: sending early warning signals generated by node data, node identification numbers and positioning information corresponding to the power distribution equipment to a power distribution maintenance station; step 9: and sending early warning signals generated by the node data, the node identification numbers and the positioning information corresponding to the towers to the power distribution maintenance station. Step 10: according to the received early warning signals or fault signals, scheduling parameters of maintenance personnel to be involved in maintenance are obtained; step 11: and determining maintenance personnel participating in maintenance according to the scheduling parameters. Step 12: after maintenance personnel finish maintenance, scoring the maintenance of the maintenance personnel according to the early warning type, the maintenance time and the fault maintenance result, and storing the scoring result.
Further, the logic instructions in the memory described above may be implemented in the form of software functional units and stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the technology or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Embodiments of the present invention provide a non-transitory computer readable storage medium storing computer instructions that cause a computer to perform the methods provided by the method embodiments described above, for example, including: step 1: acquiring node data acquired by each sensor in the power distribution network and performing clock synchronization calibration on the acquired node data; step 2: carrying out data analysis on the calibrated effective data, and comparing the analysis result with a set safety threshold range; step 3: judging whether the safety threshold value is within the safety threshold value range or not; if yes, the power distribution network is free of abnormality; if not, executing the step 4; step 4: calculating multiple values of the data of each node and a preset reference value respectively; step 5: substituting the calculated multiple value into a fault probability model to obtain fault probability; step 6: respectively acquiring node data, a node identification number and positioning information corresponding to nodes with the fault probability larger than a probability threshold value; step 7: judging the abnormal type according to the node identification number; if the power distribution network is in an abnormal state of the power distribution equipment, executing the step 8; if the power distribution network is in a line abnormal state, executing the step 9; step 8: sending early warning signals generated by node data, node identification numbers and positioning information corresponding to the power distribution equipment to a power distribution maintenance station; step 9: and sending early warning signals generated by the node data, the node identification numbers and the positioning information corresponding to the towers to the power distribution maintenance station. Step 10: according to the received early warning signals or fault signals, scheduling parameters of maintenance personnel to be involved in maintenance are obtained; step 11: and determining maintenance personnel participating in maintenance according to the scheduling parameters. Step 12: after maintenance personnel finish maintenance, scoring the maintenance of the maintenance personnel according to the early warning type, the maintenance time and the fault maintenance result, and storing the scoring result.
As the power distribution network fault prediction processing method, apparatus, device, storage medium of the present invention are units and algorithm steps of examples described in connection with the embodiments disclosed herein, and can be implemented in electronic hardware, computer software, or a combination of both, and to clearly illustrate the interchangeability of hardware and software, the components and steps of examples have been generally described in terms of functions in the above description. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
Although the present invention has been described in detail by way of preferred embodiments with reference to the accompanying drawings, the present invention is not limited thereto. Various equivalent modifications and substitutions may be made in the embodiments of the present invention by those skilled in the art without departing from the spirit and scope of the present invention, and it is intended that all such modifications and substitutions be within the scope of the present invention/be within the scope of the present invention as defined by the appended claims. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. The power distribution network fault prediction processing method is characterized in that a plurality of nodes are arranged in a power distribution network, and a sensor is arranged to collect data of each node, and the method comprises the following steps:
acquiring node data acquired by each sensor in the power distribution network and performing clock synchronization calibration on the acquired node data;
carrying out data analysis on the calibrated effective data, and comparing the analysis result with a set safety threshold range;
if the node data is not in the safety threshold range, calculating multiple values of the node data and a preset reference value respectively;
substituting the calculated multiple value into a fault probability model to obtain fault probability;
respectively acquiring node data, a node identification number and positioning information corresponding to nodes with the fault probability larger than a probability threshold value;
judging the abnormal type according to the node identification number;
if the power distribution network is in an abnormal state of the power distribution equipment, sending early warning signals generated by node data, node identification numbers and positioning information corresponding to the power distribution equipment to a power distribution maintenance station; if the power distribution network is in a line abnormal state, sending early warning signals generated by node data, node identification numbers and positioning information corresponding to the towers to a power distribution maintenance station.
2. The power distribution network fault prediction processing method according to claim 1, wherein the step of calculating a multiple value of each node data and a preset reference value includes:
and judging that the node data is not zero, and obtaining a multiple value from the ratio of a larger value to a smaller value in the node data and a preset reference value.
3. The power distribution network fault prediction processing method according to claim 2, wherein the step of acquiring node data acquired by each sensor in the power distribution network and performing clock synchronization calibration on the acquired node data comprises:
screening the calibrated data;
acquiring effective data, and executing the following steps: carrying out data analysis on the calibrated effective data, and comparing the analysis result with a set safety threshold range;
when the node data is null, generating a sensor fault signal according to the node identification number and the positioning information corresponding to the null, and sending the fault signal to the power distribution maintenance station.
4. A power distribution network fault prediction processing method according to claim 3, further comprising:
according to the received early warning signals or fault signals, scheduling parameters of maintenance personnel to be involved in maintenance are obtained;
and determining maintenance personnel participating in maintenance according to the scheduling parameters.
5. The power distribution network fault prediction processing method according to claim 4, wherein the scheduling parameters include busy and idle states of current maintenance personnel, fault distances and historical maintenance result scores; the fault distance is the distance between the current maintenance personnel and the fault early warning point;
the step of determining maintenance personnel participating in the overhaul according to the scheduling parameters comprises the following steps:
acquiring the fault distance of maintenance personnel in the current idle state according to the scheduling parameters;
and determining that the maintenance personnel with the highest historical maintenance result score among the maintenance personnel with the fault distance smaller than the first threshold value participates in maintenance.
6. The power distribution network fault prediction processing method according to claim 5, further comprising:
if maintenance personnel in the idle state and the fault distance is smaller than the first threshold value are not present, obtaining a historical maintenance result score of maintenance personnel with the minimum fault distance in the current idle state;
and when the score is larger than a set threshold value, determining that a maintainer with the smallest fault distance in the current idle state participates in maintenance.
7. The power distribution network fault prediction processing method according to claim 6, further comprising:
after maintenance personnel finish maintenance, scoring the maintenance of the maintenance personnel according to the early warning type, the maintenance time and the fault maintenance result, and storing the scoring result.
8. The power distribution network fault prediction processing device is characterized in that a plurality of nodes are arranged in a power distribution network, and a sensor is arranged to collect data of each node, wherein the device comprises a collection preprocessing module, a data analysis judging module, a multiple value calculating module, a fault probability acquiring module, an early warning node information acquiring module, an abnormal type judging module and an early warning information generating module;
the acquisition preprocessing module is used for acquiring node data acquired by each sensor in the power distribution network and carrying out clock synchronization calibration on the acquired node data;
the data analysis judging module is used for carrying out data analysis on the calibrated effective data and comparing the analysis result with a set safety threshold range;
the multiple value calculation module is used for calculating multiple values of the data of each node and a preset reference value respectively if the multiple values are not in the safety threshold range;
the fault probability acquisition module is used for substituting the calculated multiple value into a fault probability model to obtain fault probability;
the early warning node information acquisition module is used for respectively acquiring node data, a node identification number and positioning information corresponding to nodes with the fault probability larger than a probability threshold value;
the abnormal type judging module is used for judging the abnormal type according to the node identification number;
the early warning information generation module is used for sending early warning signals generated by node data, node identification numbers and positioning information corresponding to the power distribution equipment to a power distribution maintenance station if the power distribution network is in an abnormal state of the power distribution equipment; if the power distribution network is in a line abnormal state, sending early warning signals generated by node data, node identification numbers and positioning information corresponding to the towers to a power distribution maintenance station.
9. An electronic device, the electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; a memory stores computer program instructions executable by at least one processor to enable the at least one processor to perform the power distribution network fault prediction processing method of any one of claims 1 to 7.
10. A non-transitory computer-readable storage medium storing computer instructions that cause the computer to perform the power distribution network fault prediction processing method according to any one of claims 1 to 7.
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