CN114091344A - Power transmission line risk assessment model training method and device based on data coupling - Google Patents
Power transmission line risk assessment model training method and device based on data coupling Download PDFInfo
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Abstract
The invention discloses a power transmission line risk assessment model training method and system based on data coupling, wherein the method comprises the following steps: performing data coupling on the obtained electric transmission line safety risk electrical parameter index and the electric transmission line safety risk environment parameter index to generate electric transmission line safety risk assessment data; calculating a value of a transmission line safety risk assessment index based on the transmission line safety risk assessment data; generating a multi-dimensional thermodynamic image of the state of the power transmission line by using a kriging interpolation method based on the safety risk assessment data of the power transmission line; and training a power transmission line safety risk assessment model built based on a lightweight network MobileNet-V3 by taking the power transmission line state multi-dimensional thermal image as input and the value of the power transmission line safety risk assessment index as output according to preset parameters.
Description
Technical Field
The invention relates to the technical field of power system automation, in particular to a power transmission line risk assessment model training method and device based on data coupling.
Background
With the economic development and the scale enlargement of the power transmission network, a plurality of power transmission lines are positioned in areas with severe natural environments such as high altitude, heavy icing and the like, so that the safety monitoring of the power transmission lines is difficult and lagged, and the safety and the stability of the power transmission lines are seriously threatened, so that the safety and the stability evaluation method of the power transmission lines is urgently needed to be researched.
In the prior art, a series of icing identification methods are researched and developed, image identification, microclimate, sag and other methods are introduced, but the icing identification is only carried out on a single line, and only icing data of a single power transmission line is targeted, and environment and electrical data of the power transmission line are not integrated.
Disclosure of Invention
The invention aims to provide a power transmission line risk assessment model training method and device based on data coupling, and aims to solve the problems.
The invention provides a power transmission line risk assessment model training method based on data coupling, which comprises the following steps:
s1, performing data coupling on the obtained electric parameter index of the transmission line safety risk and the electric parameter index of the transmission line safety risk environment to generate transmission line safety risk assessment data;
s2, calculating a value of a safety risk evaluation index of the power transmission line based on the safety risk evaluation data of the power transmission line;
s3, generating a multi-dimensional thermodynamic image of the state of the power transmission line by using a kriging interpolation method based on the safety risk evaluation data of the power transmission line;
and S4, according to preset parameters, taking the multi-dimensional thermodynamic image of the power transmission line state as input, taking the value of the power transmission line safety risk assessment index as output, and training a power transmission line safety risk assessment model built on the basis of a lightweight network MobileNet-V3.
The invention provides a power transmission line risk assessment model training device based on data coupling, which comprises:
a data coupling module: the system comprises a data processing module, a data processing module and a data processing module, wherein the data processing module is used for performing data coupling on the electric transmission line safety risk electrical parameter index and the electric transmission line safety risk environment parameter index to generate electric transmission line safety risk assessment data;
an evaluation index calculation module: a value for calculating a transmission line safety risk assessment index based on the transmission line safety risk assessment data;
an image generation module: the system is used for generating a multi-dimensional thermodynamic image of the state of the power transmission line by using a kriging interpolation method based on the safety risk assessment data of the power transmission line;
a model training module: and the method is used for training the power transmission line safety risk assessment model built based on the lightweight network MobileNet-V3 by taking the power transmission line state multi-dimensional thermal image as input and the power transmission line safety risk assessment index as output according to preset parameters.
The embodiment of the invention also provides a power transmission line risk assessment model training device based on data coupling, which comprises: a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the above-described risk assessment model training method.
The embodiment of the invention also provides a computer-readable storage medium, wherein an implementation program for information transmission is stored on the computer-readable storage medium, and when the implementation program is executed by a processor, the steps of the risk assessment model training method are implemented.
By adopting the embodiment of the invention, the multi-dimensional thermal image of the power transmission line can be generated by integrating the environment and the electrical data of the power transmission line and integrating the environment and the electrical data of the power transmission line aiming at the areas with severe natural environments such as high altitude, heavy ice coating and the like, so that the safety risk of the power transmission line can be evaluated, the image can be identified by training the safety risk evaluation model of the power transmission line, the safety risk of the power transmission line can be rapidly evaluated, and the safe and stable operation of the power transmission line is ensured.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a power transmission line risk assessment model training method based on data coupling according to an embodiment of the present invention;
fig. 2 is a flowchart of a transmission line risk assessment method based on data coupling according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a training apparatus for a risk assessment model of a power transmission line based on data coupling according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a power transmission line risk assessment model training device based on data coupling according to an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations and positional relationships based on those shown in the drawings, and are used only for convenience of description and simplicity of description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise. Furthermore, the terms "mounted," "connected," and "connected" are to be construed broadly and may, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Method embodiment
According to an embodiment of the present invention, a method for training a risk assessment model of a power transmission line based on data coupling is provided, fig. 1 is a flowchart of the method for training the risk assessment model of the power transmission line based on data coupling according to the embodiment of the present invention, and as shown in fig. 1, the method for training the risk assessment model of the power transmission line based on data coupling according to the embodiment of the present invention specifically includes:
and S1, performing data coupling on the obtained electric parameter index of the transmission line safety risk and the electric parameter index of the transmission line safety risk environment to generate transmission line safety risk assessment data.
Specifically, the method for obtaining the safety risk electrical parameter index of the power transmission line specifically comprises the following steps:
setting the active output of a generator, the generator terminal voltage and the load active power variation range, generating a large number of samples in the variation range by using a Monte Carlo sampling method, and building a power grid actual simulation model; carrying out load flow simulation calculation on the generated sample data to obtain electric parameter indexes of the safety risk of the power transmission line, wherein the electric parameter indexes specifically comprise the average voltage of the power transmission line and the load flow of the line;
the change range of the active output of the generator is 50-150%, the change range of the voltage per unit value at the generator end is 0.8-1.1, and the change range of the load active power is 50-150%.
The method for obtaining the environmental parameter indexes of the transmission line safety risk comprises the following steps:
determining the annual maximum and minimum temperatures of all the power transmission line surrounding environments in the system, randomly generating a large number of temperature scenes in the determined maximum and minimum temperature ranges based on a Monte Carlo sampling method, simulating various climate conditions which may occur in a preset time period, generating a large number of samples of the ambient temperature of the power transmission line and the ice on the line, and forming a power transmission line safety risk environment parameter index.
In the embodiment, the tension sensor data is used as the representation of the line icing, and based on the actually measured tension data, the difference value sampling is performed by adopting a Monte Carlo sampling method based on the existing data, so that all possible tension scenes are generated, and the newly generated data is more representative.
And the obtained electric parameter indexes of the transmission line safety risk and the electric parameter indexes of the transmission line safety risk environment jointly form transmission line safety risk assessment data.
And S2, calculating the value of the power transmission line safety risk evaluation index based on the power transmission line safety risk evaluation data.
Specifically, based on the electrical and environmental parameters, the safety risk degree of the system is evaluated, wherein the voltage is represented by a deviation percentage from the reference voltage and converted into a fraction of full 100 points, as shown in formula 1:
Vscore＝score(abs(Vi-V0) Equation 1);
wherein, VscoreScoring the average voltage of the line; score is a fractional transfer function; abs is an absolute value function; viIs the average voltage of line i; v0Is the reference voltage.
The line load rate score calculation formula is shown in formula 2:
wherein L isscoreScoring the line load rate; l isiIs the current load of line i; l isi0Is the maximum load of line i.
The safety risk score calculation method of the ambient temperature around the line in the invention is shown as a formula 3:
Tscore＝score(ηiTi) Formula 3;
wherein, TscoreIs based onA safety risk score for ambient temperature; t isiIs the temperature around line i; etaiThe constants were predicted for icing thickness at different temperatures.
The line safety risk index obtained based on the tension sensor is shown in formula 4:
wherein, IscoreCalculating a line safety risk score based on the tension sensor data; i isiMeasuring values of a tension sensor of the power transmission line i; i isi0Is the tension limit of the line i.
Establishing a judgment matrix of the electric transmission line safety risk electrical parameters and the electric transmission line safety risk environmental parameters, and carrying out normalization processing; evaluating the entropy of each power transmission line safety risk evaluation index based on an entropy weight method, defining an entropy weight, and calculating to obtain the weight value of each power transmission line safety risk evaluation index as the weight of each power transmission line safety risk evaluation index in a power transmission line risk evaluation model after training is finished;
after the weight of each power transmission line safety risk assessment index is obtained through calculation, the value of the line safety risk assessment index under the multi-dimensional data is calculated based on the weight, and the comprehensive assessment result of the power transmission line safety risk is shown as a formula 5:
S＝wVVscore+wLLscore+wTTscore+wIIscoreequation 5;
wherein S is the comprehensive risk assessment result of the power transmission line, wV，wL，wTAnd wIThe distribution is the weight of the voltage, load rate, temperature and tension parameters calculated by an entropy weight method.
And S3, generating a multi-dimensional thermodynamic image of the state of the power transmission line by using a kriging interpolation method based on the safety risk evaluation data of the power transmission line.
Specifically, in the power system, the thermodynamic diagram can be combined with the electric information and the environmental information of the power transmission line to generate a plurality of power transmission line state thermodynamic images containing geographic information under the same time section, and simultaneously, the images contain multidimensional characteristic information of all the power transmission lines under the current section. In this embodiment, a kriging interpolation method is used to interpolate the node voltage of the test system to obtain voltage values of all the points in the area, and a line average voltage, a line load rate, a line ambient temperature around the line, and a line icing thermal image including geographic information are generated, in the image, the redder color represents that the voltage is higher, the yellow color represents that the voltage is at a medium level, and the green color represents that the voltage is a low-voltage area, which indicates that there is a safety risk.
And S4, according to preset parameters, taking the multi-dimensional thermodynamic image of the power transmission line state as input, taking the value of the power transmission line safety risk assessment index as output, and training a power transmission line safety risk assessment model built on the basis of a lightweight network MobileNet-V3.
Specifically, the preset parameters during training of the MobileNet-V3 model are specifically set as follows: the model type is small, the number of model layers is 16, the initial learning rate is 0.0001, the number of iterations is 200, the number of training samples in each batch is 20, the optimizer is an Adam optimizer, and the loss function selects a mean square error loss function.
Fig. 2 is a flowchart of the power transmission line risk assessment method based on data coupling according to the embodiment of the present invention, and as shown in fig. 2, in practical applications, real-time power transmission line electrical appliance and environment monitoring data including power transmission line average voltage, line load rate, line ambient temperature and tension data are obtained, and after the data are converted into thermal images, the thermal images are evaluated by a power transmission line safety risk assessment system built based on a MobileNet-V3 model, so as to obtain a power transmission line safety risk assessment result.
By adopting the embodiment of the invention, the multi-dimensional thermal image of the power transmission line can be generated by integrating the environment and the electrical data of the power transmission line and integrating the environment and the electrical data of the power transmission line aiming at the areas with severe natural environments such as high altitude, heavy ice coating and the like, so that the safety risk of the power transmission line can be evaluated, the image can be identified by training a safety risk evaluation model of the power transmission line, the safety risk of the power transmission line can be rapidly evaluated, and the safe and stable operation of the power transmission line is ensured; the method is simple to use, high in feasibility and high in evaluation precision.
Apparatus embodiment one
According to an embodiment of the present invention, a data coupling-based power transmission line risk assessment model training device is provided, fig. 3 is a schematic diagram of the data coupling-based power transmission line risk assessment model training device according to the embodiment of the present invention, as shown in fig. 3, the data coupling-based power transmission line risk assessment model training device according to the embodiment of the present invention specifically includes:
the data coupling module 30: and the data coupling module is used for performing data coupling on the electric transmission line safety risk parameter index and the electric transmission line safety risk environment parameter index to generate electric transmission line safety risk assessment data.
The evaluation index calculation module 32: and the method is used for calculating the value of the transmission line safety risk assessment index based on the transmission line safety risk assessment data.
The evaluation index calculation module 32 is specifically configured to:
establishing a judgment matrix of the electric transmission line safety risk electrical parameters and the electric transmission line safety risk environmental parameters, and carrying out normalization processing;
calculating the weight value of each power transmission line safety risk assessment index based on an entropy weight method, and taking the weight value as the weight of each power transmission line safety risk assessment index in the power transmission line risk assessment model after training is finished;
and calculating a line safety risk assessment index under the multidimensional data based on the weight.
The image generation module 34: and generating a multi-dimensional thermodynamic image of the state of the power transmission line by using a kriging interpolation method based on the safety risk assessment data of the power transmission line.
Model training module 36: and the method is used for training the power transmission line safety risk assessment model built based on the lightweight network MobileNet-V3 by taking the power transmission line state multi-dimensional thermal image as input and the power transmission line safety risk assessment index as output according to preset parameters.
The power transmission line risk assessment model training device based on data coupling further comprises an index acquisition module, specifically an electrical parameter index acquisition module and an environmental parameter index acquisition module, wherein the index acquisition module is used for acquiring an electrical parameter index and an environmental parameter index and sending the electrical parameter index and the environmental parameter index to the data coupling module;
the electrical parameter index acquisition module is specifically used for:
based on a Monte Carlo sampling method, generating a large number of samples in the change range of the set generator active output, generator terminal voltage and load active power, and carrying out power flow simulation calculation on the samples to obtain the safety risk electrical parameter index of the power transmission line;
the environmental parameter index acquisition module is specifically configured to:
based on a Monte Carlo sampling method, a large number of air temperature scenes are randomly generated in the highest and lowest air temperature ranges of all the annual surrounding environments of all the power transmission lines, various weather conditions which may occur in a preset time period are simulated, a large number of samples of the ambient temperature of the power transmission lines and the ice on the lines are generated, and the safety risk environment parameter indexes of the power transmission lines are obtained.
The embodiment of the present invention is a system embodiment corresponding to the above method embodiment, and specific operations of each module may be understood with reference to the description of the method embodiment, which is not described herein again.
Device embodiment II
The embodiment of the invention provides a power transmission line risk assessment model training device based on data coupling, as shown in fig. 4, comprising: a memory 40, a processor 42 and a computer program stored on the memory 40 and executable on the processor 42, which computer program, when executed by the processor 42, carries out the following method steps:
and S1, performing data coupling on the obtained electric parameter index of the transmission line safety risk and the electric parameter index of the transmission line safety risk environment to generate transmission line safety risk assessment data.
Specifically, the method comprises the following steps:
setting the active output of a generator, the generator terminal voltage and the load active power variation range, generating a large number of samples in the variation range by using a Monte Carlo sampling method, and building a power grid actual simulation model; carrying out load flow simulation calculation on the generated sample data to obtain electric parameter indexes of the safety risk of the power transmission line, wherein the electric parameter indexes specifically comprise the average voltage of the power transmission line and the load flow of the line;
the change range of the active output of the generator is 50-150%, the change range of the voltage per unit value at the generator end is 0.8-1.1, and the change range of the load active power is 50-150%.
Based on a Monte Carlo sampling method, a large number of air temperature scenes are randomly generated in the determined highest and lowest air temperature ranges, various weather conditions which may occur in a preset time period are simulated, a large number of samples of the ambient temperature of the power transmission line and the ice on the power transmission line are generated, and the parameter indexes of the safety risk environment of the power transmission line are formed.
And the obtained electric parameter indexes of the transmission line safety risk and the electric parameter indexes of the transmission line safety risk environment jointly form transmission line safety risk assessment data.
And S2, calculating the value of the power transmission line safety risk evaluation index based on the power transmission line safety risk evaluation data.
Specifically, based on the electrical and environmental parameters, the safety risk degree of the system is evaluated, wherein the voltage is represented by a deviation percentage from the reference voltage and converted into a fraction of full 100 points, as shown in formula 1:
Vscore＝score(abs(Vi-V0) Equation 1);
wherein, VscoreScoring the average voltage of the line; score is a fractional transfer function; abs is an absolute value function; viIs the average voltage of line i; v0Is the reference voltage.
The line load rate score calculation formula is shown in formula 2:
wherein L isscoreScoring the line load rate; l isiIs the current load of line i; l isi0Is the maximum load of line i.
The safety risk score calculation method of the ambient temperature around the line in the invention is shown as a formula 3:
Tscore＝score(ηiTi) Formula 3;
wherein, TscoreA security risk score based on ambient temperature; t isiIs the temperature around line i; etaiThe constants were predicted for icing thickness at different temperatures.
The line safety risk index obtained based on the tension sensor is shown in formula 4:
wherein, IscoreCalculating a line safety risk score based on the tension sensor data; i isiMeasuring values of a tension sensor of the power transmission line i; i isi0Is the tension limit of the line i.
Establishing a judgment matrix of the electric transmission line safety risk electrical parameters and the electric transmission line safety risk environmental parameters, and carrying out normalization processing; evaluating the entropy of each power transmission line safety risk evaluation index based on an entropy weight method, defining an entropy weight, and calculating to obtain the weight value of each power transmission line safety risk evaluation index as the weight of each power transmission line safety risk evaluation index in a power transmission line risk evaluation model after training is finished;
after the weight of each power transmission line safety risk assessment index is obtained through calculation, the value of the line safety risk assessment index under the multi-dimensional data is calculated based on the weight, and the comprehensive assessment result of the power transmission line safety risk is shown as a formula 5:
S＝wVVscore+wLLscore+wTTscore+wIIscoreequation 5;
wherein S is the comprehensive risk assessment result of the power transmission line, wV，wL，wTAnd wIThe distribution is the weight of the voltage, load rate, temperature and tension parameters calculated by an entropy weight method.
And S3, generating a multi-dimensional thermodynamic image of the state of the power transmission line by using a kriging interpolation method based on the safety risk evaluation data of the power transmission line.
Specifically, a kriging interpolation method is used for interpolating node voltages of the test system to obtain voltage values of all points in the area, a line average voltage, a line load rate, a line surrounding environment temperature and a line icing thermal image containing geographic information are generated, and an area with a green color is an area with a low voltage, which indicates that safety risks possibly exist.
And S4, according to preset parameters, taking the multi-dimensional thermodynamic image of the power transmission line state as input, taking the value of the power transmission line safety risk assessment index as output, and training a power transmission line safety risk assessment model built on the basis of a lightweight network MobileNet-V3.
Device embodiment III
The embodiment of the present invention provides a computer-readable storage medium, on which an implementation program for information transmission is stored, and when being executed by a processor 42, the implementation program implements the following method steps:
and S1, performing data coupling on the obtained electric parameter index of the transmission line safety risk and the electric parameter index of the transmission line safety risk environment to generate transmission line safety risk assessment data.
Specifically, the method comprises the following steps:
setting the active output of a generator, the generator terminal voltage and the load active power variation range, generating a large number of samples in the variation range by using a Monte Carlo sampling method, and building a power grid actual simulation model; carrying out load flow simulation calculation on the generated sample data to obtain electric parameter indexes of the safety risk of the power transmission line, wherein the electric parameter indexes specifically comprise the average voltage of the power transmission line and the load flow of the line;
the change range of the active output of the generator is 50-150%, the change range of the voltage per unit value at the generator end is 0.8-1.1, and the change range of the load active power is 50-150%.
Based on a Monte Carlo sampling method, a large number of air temperature scenes are randomly generated in the determined highest and lowest air temperature ranges, various weather conditions which may occur in a preset time period are simulated, a large number of samples of the ambient temperature of the power transmission line and the ice on the power transmission line are generated, and the parameter indexes of the safety risk environment of the power transmission line are formed.
And the obtained electric parameter indexes of the transmission line safety risk and the electric parameter indexes of the transmission line safety risk environment jointly form transmission line safety risk assessment data.
And S2, calculating the value of the power transmission line safety risk evaluation index based on the power transmission line safety risk evaluation data.
Specifically, based on the electrical and environmental parameters, the safety risk degree of the system is evaluated, wherein the voltage is represented by a deviation percentage from the reference voltage and converted into a fraction of full 100 points, as shown in formula 1:
Vscore＝score(abs(Vi-V0) Equation 1);
wherein, VscoreScoring the average voltage of the line; score is a fractional transfer function; abs is an absolute value function; viIs the average voltage of line i; v0Is the reference voltage.
The line load rate score calculation formula is shown in formula 2:
wherein L isscoreScoring the line load rate; l isiIs the current load of line i; l isi0Is the maximum load of line i.
The safety risk score calculation method of the ambient temperature around the line in the invention is shown as a formula 3:
Tscore＝score(ηiTi) Formula 3;
wherein, TscoreA security risk score based on ambient temperature; t isiIs the temperature around line i; etaiThe constants were predicted for icing thickness at different temperatures.
The line safety risk index obtained based on the tension sensor is shown in formula 4:
wherein, IscoreCalculating a line safety risk score based on the tension sensor data; i isiMeasuring values of a tension sensor of the power transmission line i; i isi0Is the tension limit of the line i.
Establishing a judgment matrix of the electric transmission line safety risk electrical parameters and the electric transmission line safety risk environmental parameters, and carrying out normalization processing; evaluating the entropy of each power transmission line safety risk evaluation index based on an entropy weight method, defining an entropy weight, and calculating to obtain the weight value of each power transmission line safety risk evaluation index as the weight of each power transmission line safety risk evaluation index in a power transmission line risk evaluation model after training is finished;
after the weight of each power transmission line safety risk assessment index is obtained through calculation, the value of the line safety risk assessment index under the multi-dimensional data is calculated based on the weight, and the comprehensive assessment result of the power transmission line safety risk is shown as a formula 5:
S＝wVVscore+wLLscore+wTTscore+wIIscoreequation 5;
wherein S is the comprehensive risk assessment result of the power transmission line, wV，wL，wTAnd wIThe distribution is the weight of the voltage, load rate, temperature and tension parameters calculated by an entropy weight method.
And S3, generating a multi-dimensional thermodynamic image of the state of the power transmission line by using a kriging interpolation method based on the safety risk evaluation data of the power transmission line.
Specifically, a kriging interpolation method is used for interpolating node voltages of the test system to obtain voltage values of all points in the area, a line average voltage, a line load rate, a line surrounding environment temperature and a line icing thermal image containing geographic information are generated, and an area with a green color is an area with a low voltage, which indicates that safety risks possibly exist.
And S4, according to preset parameters, taking the multi-dimensional thermodynamic image of the power transmission line state as input, taking the value of the power transmission line safety risk assessment index as output, and training a power transmission line safety risk assessment model built on the basis of a lightweight network MobileNet-V3.
The computer-readable storage medium of this embodiment includes, but is not limited to: ROM, RAM, magnetic or optical disks, and the like.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A power transmission line risk assessment model training method based on data coupling is characterized by comprising the following steps:
s1, performing data coupling on the obtained electric parameter index of the transmission line safety risk and the electric parameter index of the transmission line safety risk environment to generate transmission line safety risk assessment data;
s2, calculating a value of a safety risk evaluation index of the power transmission line based on the safety risk evaluation data of the power transmission line;
s3, generating a multi-dimensional thermodynamic image of the state of the power transmission line by using a kriging interpolation method based on the safety risk evaluation data of the power transmission line;
and S4, according to preset parameters, taking the multi-dimensional thermodynamic image of the power transmission line state as input, taking the value of the power transmission line safety risk assessment index as output, and training a power transmission line safety risk assessment model built on the basis of a lightweight network MobileNet-V3.
2. The method of claim 1,
the method for obtaining the electric parameter index of the transmission line safety risk of S1 comprises the following steps:
setting the active output of a generator, the variation range of generator terminal voltage and load active power, generating a large number of samples in the variation range by using a Monte Carlo sampling method, and carrying out power flow simulation calculation on the samples to obtain the safety risk electrical parameter indexes of the power transmission line, wherein the safety risk electrical parameter indexes of the power transmission line comprise the average voltage of the power transmission line and the power flow of the line;
the method for obtaining the transmission line safety risk environment parameter index of S1 comprises the following steps:
determining the annual maximum and minimum temperatures of all the power transmission line surrounding environments in the system, randomly generating a large number of temperature scenes in the maximum and minimum temperature ranges based on a Monte Carlo sampling method, simulating various climate conditions which may occur in a preset time period, generating a large number of samples of the ambient temperature of the power transmission line and the ice on the line, and forming a power transmission line safety risk environment parameter index.
3. The method according to claim 1, wherein S2 specifically comprises:
establishing a judgment matrix of the electric transmission line safety risk electrical parameters and the electric transmission line safety risk environmental parameters, and carrying out normalization processing;
calculating the weight value of each power transmission line safety risk assessment index based on an entropy weight method, and taking the weight value as the weight of each power transmission line safety risk assessment index in the power transmission line risk assessment model after training is finished;
and calculating a line safety risk assessment index under the multidimensional data based on the weight.
4. The method of claim 1, wherein the multidimensional thermal image of the power transmission line state at S3 is a thermal image of average voltage of the line, load rate of the line, ambient temperature around the line, and ice coating on the line, which contains geographical information.
5. The method according to claim 1, wherein the preset parameters of S4 specifically include: the model type is small, the number of model layers is 16, the initial learning rate is 0.0001, the iteration number is 200, the number of training samples in each batch is 20, the optimizer is an Adam optimizer, and the loss function selects a mean square error loss function.
6. The utility model provides a transmission line risk assessment model training device based on data coupling which characterized in that includes:
a data coupling module: the system comprises a data processing module, a data processing module and a data processing module, wherein the data processing module is used for performing data coupling on the electric transmission line safety risk electrical parameter index and the electric transmission line safety risk environment parameter index to generate electric transmission line safety risk assessment data;
an evaluation index calculation module: a value for calculating a transmission line safety risk assessment index based on the transmission line safety risk assessment data;
an image generation module: the system is used for generating a multi-dimensional thermodynamic image of the state of the power transmission line by using a kriging interpolation method based on the safety risk assessment data of the power transmission line;
a model training module: and the method is used for training the power transmission line safety risk assessment model built based on the lightweight network MobileNet-V3 by taking the power transmission line state multi-dimensional thermal image as input and the power transmission line safety risk assessment index as output according to preset parameters.
7. The device according to claim 6, further comprising an index acquisition module, in particular an electrical parameter index acquisition module and an environmental parameter index acquisition module,
the electrical parameter index acquisition module is specifically configured to:
based on a Monte Carlo sampling method, generating a large number of samples in the change range of the set generator active output, generator terminal voltage and load active power, and carrying out power flow simulation calculation on the samples to obtain the safety risk electrical parameter index of the power transmission line;
the environment parameter index acquisition module is specifically configured to:
based on a Monte Carlo sampling method, a large number of air temperature scenes are randomly generated in the highest and lowest air temperature ranges of all the annual surrounding environments of all the power transmission lines, various weather conditions which may occur in a preset time period are simulated, a large number of samples of the ambient temperature of the power transmission lines and the ice on the lines are generated, and the safety risk environment parameter indexes of the power transmission lines are obtained.
8. The apparatus according to claim 6, wherein the evaluation index calculation module is specifically configured to:
establishing a judgment matrix of the electric transmission line safety risk electrical parameters and the electric transmission line safety risk environmental parameters, and carrying out normalization processing;
calculating the weight value of each power transmission line safety risk assessment index based on an entropy weight method, and taking the weight value as the weight of each power transmission line safety risk assessment index in the power transmission line risk assessment model after training is finished;
and calculating a line safety risk assessment index under the multidimensional data based on the weight.
9. The utility model provides a transmission line risk assessment model training equipment based on data coupling which characterized in that includes: memory, a processor and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the risk assessment model training method according to any one of claims 1 to 5.
10. A computer-readable storage medium, on which an information transfer implementing program is stored, which, when executed by a processor, implements the steps of the risk assessment model training method according to any one of claims 1 to 5.
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| CN116362631B (en) * | 2023-06-02 | 2023-08-11 | 国网安徽省电力有限公司经济技术研究院 | DC power distribution network operation safety evaluation system based on big data |
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