CN116050599A - Line icing fault prediction method, system, storage medium and equipment - Google Patents
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Abstract
The invention discloses a line icing fault prediction method, a system, a storage medium and equipment, and relates to the technical field of power grid disaster prevention, wherein the method comprises the following steps: collecting an icing data set, wherein the icing data set comprises historical meteorological data, current meteorological data, historical icing data, equipment information, overhaul information and fault information; preprocessing the icing data set; constructing a meteorological icing model based on historical meteorological data and historical icing data; inputting current meteorological data into a meteorological icing model, and predicting an icing area; based on the ice coating area and the equipment information, obtaining an ice coating line through calculation; analyzing the icing data set, calculating the characteristics of the line icing fault, and constructing a line icing fault model; the method and the device can solve the technical problems of high construction and maintenance cost caused by measuring the ice coating thickness by using an artificial ice observation station in the prior art.
Description
Technical Field
The invention relates to the technical field of disaster prevention of power grids, in particular to a line icing fault prediction system, a storage medium and equipment.
Background
The power system is a huge and complex system involving multiple links of transmission, delivery, transformation, distribution, utilization and the like, and the safe operation of the power system is closely related to the meteorological environment. The ice coating of the power transmission line can cause huge damage to a power system. The continuous increase of the thickness of the ice coating can cause overload of bearing load of a power transmission line, thereby causing serious accidents such as tripping, collapse of an iron tower, power communication interruption and the like, and seriously threatening the reliability of power supply and the integrity of power transmission infrastructure. Therefore, the line icing fault prediction has important significance.
At present, a line icing fault prediction method generally uses an artificial ice observation station to measure the icing thickness, namely, a simulated wire is built at the ice observation point, the icing thickness of the simulated wire is measured, and the icing thickness of an actual wire is calculated. The disadvantage of this method is the high construction and maintenance costs.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a line icing fault prediction method, a line icing fault prediction system, a storage medium and line icing fault prediction equipment, and aims to solve the technical problems that in the prior art, an artificial ice observation station is used for measuring the icing thickness and the construction and maintenance costs are high.
The first aspect of the present invention provides a line icing fault prediction method, which includes:
the method comprises the steps of collecting an icing data set related to the icing condition of the power transmission line, wherein the icing data set comprises historical meteorological data, current meteorological data, historical icing data, equipment information, overhaul information and fault information;
preprocessing the icing data set, and removing abnormal data;
constructing a meteorological icing model based on the historical meteorological data and the historical icing data;
inputting the current meteorological data into the meteorological icing model, and predicting an icing area;
based on the ice coating area and the equipment information, obtaining an ice coating line through calculation;
analyzing the historical icing data, the equipment information, the overhaul information and the fault information, calculating the characteristics of the line icing fault, and constructing a line icing fault model through the characteristics;
and acquiring various characteristics of the ice coating circuit, and inputting the characteristics into the circuit ice coating fault model to obtain the predicted fault condition of the ice coating circuit.
Compared with the prior art, the line icing fault prediction method in the embodiment has the beneficial effects that: the line icing fault prediction method provided by the invention can effectively predict the icing line fault condition, and concretely comprises the steps of collecting an icing data set related to the icing condition of the power transmission line, wherein the icing data set comprises historical meteorological data, current meteorological data, historical icing data, equipment information, overhaul information and fault information; preprocessing the icing data set, and removing abnormal data to ensure the prediction accuracy; constructing a meteorological icing model based on historical meteorological data and historical icing data; inputting current meteorological data into a meteorological icing model, and predicting an icing area; based on the icing area and the equipment information, an icing line is obtained through calculation, and is predicted through analysis of historical meteorological data and current meteorological data, and the icing line is positioned; analyzing historical icing data, equipment information, overhaul information and fault information, calculating the characteristics of line icing faults, and constructing a line icing fault model through the characteristics; each characteristic of the icing line is acquired, the characteristics are input into the line icing fault model, the predicted fault condition of the icing line is obtained, the historical icing data, equipment information and overhaul information are subjected to fault correlation characteristic extraction to construct the line icing fault model, the multi-dimensional refined icing line fault condition prediction is realized, the prediction accuracy is further improved, the cost is low, the line fault caused by icing is prevented, the safe, stable and economic operation of the power system is ensured, and the technical problems that the icing thickness is measured by using an artificial icing station and the construction and maintenance cost is high are solved.
According to an aspect of the above technical solution, the step of constructing a weather icing model based on the historical weather data and the historical icing data specifically includes:
based on the historical meteorological data and the historical icing data, constructing a functional relation between each meteorological type data and the icing thickness, wherein the historical meteorological data comprises a plurality of meteorological type data;
carrying out normalization processing on each meteorological type data, and constructing a meteorological icing model through each functional relation, wherein a calculation formula of the normalization processing is as follows:
wherein a is i For the ith weather type data, a max For the maximum value in the ith weather type data, a min Is the minimum value in the ith weather type data.
According to an aspect of the above technical solution, the step of obtaining the ice-covered line by calculation based on the ice-covered area and the device information specifically includes:
and obtaining an ice coating line and an ice coating tower through calculation based on the ice coating area and the longitude and latitude of the tower in the equipment information, wherein the calculation formula is as follows:
haver sin(θ)＝sin 2 (θ/2)
r is the radius of the earth and,
the latitude of the icing area and the tower is Δλ, which is the difference in longitude between the icing area and the tower.
According to an aspect of the above technical solution, analyzing the historical icing data, the equipment information, the overhaul information and the fault information, calculating characteristics of the line icing fault, and constructing a line icing fault model according to the characteristics, including:
analyzing the fault information, the historical icing data, the equipment information and the overhaul information respectively, and calculating the characteristics and the correlation of the line icing fault respectively, wherein the calculation formula of the correlation is as follows:
wherein X is fault information,
y is the mean value of the fault information, and Y is the characteristic of the fault information->
Is the mean of the features;
and constructing a line icing fault model through the features and the correlation of the features.
According to an aspect of the above technical solution, the step of constructing the line icing fault model by the features and the correlation of the features specifically includes:
acquiring a characteristic with correlation reaching a preset value, and constructing a line icing fault model according to the characteristic and the correlation of the characteristic;
and optimizing the line icing fault model through a particle swarm optimization algorithm.
According to an aspect of the foregoing technical solution, the method further includes:
the predicted fault condition is monitored in real time, and the accuracy rate and the regression rate of the predicted fault condition are calculated;
and calculating the accuracy of the line icing fault model prediction based on the precision rate and the regression rate.
According to an aspect of the above technical solution, the step of preprocessing the ice-covered data set and removing abnormal data specifically includes:
acquiring basic conditions of line icing, and comparing the icing data sets;
judging whether the icing data set meets basic conditions or not;
if yes, reserving the icing data set;
and if not, eliminating the icing data set.
The second aspect of the present invention provides a line icing fault prediction system, implemented by the method according to any one of the above technical solutions, where the system includes:
the data collection module is used for collecting an icing data set related to the icing condition of the power transmission line, wherein the icing data set comprises historical meteorological data, current meteorological data, historical icing data, equipment information, overhaul information and fault information;
the data preprocessing module is used for preprocessing the icing data set and removing abnormal data;
the weather icing model construction module is used for constructing a weather icing model based on the historical weather data and the historical icing data;
the ice-covering area prediction module is used for inputting the current meteorological data into the meteorological ice-covering model to predict an ice-covering area;
the ice coating line calculation module is used for calculating an ice coating line based on the ice coating area and the equipment information;
the line icing fault model construction module is used for analyzing the historical icing data, the equipment information, the overhaul information and the fault information, calculating the characteristics of line icing faults and constructing a line icing fault model through the characteristics;
and the predicted fault condition output module is used for acquiring various characteristics of the ice coating circuit, inputting the characteristics into the circuit ice coating fault model and obtaining the predicted fault condition of the ice coating circuit.
A third aspect of the present invention provides a computer readable storage medium having stored thereon computer instructions, which when executed by a processor, perform the steps of the method according to any of the above claims.
A fourth aspect of the present invention provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of the above technical solutions when said program is executed.
Drawings
The foregoing and/or additional aspects and advantages of the invention will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:
fig. 1 is a flow chart of a line icing fault prediction method according to a first embodiment of the present invention;
FIG. 2 is a block diagram of a line icing fault prediction system according to a second embodiment of the present invention;
description of the drawings element symbols:
the system comprises a data acquisition module 100, a data preprocessing module 200, a meteorological icing model construction module 300, an icing region prediction module 400, an icing line calculation module 500, a line icing fault model construction module 600 and a prediction fault condition output module 700.
Detailed Description
In order to make the objects, features and advantages of the present invention more comprehensible, embodiments accompanied with figures are described in detail below. Several embodiments of the invention are presented in the figures. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
It will be understood that when an element is referred to as being "mounted" on another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," "upper," "lower," and the like are used herein for descriptive purposes only and not to indicate or imply that the apparatus or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore should not be construed as limiting the invention.
In the present invention, unless explicitly stated and limited otherwise, the terms "mounted," "connected," "secured," and the like are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
Example 1
Referring to fig. 1, a first embodiment of the present invention provides a line icing fault prediction method, which includes steps S10-S16:
step S10, an icing data set related to the icing condition of the power transmission line is collected, wherein the icing data set comprises historical meteorological data, current meteorological data, historical icing data, equipment information, overhaul information and fault information;
in this embodiment, the data acquisition is coupled to the upstream system to acquire data and store the results on the big data platform HDFS for subsequent data processing. The upstream system has the functions of data vacancy warning, data quality auditing and the like, generates warning information when the data has quality problems, and displays the warning information on an interface; and starting an acquisition program through ETL scheduling, and storing the result on a big data platform HDFS (distributed file system) for subsequent data processing. After the data generation is completed, the upstream system writes a log of the completion of the standard data in a specified log table, and the acquisition process judges whether the data are in order or not through the data log provided by the upstream. If the data is not in good order, generating data and providing a log on time, and reminding an upstream system through the log. And the program enters a cyclic waiting process, and the data is automatically collected after the data are in full. And auditing the data quality, and if the data has quality problems, generating alarm information. The data flow links are few, and the speed is high.
Step S11, preprocessing the icing data set, and eliminating abnormal data;
the icing data set may have null values and abnormal data, so that preprocessing is required for the icing data set to ensure the accuracy of prediction, and an accurate data source is provided for icing analysis and line icing fault prediction.
Preprocessing the icing data set and removing abnormal data, wherein the method specifically comprises the following steps of:
acquiring basic conditions of line icing, and comparing the icing data sets; in the embodiment, the basic condition is that the surface temperature of the power transmission line is 2 ℃ or below, the relative humidity of the environment is 85% or above, and the wind speed of the environment is more than or equal to 1m/s.
Judging whether the icing data set meets basic conditions or not;
if yes, reserving the icing data set;
and if not, eliminating the icing data set.
And in addition, comparing the data in the icing data set with the situation of the ring ratio at the last moment and the situation of the same ratio at the same moment as yesterday, if the data exceeds the threshold value, recognizing that the data is abnormal, removing the icing data set, and removing the mutation value in the icing data set.
Step S12, constructing a meteorological icing model based on the historical meteorological data and the historical icing data;
based on the historical meteorological data and the historical icing data, constructing a functional relation between each meteorological type data and the icing thickness, wherein the historical meteorological data comprises a plurality of meteorological type data; for example, historical meteorological data includes temperature, humidity, altitude, and wind speed. And respectively constructing the functional relation between the meteorological type data of the temperature, the humidity, the altitude and the wind speed and the thickness of the ice coating.
Carrying out normalization processing on each meteorological type data, and constructing a meteorological icing model through each functional relation, wherein a calculation formula of the normalization processing is as follows:
wherein a is i For the ith weather type data, a max For the maximum value in the ith weather type data, a min Is the minimum value in the ith weather type data.
It should be noted that the difference of the value ranges of the different meteorological type data is relatively large, and in order to reduce the influence of dimensions on the meteorological icing model, normalization processing needs to be performed on the different meteorological type data.
In addition, through each function relation, various machine learning algorithms such as XGBOOST, decision trees and the like are respectively adopted to build a weather ice coating model, the effect of the weather ice coating model is verified, MAPE is adopted to conduct quantization, the effect of the weather ice coating model is accurately judged, and a chart is adopted to conduct visual display.
S13, inputting the current meteorological data into the meteorological icing model, and predicting an icing area;
step S14, based on the ice coating area and the equipment information, obtaining an ice coating line through calculation;
specifically, based on the icing area and the longitude and latitude of the tower in the equipment information, an icing line and the icing tower are obtained through calculation, wherein the calculation formula is as follows:
haver sin(θ)＝sin 2 (θ/2)
r is the radius of the earth and,
the latitude of the icing area and the tower is Δλ, which is the difference in longitude between the icing area and the tower.
Step S15, analyzing the historical icing data, the equipment information, the overhaul information and the fault information, calculating the characteristics of the line icing fault, and constructing a line icing fault model through the characteristics;
analyzing the fault information, the historical icing data, the equipment information and the overhaul information respectively, and calculating the characteristics and the correlation of the line icing fault respectively, wherein the calculation formula of the correlation is as follows:
wherein X is fault information,
y is the mean value of the fault information, and Y is the characteristic of the fault information->
Is the mean of the features;
and constructing a line icing fault model through the features and the correlation of the features.
Through the characteristics and the correlation of the characteristics, the step of constructing the line icing fault model specifically comprises the following steps:
acquiring a characteristic with correlation reaching a preset value, and constructing a line icing fault model according to the characteristic and the correlation of the characteristic; wherein the characteristics include operational years, ice coating thickness, and line length.
And optimizing the line icing fault model through a particle swarm optimization algorithm.
The particle swarm optimization algorithm is Particle Swarm Optimization PSO, and a set of a swarm intelligent algorithm and a machine learning algorithm can be realized to generate a PSO-RF algorithm. The method comprises the following specific steps:
initializing: initializing a particle group (n particles in total): each particle is given a random initial position and velocity. The position is a parameter of the random forest model, and the speed is a rate of change of the parameter.
Calculating an adaptation value: and calculating the model effect of each particle position according to the fitness function.
Calculating the optimal adaptation value of the individual: for each particle, the adaptation value of its current position is compared with the adaptation value corresponding to its historical best position (pbest), and if the adaptation value of the current position is higher, the historical best position is updated with the current position.
Solving the optimal adaptation value of the group: for each particle, comparing the model effect of its current position with an adaptation value corresponding to its global model optimal effect (gbest), and if the effect of the current position is higher, updating the global optimal position with the current position.
Particle position (model parameters) and velocity (model rate) are updated.
Judging whether the algorithm is ended: if the end condition is not met, returning to the step to calculate the adaptive value, and if the end condition is met, ending the algorithm, wherein the global optimal position (gbest) is the global optimal solution of the model parameters.
S16, acquiring various characteristics of the ice coating line, and inputting the characteristics into the line ice coating fault model to obtain a predicted fault condition of the ice coating line;
in addition, the method for predicting the line icing fault further comprises the following steps:
the predicted fault condition is monitored in real time, and the accuracy rate and the regression rate of the predicted fault condition are calculated;
and calculating the accuracy of the line icing fault model prediction based on the precision rate and the regression rate.
Compared with the prior art, the line icing fault prediction method provided by the invention has the beneficial effects that: the line icing fault prediction method provided by the invention can effectively predict the icing line fault condition, and concretely comprises the steps of collecting an icing data set related to the icing condition of the power transmission line, wherein the icing data set comprises historical meteorological data, current meteorological data, historical icing data, equipment information, overhaul information and fault information; preprocessing the icing data set, and removing abnormal data to ensure the prediction accuracy; constructing a meteorological icing model based on historical meteorological data and historical icing data; inputting current meteorological data into a meteorological icing model, and predicting an icing area; based on the icing area and the equipment information, an icing line is obtained through calculation, and is predicted through analysis of historical meteorological data and current meteorological data, and the icing line is positioned; analyzing historical icing data, equipment information, overhaul information and fault information, calculating the characteristics of line icing faults, and constructing a line icing fault model through the characteristics; each characteristic of the icing line is acquired, the characteristics are input into the line icing fault model, the predicted fault condition of the icing line is obtained, the historical icing data, equipment information and overhaul information are subjected to fault correlation characteristic extraction to construct the line icing fault model, the multi-dimensional refined icing line fault condition prediction is realized, the prediction accuracy is further improved, the cost is low, the line fault caused by icing is prevented, the safe, stable and economic operation of the power system is ensured, and the technical problems that the icing thickness is measured by using an artificial icing station and the construction and maintenance cost is high are solved.
Example two
Referring to fig. 2, a line icing fault prediction system according to a second embodiment of the present invention is shown, the system includes:
the data collection module is used for collecting an icing data set related to the icing condition of the power transmission line, wherein the icing data set comprises historical meteorological data, current meteorological data, historical icing data, equipment information, overhaul information and fault information;
in this embodiment, the data acquisition is coupled to the upstream system to acquire data and store the results on the big data platform HDFS for subsequent data processing. The upstream system has the functions of data vacancy warning, data quality auditing and the like, generates warning information when the data has quality problems, and displays the warning information on an interface; and starting an acquisition program through ETL scheduling, and storing the result on a big data platform HDFS (distributed file system) for subsequent data processing. After the data generation is completed, the upstream system writes a log of the completion of the standard data in a specified log table, and the acquisition process judges whether the data are in order or not through the data log provided by the upstream. If the data is not in good order, generating data and providing a log on time, and reminding an upstream system through the log. And the program enters a cyclic waiting process, and the data is automatically collected after the data are in full. And auditing the data quality, and if the data has quality problems, generating alarm information. The data flow links are few, and the speed is high.
The data preprocessing module is used for preprocessing the icing data set and removing abnormal data;
the icing data set may have null values and abnormal data, so that preprocessing is required for the icing data set to ensure the accuracy of prediction, and an accurate data source is provided for icing analysis and line icing fault prediction.
The method comprises the steps of obtaining basic conditions of line icing, and comparing the icing data sets; in the embodiment, the basic condition is that the surface temperature of the power transmission line is 2 ℃ or below, the relative humidity of the environment is 85% or above, and the wind speed of the environment is more than or equal to 1m/s.
Judging whether the icing data set meets basic conditions or not;
if yes, reserving the icing data set;
and if not, eliminating the icing data set.
And in addition, comparing the data in the icing data set with the situation of the ring ratio at the last moment and the situation of the same ratio at the same moment as yesterday, if the data exceeds the threshold value, recognizing that the data is abnormal, removing the icing data set, and removing the mutation value in the icing data set.
The weather icing model construction module is used for constructing a weather icing model based on the historical weather data and the historical icing data;
based on the historical meteorological data and the historical icing data, constructing a functional relation between each meteorological type data and the icing thickness, wherein the historical meteorological data comprises a plurality of meteorological type data; for example, historical meteorological data includes temperature, humidity, altitude, and wind speed. And respectively constructing the functional relation between the meteorological type data of the temperature, the humidity, the altitude and the wind speed and the thickness of the ice coating.
Carrying out normalization processing on each meteorological type data, and constructing a meteorological icing model through each functional relation, wherein a calculation formula of the normalization processing is as follows:
wherein a is i For the ith weather type data, a max For the maximum value in the ith weather type data, a min Is the minimum value in the ith weather type data.
It should be noted that the difference of the value ranges of the different meteorological type data is relatively large, and in order to reduce the influence of dimensions on the meteorological icing model, normalization processing needs to be performed on the different meteorological type data.
In addition, through each function relation, various machine learning algorithms such as XGBOOST, decision trees and the like are respectively adopted to build a weather ice coating model, the effect of the weather ice coating model is verified, MAPE is adopted to conduct quantization, the effect of the weather ice coating model is accurately judged, and a chart is adopted to conduct visual display.
The ice-covering area prediction module is used for inputting the current meteorological data into the meteorological ice-covering model to predict an ice-covering area;
the ice coating line calculation module is used for calculating an ice coating line based on the ice coating area and the equipment information;
specifically, based on the icing area and the longitude and latitude of the tower in the equipment information, an icing line and the icing tower are obtained through calculation, wherein the calculation formula is as follows:
haver sin(θ)＝sin 2 (θ/2)
r is the radius of the earth and,
the latitude of the icing area and the tower is Δλ, which is the difference in longitude between the icing area and the tower.
The line icing fault model construction module is used for analyzing the historical icing data, the equipment information, the overhaul information and the fault information, calculating the characteristics of line icing faults and constructing a line icing fault model through the characteristics;
analyzing the fault information, the historical icing data, the equipment information and the overhaul information respectively, and calculating the characteristics and the correlation of the line icing fault respectively, wherein the calculation formula of the correlation is as follows:
wherein X is fault information,
y is the mean value of the fault information, and Y is the characteristic of the fault information->
Is the mean of the features;
and constructing a line icing fault model through the features and the correlation of the features.
Through the characteristics and the correlation of the characteristics, the step of constructing the line icing fault model specifically comprises the following steps:
acquiring a characteristic with correlation reaching a preset value, and constructing a line icing fault model according to the characteristic and the correlation of the characteristic; wherein the characteristics include operational years, ice coating thickness, and line length.
And optimizing the line icing fault model through a particle swarm optimization algorithm.
And the predicted fault condition output module is used for acquiring various characteristics of the ice coating circuit, inputting the characteristics into the circuit ice coating fault model and obtaining the predicted fault condition of the ice coating circuit.
In addition, the system for predicting the line icing fault further comprises:
the predicted fault condition is monitored in real time, and the accuracy rate and the regression rate of the predicted fault condition are calculated;
and calculating the accuracy of the line icing fault model prediction based on the precision rate and the regression rate.
Compared with the prior art, the line icing fault prediction system provided by the invention has the beneficial effects that: the line icing fault prediction system provided by the invention can effectively predict the icing line fault condition, and concretely comprises a data collection module, a data analysis module and a data analysis module, wherein the data collection module is used for collecting an icing data set related to the icing condition of the power transmission line, and the icing data set comprises historical meteorological data, current meteorological data, historical icing data, equipment information, overhaul information and fault information; the data preprocessing module is used for preprocessing the icing data set, eliminating abnormal data, preprocessing the icing data set and eliminating the abnormal data so as to ensure the prediction accuracy; the weather icing model construction module is used for constructing a weather icing model based on historical weather data and historical icing data; the ice coating area prediction module is used for inputting current meteorological data into the meteorological ice coating model to predict an ice coating area; the ice coating line calculation module is used for calculating an ice coating line based on the ice coating area and the equipment information, predicting the ice coating line through analysis of historical meteorological data and current meteorological data, and positioning the ice coating line; the line icing fault model construction module is used for analyzing the historical icing data, the equipment information, the overhaul information and the fault information, calculating the characteristics of line icing faults and constructing a line icing fault model through the characteristics; the prediction fault condition output module is used for acquiring various characteristics of the icing line, inputting the characteristics into the line icing fault model to obtain the prediction fault condition of the icing line, extracting fault correlation characteristics of historical icing data, equipment information and overhaul information to construct the line icing fault model, realizing multidimensional and refined icing line fault condition prediction, further improving the prediction accuracy, having low cost, preventing line faults caused by icing, and ensuring safe, stable and economic operation of an electric power system, thereby solving the technical problems of high construction and maintenance cost caused by measuring the icing thickness by using an artificial icing observation station.
A third embodiment of the invention is directed to a computer readable storage medium having stored thereon computer instructions, which when executed by a processor, perform the steps of the method described in the above embodiments.
A fourth embodiment of the invention is directed to a computer device comprising a memory, a processor and a computer program stored on the memory and being executable on the processor, characterized in that the processor implements the steps of the method as described in the above embodiments when said program is executed.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing examples illustrate only a few embodiments of the invention, and are described in detail, but are not to be construed as limiting the scope of the invention. It should be noted that it is possible for those skilled in the art to make several variations and modifications without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (10)
1. A line icing fault prediction method, the method comprising:
the method comprises the steps of collecting an icing data set related to the icing condition of the power transmission line, wherein the icing data set comprises historical meteorological data, current meteorological data, historical icing data, equipment information, overhaul information and fault information;
preprocessing the icing data set, and removing abnormal data;
constructing a meteorological icing model based on the historical meteorological data and the historical icing data;
inputting the current meteorological data into the meteorological icing model, and predicting an icing area;
based on the ice coating area and the equipment information, obtaining an ice coating line through calculation;
analyzing the historical icing data, the equipment information, the overhaul information and the fault information, calculating the characteristics of the line icing fault, and constructing a line icing fault model through the characteristics;
and acquiring various characteristics of the ice coating circuit, and inputting the characteristics into the circuit ice coating fault model to obtain the predicted fault condition of the ice coating circuit.
2. The line icing fault prediction method according to claim 1, characterized in that the step of constructing a weather icing model based on the historical weather data and the historical icing data specifically comprises:
based on the historical meteorological data and the historical icing data, constructing a functional relation between each meteorological type data and the icing thickness, wherein the historical meteorological data comprises a plurality of meteorological type data;
carrying out normalization processing on each meteorological type data, and constructing a meteorological icing model through each functional relation, wherein a calculation formula of the normalization processing is as follows:
wherein a is i For the ith weather type data, a max For the maximum value in the ith weather type data, a min Is the minimum value in the ith weather type data.
3. The line icing fault prediction method according to claim 1, wherein the step of calculating an icing line based on the icing region and the equipment information specifically comprises:
and obtaining an ice coating line and an ice coating tower through calculation based on the ice coating area and the longitude and latitude of the tower in the equipment information, wherein the calculation formula is as follows:
haversin(θ)＝sin 2 (θ/2)
r is the radius of the earth and,
the latitude of the icing area and the tower is Δλ, which is the difference in longitude between the icing area and the tower.
4. The line icing fault prediction method according to claim 1, wherein the step of analyzing the historical icing data, the equipment information, the overhaul information and the fault information, calculating characteristics of line icing faults, and constructing a line icing fault model through the characteristics specifically comprises the steps of:
analyzing the fault information, the historical icing data, the equipment information and the overhaul information respectively, and calculating the characteristics and the correlation of the line icing fault respectively, wherein the calculation formula of the correlation is as follows:
wherein X is fault information,
y is the mean value of the fault information, and Y is the characteristic of the fault information->
Is the mean of the features;
and constructing a line icing fault model through the features and the correlation of the features.
5. The method for predicting line icing faults according to claim 4, wherein the step of constructing a line icing fault model by means of the features and the correlation of the features specifically comprises:
acquiring a characteristic with correlation reaching a preset value, and constructing a line icing fault model according to the characteristic and the correlation of the characteristic;
and optimizing the line icing fault model through a particle swarm optimization algorithm.
6. The line icing fault prediction method according to claim 1, characterized in that the method further comprises:
the predicted fault condition is monitored in real time, and the accuracy rate and the regression rate of the predicted fault condition are calculated;
and calculating the accuracy of the line icing fault model prediction based on the precision rate and the regression rate.
7. The line icing fault prediction method according to claim 1, wherein the step of preprocessing the icing data set and removing abnormal data specifically comprises:
acquiring basic conditions of line icing, and comparing the icing data sets;
judging whether the icing data set meets basic conditions or not;
if yes, reserving the icing data set;
and if not, eliminating the icing data set.
8. A line icing fault prediction system, implemented by the method of any of claims 1-7, comprising:
the data collection module is used for collecting an icing data set related to the icing condition of the power transmission line, wherein the icing data set comprises historical meteorological data, current meteorological data, historical icing data, equipment information, overhaul information and fault information;
the data preprocessing module is used for preprocessing the icing data set and removing abnormal data;
the weather icing model construction module is used for constructing a weather icing model based on the historical weather data and the historical icing data;
the ice-covering area prediction module is used for inputting the current meteorological data into the meteorological ice-covering model to predict an ice-covering area;
the ice coating line calculation module is used for calculating an ice coating line based on the ice coating area and the equipment information;
the line icing fault model construction module is used for analyzing the historical icing data, the equipment information, the overhaul information and the fault information, calculating the characteristics of line icing faults and constructing a line icing fault model through the characteristics;
and the predicted fault condition output module is used for acquiring various characteristics of the ice coating circuit, inputting the characteristics into the circuit ice coating fault model and obtaining the predicted fault condition of the ice coating circuit.
9. A computer readable storage medium having stored thereon computer instructions, which when executed by a processor, implement the steps of the method of any of claims 1-7.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1-7 when the program is executed.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117192312A (en) * | 2023-11-07 | 2023-12-08 | 云南电网有限责任公司 | Machine learning-based secondary alternating current cable insulation abnormality monitoring method and system |
| CN117494026A (en) * | 2023-12-28 | 2024-02-02 | 国网浙江省电力有限公司金华供电公司 | Method, system and storage medium for positioning icing fault of power transmission line under cold and tidal weather |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117192312A (en) * | 2023-11-07 | 2023-12-08 | 云南电网有限责任公司 | Machine learning-based secondary alternating current cable insulation abnormality monitoring method and system |
| CN117192312B (en) * | 2023-11-07 | 2024-04-19 | 云南电网有限责任公司 | Machine learning-based secondary alternating current cable insulation abnormality monitoring method and system |
| CN117494026A (en) * | 2023-12-28 | 2024-02-02 | 国网浙江省电力有限公司金华供电公司 | Method, system and storage medium for positioning icing fault of power transmission line under cold and tidal weather |
| CN117494026B (en) * | 2023-12-28 | 2024-04-05 | 国网浙江省电力有限公司金华供电公司 | Method, system and storage medium for positioning icing fault of power transmission line under cold and tidal weather |
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