CN117034772A - Current-carrying unbalance degree determining method and device and computer equipment - Google Patents
Current-carrying unbalance degree determining method and device and computer equipment Download PDFInfo
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Abstract
The application relates to a current-carrying unbalance degree determining method, a device, a computer device and a storage medium. The method comprises the following steps: acquiring a plurality of influence factors influencing the current-carrying unbalance degree in a cable line and influence factor data corresponding to each influence factor, and establishing a simulation model of the cable line based on each influence factor; based on a simulation model, respectively identifying the influence degree of each influence factor on the current-carrying unbalance degree through a control variable strategy, and calculating the weight value of each influence factor based on the influence degree of each influence factor on the current-carrying unbalance degree; and adjusting weight parameters of all influence factors in the initial current-carrying unbalance degree determination network based on the weight values of all influence factors to obtain a current-carrying unbalance degree determination network, and calculating the target current-carrying unbalance degree of the cable line based on the data of all influence factors and the current-carrying unbalance degree determination network. By adopting the method, the accuracy of the calculated current-carrying unbalance degree can be improved.
Description
Technical Field
The present application relates to the field of power cable technologies, and in particular, to a method, an apparatus, and a computer device for determining current-carrying unbalance.
Background
With the rapid increase of urban electricity load demands, in order to reduce equipment cost and be limited by technical conditions, power supply modes adopting in-phase parallel cables are also increasingly increased, so that land is saved, and the power transmission capacity is improved. However, the in-phase parallel cable is complex in structure, electromagnetic coupling among different cables is enhanced, a plurality of new problems are brought to safe operation of the cable, and various problems of safe operation of the cable can be identified by researching the current-carrying unbalance degree of the cable, so that the research on the current-carrying unbalance degree of the parallel cable has profound significance.
The traditional mode of recognizing the current-carrying unbalance degree is to firstly establish a simulation model of the current-carrying unbalance degree by adopting a simulation software calculation method, and then to simulate and analyze the result and the change rule of the current-carrying unbalance of the cable under the action of a single factor.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a current-carrying unbalance degree determination method, apparatus, computer device, computer-readable storage medium, and computer program product.
In a first aspect, the present application provides a method of determining a current carrying imbalance. The method comprises the following steps:
acquiring a plurality of influence factors influencing the current-carrying unbalance degree in a cable line and influence factor data corresponding to each influence factor, and establishing a simulation model of the cable line based on each influence factor;
based on the simulation model, respectively identifying the influence degree of each influence factor on the current-carrying unbalance degree through a control variable strategy, and calculating the weight value of each influence factor based on the influence degree of each influence factor on the current-carrying unbalance degree;
and adjusting weight parameters of all influence factors in an initial current-carrying unbalance degree determination network based on the weight values of all influence factors to obtain a current-carrying unbalance degree determination network, and calculating the target current-carrying unbalance degree of the cable line based on all influence factor data and the current-carrying unbalance degree determination network.
Optionally, after the simulation model of the cable line is built based on each influence factor, the method further includes:
collecting a plurality of influence factor data corresponding to each influence factor, and carrying out permutation and combination based on the plurality of influence factor data corresponding to each influence factor to obtain data sets containing the influence factor data corresponding to each influence factor;
And constructing a data matrix corresponding to each influence factor based on each data set.
Optionally, based on the simulation model, the identifying, by controlling a variable policy, the influence degree of each influence factor on the current-carrying unbalance includes:
inputting each data group in the data matrix into the simulation model respectively, and carrying out simulation current transmission processing on the simulation model to obtain the current carrying unbalance degree corresponding to each data group;
dividing each data set into data sets with only single influencing factor data variables, obtaining data sets corresponding to each influencing factor, and analyzing the influence degree of the influencing factors corresponding to each data set on the current carrying unbalance degree based on the current carrying unbalance degree corresponding to each data set contained in each data set.
Optionally, each data set in the data matrix is respectively input into the simulation model, and simulation current transmission processing is performed on the simulation model to obtain a current carrying unbalance degree corresponding to each data set, which includes:
based on each data group in the data matrix, respectively carrying out simulation current transmission processing on the simulation model, wherein each data group corresponds to current carrying information;
And calculating the current carrying unbalance of each piece of current carrying information through a current carrying unbalance algorithm to obtain the current carrying unbalance corresponding to each data set.
Optionally, the analyzing the degree of influence of the influence factor corresponding to each data set on the degree of current carrying unbalance based on the degree of current carrying unbalance corresponding to each data set included in each data set includes:
identifying the current carrying unbalance degree corresponding to each influence factor data of the influence factors of each data set based on the current carrying unbalance degree corresponding to each data set contained in each data set;
for each influence factor, calculating a data difference value between the influence factor data and an imbalance degree difference value between current carrying imbalance degrees corresponding to the influence factor data, and determining an association relation between a data variable of the influence factor and an imbalance degree variable of the current carrying imbalance degree based on the data difference values and the imbalance degree difference values corresponding to the data difference values;
and determining the influence degree of the influence factors on the current carrying unbalance based on the association relation between the data variable of the influence factors and the unbalance variable of the current carrying unbalance.
Optionally, the calculating the weight value of each influencing factor based on the influence degree of each influencing factor on the current carrying unbalance comprises:
for each influencing factor, calculating an unbalance difference value corresponding to a unit data difference value of the influencing factor based on each data difference value of the influencing factor and the unbalance difference value corresponding to each data difference value;
and carrying out normalization processing on the unbalance difference value corresponding to the unit data difference value of each influence factor to obtain the weight value of each influence factor.
In a second aspect, the present application also provides a device for determining a current-carrying unbalance degree. The device comprises:
the acquisition module is used for acquiring a plurality of influence factors influencing the current-carrying unbalance degree in the cable line and influence factor data corresponding to each influence factor, and establishing a simulation model of the cable line based on each influence factor;
the first calculation module is used for respectively identifying the influence degree of each influence factor on the current-carrying unbalance degree through a control variable strategy based on the simulation model, and calculating the weight value of each influence factor based on the influence degree of each influence factor on the current-carrying unbalance degree;
The second calculation module is used for adjusting weight parameters of all influence factors in the initial current-carrying unbalance degree determination network based on the weight values of all influence factors to obtain a current-carrying unbalance degree determination network, and calculating the target current-carrying unbalance degree of the cable line based on all influence factor data and the current-carrying unbalance degree determination network.
Optionally, the apparatus further includes:
the acquisition module is used for acquiring a plurality of influence factor data corresponding to each influence factor, and carrying out permutation and combination based on the plurality of influence factor data corresponding to each influence factor to obtain a data set containing the influence factor data corresponding to each influence factor;
the construction module is used for constructing a data matrix corresponding to each influence factor based on each data set.
Optionally, the first computing module is specifically configured to:
inputting each data group in the data matrix into the simulation model respectively, and carrying out simulation current transmission processing on the simulation model to obtain the current carrying unbalance degree corresponding to each data group;
dividing each data set into data sets with only single influencing factor data variables, obtaining data sets corresponding to each influencing factor, and analyzing the influence degree of the influencing factors corresponding to each data set on the current carrying unbalance degree based on the current carrying unbalance degree corresponding to each data set contained in each data set.
Optionally, the first computing module is specifically configured to:
based on each data group in the data matrix, respectively carrying out simulation current transmission processing on the simulation model, wherein each data group corresponds to current carrying information;
and calculating the current carrying unbalance of each piece of current carrying information through a current carrying unbalance algorithm to obtain the current carrying unbalance corresponding to each data set.
Optionally, the first computing module is specifically configured to:
identifying the current carrying unbalance degree corresponding to each influence factor data of the influence factors of each data set based on the current carrying unbalance degree corresponding to each data set contained in each data set;
for each influence factor, calculating a data difference value between the influence factor data and an imbalance degree difference value between current carrying imbalance degrees corresponding to the influence factor data, and determining an association relation between a data variable of the influence factor and an imbalance degree variable of the current carrying imbalance degree based on the data difference values and the imbalance degree difference values corresponding to the data difference values;
and determining the influence degree of the influence factors on the current carrying unbalance based on the association relation between the data variable of the influence factors and the unbalance variable of the current carrying unbalance.
Optionally, the first computing module is specifically configured to:
for each influencing factor, calculating an unbalance difference value corresponding to a unit data difference value of the influencing factor based on each data difference value of the influencing factor and the unbalance difference value corresponding to each data difference value;
and carrying out normalization processing on the unbalance difference value corresponding to the unit data difference value of each influence factor to obtain the weight value of each influence factor.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the steps of the method of any of the first aspects when the processor executes the computer program.
In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method of any of the first aspects.
In a fifth aspect, the present application also provides a computer program product. The computer program product comprising a computer program which, when executed by a processor, implements the steps of the method of any of the first aspects.
According to the method, the device and the computer equipment for determining the current carrying unbalance, the simulation model of the cable line is built based on a plurality of influence factors influencing the current carrying unbalance in the cable line and influence factor data corresponding to each influence factor; based on the simulation model, respectively identifying the influence degree of each influence factor on the current-carrying unbalance degree through a control variable strategy, and calculating the weight value of each influence factor based on the influence degree of each influence factor on the current-carrying unbalance degree; and adjusting weight parameters of all influence factors in an initial current-carrying unbalance degree determination network based on the weight values of all influence factors to obtain a current-carrying unbalance degree determination network, and calculating the target current-carrying unbalance degree of the cable line based on all influence factor data and the current-carrying unbalance degree determination network. A simulation model is built for a plurality of influence factors influencing the current-carrying unbalance degree in a cable line, influence factor data of each influence factor are adjusted based on a control variable method, influence degree of each influence factor on the current-carrying unbalance degree is identified, and therefore the weight value of each influence factor is obtained. Then, the weight parameters of all influence factors in the network are determined based on the weight values of all influence factors by adjusting the initial current-carrying unbalance, so that the target current-carrying unbalance of the cable line is calculated, the influence weights of all influence factors on the current-carrying unbalance are analyzed while a plurality of influence factors of the current-carrying unbalance are comprehensively considered, the corresponding target current-carrying unbalance of the cable line is calculated, and the accuracy of the calculated current-carrying unbalance is improved.
Drawings
FIG. 1 is a flow chart of a method for determining a carrier flow imbalance in an embodiment;
FIG. 2 is a flow diagram of an example of carrier flow imbalance determination in one embodiment;
FIG. 3 is a block diagram of a carrier flow imbalance determination apparatus in one embodiment;
fig. 4 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The current-carrying unbalance degree determining method provided by the embodiment of the application is mainly applied to an application environment corresponding to a cable line simulation process. The method can be applied to the terminal, the server and a system comprising the terminal and the server, and is realized through interaction of the terminal and the server. The server may be implemented as a stand-alone server or as a server cluster formed by a plurality of servers. The terminal may be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, etc. The terminal establishes a simulation model for a plurality of influence factors influencing the current-carrying unbalance degree in the cable line, adjusts influence factor data of each influence factor based on a control variable method, and identifies the influence degree of each influence factor on the current-carrying unbalance degree, so that the weight value of each influence factor is obtained. Then, the weight parameters of all influence factors in the network are determined based on the weight values of all influence factors by adjusting the initial current-carrying unbalance, so that the target current-carrying unbalance of the cable line is calculated, the influence weights of all influence factors on the current-carrying unbalance are analyzed while a plurality of influence factors of the current-carrying unbalance are comprehensively considered, the corresponding target current-carrying unbalance of the cable line is calculated, and the accuracy of the calculated current-carrying unbalance is improved.
In one embodiment, as shown in fig. 1, a method for determining a current-carrying unbalance is provided, which is described by taking an application of the method to a terminal as an example, and includes the following steps:
step S101, a plurality of influence factors influencing the current-carrying unbalance degree in the cable line and influence factor data corresponding to each influence factor are obtained, and a simulation model of the cable line is built based on each influence factor.
In this embodiment, a terminal responds to an influence factor uploading operation of a worker, acquires a plurality of influence factors influencing current-carrying unbalance in a cable line, and acquires a current data value of each image factor of the cable line, thereby obtaining influence factor data corresponding to each influence factor of the cable box line. The influencing factors include, but are not limited to, the laying environment, the laying mode, the phase sequence arrangement mode, the wire core resistivity difference, the cable insulation layer thickness difference, the cable wire core thickness difference, the relative dielectric constant and relative magnetic permeability of the cable insulation material, the cable line length, the contact resistance and the soil resistivity of the parallel cables. The data of the influencing factors corresponding to the laying environment comprise soil direct-buried laying, tunnel laying and cable trench radiation; the data of the influencing factors corresponding to the laying mode comprise one-line laying, double-row laying, inverted-triangle laying and the like.
And deleting all structural information except the influence factors in the historical simulation model of the cable line by the terminal based on the influence factors of the cable line to obtain a simulation model of the cable line, which is built based on the influence factors of the cable line.
Step S102, based on the simulation model, the influence degree of each influence factor on the current-carrying unbalance degree is respectively identified through a control variable strategy, and the weight value of each influence factor is calculated based on the influence degree of each influence factor on the current-carrying unbalance degree.
In this embodiment, the terminal obtains each influence factor data of each influence factor, then, the terminal adjusts the single influence factor data based on each influence factor data of each influence factor through a control variable method, inputs the adjusted influence factor data of each influence factor into the simulation model, carries out a simulation current transmission process to obtain a current carrying unbalance degree corresponding to each influence factor data of each influence factor, and then, the terminal analyzes the influence degree of each influence factor on the current carrying unbalance degree based on the current carrying unbalance degree corresponding to each influence factor data of each influence factor. And finally, the terminal calculates the weight value of each influence factor based on the influence degree of each influence factor on the current-carrying unbalance degree. The specific identification process and calculation process will be described in detail later.
Step S103, adjusting weight parameters of all influence factors in the initial current-carrying unbalance degree determination network based on the weight values of all influence factors to obtain a current-carrying unbalance degree determination network, and calculating the target current-carrying unbalance degree of the cable line based on the data of all influence factors and the current-carrying unbalance degree determination network.
In this embodiment, the terminal adjusts the weight parameters of each influence factor in the initial current-carrying unbalance determination network based on the weight values of each influence factor, so as to obtain the current-carrying unbalance determination network. Then, the terminal determines a network based on the influence factor data and the current-carrying unbalance, and calculates the target current-carrying unbalance of the cable line. The current-carrying unbalance determination network is a neural network comprising an input layer, a hidden layer and an output layer, wherein the hidden layer and the output layer comprise an activation function.
Specifically, the hidden layer activation function is:
the output layer activation function is:
wherein x is an output parameter, S h To hide layer neurons, S k Is the kth hidden layer neuron.
The terminal constructs an input matrix X corresponding to the current-carrying unbalance degree determination network by acquiring sample influence factor data of a plurality of influence factors, and takes the first 70% of lines to form a training set input matrix X 1 The last 30% of rows form the test set input matrix X 2 Splitting the output vector Y in the step 3 into Y corresponding to the input matrix 1 ,Y 2 . Training the neural network model by putting back the training set input and output, wherein the nonlinear transformation output of the neural network is defined as:
Y＝f(F(X,W i ))
in the above formula, Y is an output vector, X is an input matrix, W i For the weight of each influencing factor, F (X, W i ) For the point multiplication of the input parameters (influencing factors) and the weights, f (x) is a nonlinear variation function.
Based on the scheme, a simulation model is built for a plurality of influence factors influencing the current-carrying unbalance degree in the cable line, influence factor data of each influence factor are adjusted based on a control variable method, influence degree of each influence factor on the current-carrying unbalance degree is identified, and therefore the weight value of each influence factor is obtained. Then, the weight parameters of all influence factors in the network are determined based on the weight values of all influence factors by adjusting the initial current-carrying unbalance, so that the target current-carrying unbalance of the cable line is calculated, the influence weights of all influence factors on the current-carrying unbalance are analyzed while a plurality of influence factors of the current-carrying unbalance are comprehensively considered, the corresponding target current-carrying unbalance of the cable line is calculated, and the accuracy of the calculated current-carrying unbalance is improved.
Optionally, after establishing the simulation model of the cable line based on each influencing factor, the method further comprises: collecting a plurality of influence factor data corresponding to each influence factor, and carrying out permutation and combination based on the plurality of influence factor data corresponding to each influence factor to obtain data sets containing the influence factor data corresponding to each influence factor; and constructing a data matrix corresponding to each influencing factor based on each data set.
In this embodiment, the terminal collects a plurality of influence factor data corresponding to each influence factor, and performs permutation and combination based on the plurality of influence factor data corresponding to each influence factor, so as to obtain a data set including the influence factor data corresponding to each influence factor. Then, the terminal constructs a data matrix corresponding to each influencing factor based on each data set. The terminal selects a plurality of numerical points (each influence factor data) according to a fixed step length principle according to a numerical variation range possibly occurring in the production and operation process of the numerical factors (such as wire core resistivity, insulating layer thickness and the like) corresponding to the numerical factors and the non-numerical factors, and then combines the numerical points with the non-numerical factors (such as arrangement mode, laying mode and the like) to form an input matrix, wherein the input matrix is formed by row vectors with values of the influence factors, and the specific constitution is as follows:
In the ith row vector [ x ] i1 ,…,x ig ]Represents the combination of the values of the factors of the ith group of influence factors, g represents the number of the influence factors and x ig Representing the value of the ith group g influence factor.
Based on the scheme, the processing efficiency of subsequent simulation processing is improved by constructing the data matrix and simulating based on the data matrix.
Optionally, the method for identifying the influence degree of each influence factor on the current-carrying unbalance degree by controlling the variable strategy includes: inputting each data group in the data matrix into a simulation model respectively, and carrying out simulation current transmission processing on the simulation model to obtain the corresponding current carrying unbalance degree of each data group; dividing each data set into data sets with only single influencing factor data variables, obtaining data sets corresponding to each influencing factor, and analyzing the influence degree of the influencing factor corresponding to each data set on the current carrying unbalance based on the current carrying unbalance corresponding to each data set contained in each data set.
In this embodiment, the terminal inputs each data group in the data matrix into the simulation model, and performs simulation current transmission processing on the simulation model to obtain the current-carrying unbalance degree corresponding to each data group. The specific current-carrying unbalance calculation process will be described in detail later. And the terminal divides each data group into data sets with only single influencing factor data variables to obtain the data sets corresponding to each influencing factor. And then, the terminal analyzes the influence degree of the influence factors corresponding to each data set on the current carrying unbalance degree based on the current carrying unbalance degree corresponding to each data set contained in each data set.
Based on the scheme, the influence degree of each influence factor on the current-carrying unbalance degree is identified through simulating the current transmission process, and the convulsion of the influence degree of the identified influence factors on the current-carrying unbalance degree is improved and can only be read.
Optionally, each data group in the data matrix is respectively input into a simulation model, and simulation current transmission processing is performed on the simulation model to obtain a current carrying unbalance degree corresponding to each data group, which comprises the following steps: based on each data group in the data matrix, respectively carrying out simulation current transmission processing on the simulation model, wherein the current carrying information corresponds to each data group; and calculating the current carrying unbalance degree of each piece of current carrying information through a current carrying unbalance degree algorithm to obtain the current carrying unbalance degree corresponding to each data group.
In this embodiment, the terminal performs the simulation current transmission processing on the simulation model based on each data set in the data matrix, so as to obtain the current carrying information corresponding to each data set. Wherein the current carrying information comprises current information for each phase of the in-phase parallel cable. And then, the terminal calculates the current carrying unbalance degree of each piece of current carrying information through a current carrying unbalance degree algorithm to obtain the current carrying unbalance degree corresponding to each data group. The current-carrying unbalance algorithm is based on an in-phase parallel cable structure, and the calculation formula of the algorithm is as follows: 1. (maximum current-minimum current)/maximum current; 2. MAX (phase current-three-phase average current)/three-phase average current. For example, if the three-phase currents are ia=9aib=8aic=4a, the three-phase average currents are 7A, the phase currents-three-phase average currents are 2A, 1A, and 3A, respectively, and the maximum difference is obtained at the terminal, MAX (phase current-three-phase average current) =3a, so that the three-phase current imbalance degree=3/7.
Based on the scheme, the current carrying unbalance degree corresponding to each data group is calculated through the simulated current carrying information, so that the link relation between the data of each influencing factor and the current carrying unbalance degree is improved.
Optionally, based on the current carrying unbalance degree corresponding to each data set included in each data set, analyzing the influence degree of the influence factor corresponding to each data set on the current carrying unbalance degree includes: identifying the current carrying unbalance degree corresponding to each influence factor data of the influence factors of each data set based on the current carrying unbalance degree corresponding to each data set contained in each data set; for each influence factor, calculating a data difference value between the data of each influence factor and an imbalance difference value between the current carrying imbalance corresponding to the data of each influence factor, and determining the association relation between the data variable of the influence factor and the imbalance variable of the current carrying imbalance based on each data difference value and the imbalance difference value corresponding to each data difference value; and determining the influence degree of the influence factors on the current carrying unbalance based on the association relation between the data variable of the influence factors and the unbalance variable of the current carrying unbalance.
In this embodiment, the terminal identifies the current-carrying unbalance degree corresponding to each influence factor data of the influence factors to which each data set belongs, based on the current-carrying unbalance degree corresponding to each data set included in each data set. Then, the terminal calculates, for each influencing factor, a data difference between the influencing factor data of the influencing factor and an imbalance difference between the current carrying imbalance corresponding to the influencing factor data of the influencing factor. And then, the terminal determines the association relation between the data variable of the influence factor and the unbalance variable of the current carrying unbalance based on each data difference value and the unbalance difference value corresponding to each data difference value. The association relationship is the corresponding relationship of the unbalance degree difference value corresponding to the data difference value. And determining the influence degree of the influence factors on the current carrying unbalance based on the association relation between the data variable of the influence factors and the unbalance variable of the current carrying unbalance.
Based on the scheme, the influence degree of the influence factors on the current-carrying unbalance degree is determined by identifying the association relation between each data difference value and the unbalance degree difference value corresponding to each data difference value, so that the determination accuracy of the influence degree is improved.
Optionally, calculating the weight value of each influencing factor based on the influence degree of each influencing factor on the current-carrying unbalance degree includes: for each influencing factor, calculating an unbalance difference value corresponding to the unit data difference value of the influencing factor based on each data difference value of the influencing factor and the unbalance difference value corresponding to each data difference value; and carrying out normalization processing on the unbalance difference value corresponding to the unit data difference value of each influence factor to obtain the weight value of each influence factor.
In this embodiment, the terminal calculates, for each influencing factor, an imbalance difference value corresponding to a unit data difference value of the influencing factor based on each data difference value of the influencing factor and an imbalance difference value corresponding to each data difference value. For example, if the data differences of the influencing factors are 3, 5 and 7 and the unbalance differences corresponding to the data differences are 6, 9 and 13, the terminal performs unit-term calculation on each data difference and the unbalance corresponding to the data difference to obtain the unbalance difference corresponding to the unit data difference of the first data difference as 2; the unbalance difference value corresponding to the unit data difference value of the second data difference value is 1.8; the unit data difference of the third data difference corresponds to an imbalance difference of 1.86, and the unit data difference of the influencing factor corresponds to an imbalance difference of (2+1.8+1.85)/3=1.88. And then, the terminal normalizes the unbalance difference value corresponding to the unit data difference value of each influence factor to obtain the weight value of each influence factor.
Based on the scheme, the weight value of each influence factor is determined by calculating the unbalance degree difference value corresponding to the unit data difference value of the influence factor, so that the accuracy of the determined weight value of each influence factor is improved.
The application also provides a current-carrying unbalance degree determination example, as shown in fig. 2, and the specific processing procedure comprises the following steps:
acquiring a plurality of influence factors influencing the current-carrying unbalance degree in a cable line and influence factor data corresponding to each influence factor;
step S201, based on each influence factor, a simulation model of the cable line is established.
Step S202, collecting a plurality of influence factor data corresponding to each influence factor, and carrying out permutation and combination based on the plurality of influence factor data corresponding to each influence factor to obtain a data set containing the influence factor data corresponding to each influence factor.
Step S203, based on each data group, constructing a data matrix corresponding to each influencing factor.
Step S204, based on each data group in the data matrix, the simulation current transmission processing is performed on the simulation model, and the current carrying information corresponding to each data group is obtained.
Step S205, calculating the current carrying unbalance degree of each current carrying information through a current carrying unbalance degree algorithm, and obtaining the current carrying unbalance degree corresponding to each data group.
In step S206, each data set is divided into data sets with only single influencing factor data variables, so as to obtain data sets corresponding to each influencing factor.
Step S207, based on the current-carrying unbalance degree corresponding to each data set included in each data set, identifies the current-carrying unbalance degree corresponding to each influence factor data of the influence factors to which each data set belongs.
Step S208, for each influencing factor, calculating a data difference value between the data of each influencing factor and an imbalance difference value between the current carrying imbalance corresponding to the data of each influencing factor, and determining the association relationship between the data variable of the influencing factor and the imbalance variable of the current carrying imbalance based on each data difference value and the imbalance difference value corresponding to each data difference value.
Step S209, determining the degree of influence of the influencing factors on the current carrying unbalance based on the association relationship between the data variable of the influencing factors and the unbalance variable of the current carrying unbalance.
Step S210, for each influence factor, calculating an unbalance difference value corresponding to the unit data difference value of the influence factor based on each data difference value of the influence factor and the unbalance difference value corresponding to each data difference value.
Step S211, carrying out normalization processing on the unbalance degree difference value corresponding to the unit data difference value of each influence factor to obtain the weight value of each influence factor.
Step S212, based on the weight value of each influence factor, the weight parameters of each influence factor in the initial current-carrying unbalance degree determination network are adjusted to obtain the current-carrying unbalance degree determination network.
Step S213, calculating the target current-carrying unbalance of the cable line based on the influence factor data and the current-carrying unbalance determination network.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a current-carrying unbalance determining device for realizing the current-carrying unbalance determining method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of the device for determining the current carrying unbalance provided below may be referred to the limitation of the method for determining the current carrying unbalance hereinabove, and will not be repeated here.
In one embodiment, as shown in fig. 3, there is provided a current-carrying unbalance determination device, comprising: an acquisition module 310, a first calculation module 320, and a second calculation module 330, wherein:
an obtaining module 310, configured to obtain a plurality of influence factors affecting the current-carrying unbalance in the cable line and influence factor data corresponding to each influence factor, and establish a simulation model of the cable line based on each influence factor;
the first calculating module 320 is configured to identify, based on the simulation model, a degree of influence of each influence factor on the current-carrying unbalance through a control variable policy, and calculate a weight value of each influence factor based on the degree of influence of each influence factor on the current-carrying unbalance;
The second calculating module 330 is configured to adjust weight parameters of each influencing factor in the initial current-carrying unbalance determining network based on the weight value of each influencing factor, obtain a current-carrying unbalance determining network, and calculate a target current-carrying unbalance of the cable line based on each influencing factor data and the current-carrying unbalance determining network.
Optionally, the apparatus further includes:
the acquisition module is used for acquiring a plurality of influence factor data corresponding to each influence factor, and carrying out permutation and combination based on the plurality of influence factor data corresponding to each influence factor to obtain a data set containing the influence factor data corresponding to each influence factor;
the construction module is used for constructing a data matrix corresponding to each influence factor based on each data set.
Optionally, the first computing module 310 is specifically configured to:
inputting each data group in the data matrix into the simulation model respectively, and carrying out simulation current transmission processing on the simulation model to obtain the current carrying unbalance degree corresponding to each data group;
dividing each data set into data sets with only single influencing factor data variables, obtaining data sets corresponding to each influencing factor, and analyzing the influence degree of the influencing factors corresponding to each data set on the current carrying unbalance degree based on the current carrying unbalance degree corresponding to each data set contained in each data set.
Optionally, the first computing module 310 is specifically configured to:
based on each data group in the data matrix, respectively carrying out simulation current transmission processing on the simulation model, wherein each data group corresponds to current carrying information;
and calculating the current carrying unbalance of each piece of current carrying information through a current carrying unbalance algorithm to obtain the current carrying unbalance corresponding to each data set.
Optionally, the first computing module 310 is specifically configured to:
identifying the current carrying unbalance degree corresponding to each influence factor data of the influence factors of each data set based on the current carrying unbalance degree corresponding to each data set contained in each data set;
for each influence factor, calculating a data difference value between the influence factor data and an imbalance degree difference value between current carrying imbalance degrees corresponding to the influence factor data, and determining an association relation between a data variable of the influence factor and an imbalance degree variable of the current carrying imbalance degree based on the data difference values and the imbalance degree difference values corresponding to the data difference values;
and determining the influence degree of the influence factors on the current carrying unbalance based on the association relation between the data variable of the influence factors and the unbalance variable of the current carrying unbalance.
Optionally, the first computing module 310 is specifically configured to:
for each influencing factor, calculating an unbalance difference value corresponding to a unit data difference value of the influencing factor based on each data difference value of the influencing factor and the unbalance difference value corresponding to each data difference value;
and carrying out normalization processing on the unbalance difference value corresponding to the unit data difference value of each influence factor to obtain the weight value of each influence factor.
The respective modules in the above-described current unbalance determination device may be implemented in whole or in part by software, hardware, or a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a method of determining a current carrying imbalance. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by persons skilled in the art that the architecture shown in fig. 4 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting as to the computer device to which the present inventive arrangements are applicable, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In an embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method of any of the first aspects when the computer program is executed.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the method of any of the first aspects.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method of any of the first aspects.
The user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
Claims (10)
1. A method of determining a current carrying imbalance, the method comprising:
acquiring a plurality of influence factors influencing the current-carrying unbalance degree in a cable line and influence factor data corresponding to each influence factor, and establishing a simulation model of the cable line based on each influence factor;
based on the simulation model, respectively identifying the influence degree of each influence factor on the current-carrying unbalance degree through a control variable strategy, and calculating the weight value of each influence factor based on the influence degree of each influence factor on the current-carrying unbalance degree;
And adjusting weight parameters of all influence factors in an initial current-carrying unbalance degree determination network based on the weight values of all influence factors to obtain a current-carrying unbalance degree determination network, and calculating the target current-carrying unbalance degree of the cable line based on all influence factor data and the current-carrying unbalance degree determination network.
2. The method of claim 1, wherein after establishing the simulation model of the cabling based on each of the influencing factors, further comprising:
collecting a plurality of influence factor data corresponding to each influence factor, and carrying out permutation and combination based on the plurality of influence factor data corresponding to each influence factor to obtain data sets containing the influence factor data corresponding to each influence factor;
and constructing a data matrix corresponding to each influence factor based on each data set.
3. The method according to claim 2, wherein the identifying, based on the simulation model, the degree of influence of each influence factor on the current-carrying unbalance by controlling a variable strategy, respectively, includes:
inputting each data group in the data matrix into the simulation model respectively, and carrying out simulation current transmission processing on the simulation model to obtain the current carrying unbalance degree corresponding to each data group;
Dividing each data set into data sets with only single influencing factor data variables, obtaining data sets corresponding to each influencing factor, and analyzing the influence degree of the influencing factors corresponding to each data set on the current carrying unbalance degree based on the current carrying unbalance degree corresponding to each data set contained in each data set.
4. A method according to claim 3, wherein said inputting each data group in the data matrix into the simulation model respectively, and performing a simulation current transmission process on the simulation model to obtain a current carrying unbalance corresponding to each data group includes:
based on each data group in the data matrix, respectively carrying out simulation current transmission processing on the simulation model, wherein each data group corresponds to current carrying information;
and calculating the current carrying unbalance of each piece of current carrying information through a current carrying unbalance algorithm to obtain the current carrying unbalance corresponding to each data set.
5. The method according to claim 1, wherein analyzing the degree of influence of the influence factor corresponding to each data set on the degree of current carrying unbalance based on the degree of current carrying unbalance corresponding to each data set included in each data set comprises:
Identifying the current carrying unbalance degree corresponding to each influence factor data of the influence factors of each data set based on the current carrying unbalance degree corresponding to each data set contained in each data set;
for each influence factor, calculating a data difference value between the influence factor data and an imbalance degree difference value between current carrying imbalance degrees corresponding to the influence factor data, and determining an association relation between a data variable of the influence factor and an imbalance degree variable of the current carrying imbalance degree based on the data difference values and the imbalance degree difference values corresponding to the data difference values;
and determining the influence degree of the influence factors on the current carrying unbalance based on the association relation between the data variable of the influence factors and the unbalance variable of the current carrying unbalance.
6. The method of claim 5, wherein calculating a weight value for each influencing factor based on the degree of influence of each influencing factor on the current carrying unbalance comprises:
for each influencing factor, calculating an unbalance difference value corresponding to a unit data difference value of the influencing factor based on each data difference value of the influencing factor and the unbalance difference value corresponding to each data difference value;
And carrying out normalization processing on the unbalance difference value corresponding to the unit data difference value of each influence factor to obtain the weight value of each influence factor.
7. A current-carrying unbalance determination device, characterized in that the device comprises:
the acquisition module is used for acquiring a plurality of influence factors influencing the current-carrying unbalance degree in the cable line and influence factor data corresponding to each influence factor, and establishing a simulation model of the cable line based on each influence factor;
the first calculation module is used for respectively identifying the influence degree of each influence factor on the current-carrying unbalance degree through a control variable strategy based on the simulation model, and calculating the weight value of each influence factor based on the influence degree of each influence factor on the current-carrying unbalance degree;
the second calculation module is used for adjusting weight parameters of all influence factors in the initial current-carrying unbalance degree determination network based on the weight values of all influence factors to obtain a current-carrying unbalance degree determination network, and calculating the target current-carrying unbalance degree of the cable line based on all influence factor data and the current-carrying unbalance degree determination network.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
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