Overhead power transmission corridor electromagnetic environment evaluation method and device, terminal and storage medium

Abstract

The present application relates to overhead line planning technical field, especially in an overhead transmission corridor electromagnetic environment evaluation method, device, terminal and storage medium, the present application method first obtains multiple environmental monitoring data sets and multiple electromagnetic data sets, then according to the correlation of the multiple environmental monitoring data sets and the multiple electromagnetic data sets, determine multiple influence factors and multiple influence factor data sets, then according to the multiple influence factor data sets and the multiple electromagnetic data sets, construct electromagnetic evaluation model, finally multiple typical data sets are input into the electromagnetic evaluation model, obtain the multiple outputs of the electromagnetic evaluation model as the score of overhead transmission corridor electromagnetic environment. The present application embodiment, based on the measured data to construct the model, based on the measured data to solve the model, therefore, the model precision based on environmental monitoring data is high, and the data deviation obtained from the model output result and the real environment is small.

Description

Technical Field

[0001] This invention relates to the field of overhead line planning technology, and in particular to a method, device, terminal and storage medium for evaluating the electromagnetic environment of an overhead power transmission corridor. Background Technology

[0002] Transmission lines are divided into overhead transmission lines and cable lines. Overhead transmission lines consist of line towers, conductors, insulators, line hardware, guy wires, tower foundations, grounding devices, etc., and are erected on the ground. According to the nature of the transmitted current, power transmission is divided into AC transmission and DC transmission. The maximum transmission power determined after comprehensively considering technical, economic and other factors is called the transmission capacity of the line. The protection of transmission lines is divided into main protection and backup protection. Currently, three-phase AC transmission with a frequency of 50 Hz (or 60 Hz) is widely used. Since the 1960s, DC transmission has also seen new developments and, in conjunction with AC transmission, forms a hybrid AC / DC power system.

[0003] The main parameters to consider in the electromagnetic environment of power transmission lines are power frequency electric field, power frequency magnetic field, corona discharge, radio interference, and audible noise. The interaction between the electromagnetic environment and the transmission lines has a very serious impact on the equipment in the transmission corridor and the transmission lines themselves. Therefore, it is essential to conduct a reasonable evaluation of the electromagnetic environment of the transmission lines.

[0004] Currently, the evaluation of electromagnetic environment parameters of transmission lines is carried out by constructing an electromagnetic environment influence model through a physical model. However, in reality, the evaluation accuracy and practicality of this model cannot meet the needs of design and construction, and it cannot accurately guide the planning of overhead lines, thus causing great inconvenience to the design and construction of transmission lines.

[0005] Therefore, it is necessary to develop and design a method for evaluating the electromagnetic environment of overhead power transmission corridors. Summary of the Invention

[0006] The present invention provides a method, device, terminal and storage medium for evaluating the electromagnetic environment of overhead power transmission corridors, which solves the problem that the evaluation results of the electromagnetic environment of power transmission lines are inaccurate when using the method of constructing an evaluation model of the electromagnetic environment influence through a physical model.

[0007] In a first aspect, embodiments of the present invention provide a method for evaluating the electromagnetic environment of an overhead power transmission corridor, comprising:

[0008] Multiple environmental monitoring datasets and multiple electromagnetic datasets were acquired. The environmental monitoring datasets included multiple environmental monitoring data acquired in the power transmission corridor at different time points.

[0009] Based on the correlation between the multiple environmental monitoring datasets and the multiple electromagnetic datasets, multiple influencing factors and multiple influencing factor datasets corresponding to the multiple influencing factors are determined;

[0010] Based on the multiple influencing factor datasets and the multiple electromagnetic datasets, an electromagnetic evaluation model is constructed.

[0011] Multiple typical datasets are input into the electromagnetic evaluation model, and multiple outputs of the electromagnetic evaluation model are obtained as scores for the electromagnetic environment of the overhead power transmission corridor. The typical datasets are obtained based on the multiple influencing factors.

[0012] In one possible implementation, determining multiple influencing factors and multiple influencing factor datasets corresponding to the multiple influencing factors based on the correlation between the multiple environmental monitoring datasets and the multiple electromagnetic datasets includes:

[0013] For each of the plurality of environmental monitoring datasets, perform the following steps:

[0014] The environmental dataset is expanded to obtain environmental data row vectors, multiple difference row vectors, and multiple integral row vectors;

[0015] An environment matrix is ​​constructed based on the environmental data row vectors, the plurality of difference row vectors, and the plurality of integral row vectors;

[0016] Based on the environmental matrix, the multiple electromagnetic datasets, and the first formula, multiple correlation factors are obtained, wherein the first formula is:

[0017]

[0018] In the formula, A i Let B(j,:) be the i-th electromagnetic dataset, B(j,:) be the j-th row of the environment matrix, and A be the i-th electromagnetic dataset. i (k) is the k-th element of the i-th electromagnetic dataset, B(j,k) is the element in the j-th row and k-th column of the environment matrix, and R ij Let n be the correlation factor between the i-th electromagnetic dataset and the j-th row of the environment matrix, and n be the total number of elements in the electromagnetic dataset.

[0019] The influencing factors corresponding to the electromagnetic dataset are determined based on the target correlation factor, wherein the target correlation factor is a correlation factor whose absolute value is greater than a threshold.

[0020] The row vectors corresponding to the target correlation factors are added to the influencing factor dataset corresponding to the electromagnetic dataset.

[0021] In one possible implementation, multiple elements in the environmental data row vector are arranged in chronological order according to time nodes. The expansion of the environmental dataset to obtain environmental data row vectors, multiple difference row vectors, and multiple integral row vectors includes:

[0022] The difference row vector is obtained based on the environmental data row vector and the second formula, wherein the second formula is:

[0023]

[0024] In the formula, B(D+1,k) is the kth element of the Dth difference, and X(k) is the kth element of the environmental data row vector;

[0025] Based on the environmental data row vector and the third formula, the integral row vector is obtained, wherein the third formula is:

[0026]

[0027] In the formula, B(I+D+1,k) is the kth element of the I-th integral.

[0028] In one possible implementation, constructing an electromagnetic evaluation model based on the plurality of influencing factor datasets and the plurality of electromagnetic datasets includes:

[0029] For each of the plurality of electromagnetic datasets, perform the following steps:

[0030] Obtain the dataset of influencing factors for the corresponding electromagnetic dataset;

[0031] Based on the first element of each row in the influencing factor dataset and the first element in the electromagnetic dataset, a model equation for the corresponding electromagnetic dataset is constructed, wherein the model equation contains multiple undetermined parameters.

[0032] By using the influencing factor dataset and the electromagnetic dataset, the model equation is solved to obtain solutions for multiple undetermined parameters of the model equation;

[0033] Substituting the solution into the model equation, the model corresponding to the electromagnetic dataset is obtained.

[0034] In one possible implementation, the model equations are:

[0035]

[0036] In the formula, f i (X i Let A be the model equation for the i-th electromagnetic dataset. i(1) is the first element of the i-th electromagnetic dataset, w m Let x be the m-th undetermined coefficient, M be the total number of series, n be the total number of elements in the electromagnetic dataset, and x be the undetermined coefficient. o Let C(o,1) be the o-th dependent variable, and let C(o,1) be the element in the o-th row and 1-th column of the electromagnetic dataset.

[0037] In one possible implementation, the total number of series is greater than or equal to the number of rows in the electromagnetic dataset.

[0038] In one possible implementation, solving the model equations using the influencing factor dataset and the electromagnetic dataset to obtain solutions for multiple undetermined parameters of the model equations includes:

[0039] Determine a predetermined position, wherein the predetermined position is the position from which data is extracted from each row of the electromagnetic dataset and the influencing factor dataset;

[0040] Data retrieval steps: According to predetermined positions, retrieve multiple data points from each row of the electromagnetic dataset and the influencing factor dataset;

[0041] Multiple data points extracted from each row of the influencing factor dataset are input into the model equation to obtain the output of the model equation;

[0042] The difference between the output result and the data taken from the electromagnetic dataset is calculated;

[0043] If the difference is greater than the threshold, then multiple undetermined parameters in the model equation are adjusted according to the difference, and after adjusting the predetermined position according to the predetermined procedure, the process jumps to the data retrieval step.

[0044] Secondly, embodiments of the present invention provide an electromagnetic environment assessment device for overhead power transmission corridors, used to implement the electromagnetic environment assessment method for overhead power transmission corridors as described in the first aspect or any possible implementation thereof, wherein the electromagnetic environment assessment device for overhead power transmission corridors includes:

[0045] The data acquisition module is used to acquire multiple environmental monitoring datasets and multiple electromagnetic datasets. The environmental monitoring datasets include multiple environmental monitoring data acquired in the power transmission corridor at different time points.

[0046] The correlation determination module is used to determine multiple influencing factors and multiple influencing factor datasets corresponding to the multiple influencing factors based on the correlation between the multiple environmental monitoring datasets and the multiple electromagnetic datasets.

[0047] The model building module is used to build an electromagnetic evaluation model based on the multiple influencing factor datasets and the multiple electromagnetic datasets.

[0048] as well as,

[0049] The evaluation output module is used to input multiple typical datasets into the electromagnetic evaluation model and obtain multiple outputs of the electromagnetic evaluation model as scores of the electromagnetic environment of the overhead power transmission corridor, wherein the typical datasets are obtained based on the multiple influencing factors.

[0050] Thirdly, embodiments of the present invention provide a terminal, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the steps of the method as described in the first aspect or any possible implementation of the first aspect.

[0051] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method as described in the first aspect or any possible implementation thereof.

[0052] The beneficial effects of the embodiments of the present invention compared with the prior art are as follows:

[0053] This invention discloses a method for evaluating the electromagnetic environment of an overhead power transmission corridor. First, it acquires multiple environmental monitoring datasets and multiple electromagnetic datasets. The environmental monitoring datasets include multiple environmental monitoring data acquired at different time points within the transmission corridor. Then, based on the correlation between the multiple environmental monitoring datasets and the multiple electromagnetic datasets, it determines multiple influencing factors and multiple influencing factor datasets corresponding to these factors. Next, it constructs an electromagnetic evaluation model based on the multiple influencing factor datasets and the multiple electromagnetic datasets. Finally, it inputs multiple typical datasets into the electromagnetic evaluation model and obtains multiple outputs from the model as scores for the electromagnetic environment of the overhead power transmission corridor. The typical datasets are obtained based on the multiple influencing factors. This invention constructs and solves the model based on measured data; therefore, the model constructed based on environmental monitoring data has high accuracy, and the deviation between the model output results and the data obtained from the actual environment is small.

[0054] In this embodiment of the invention, when constructing the electromagnetic evaluation model, the influence of time on electromagnetic data is considered. Factors with small short-term impact but long-lasting effects and rapidly changing factors that can have an impact are taken as influencing factors. After correlation and new judgment, they are taken as influencing factors. Therefore, the model construction is more accurate. Attached Figure Description

[0055] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 This is a flowchart of the electromagnetic environment evaluation method for overhead power transmission corridors provided by the embodiments of the present invention;

[0057] Figure 2 This is a functional block diagram of the electromagnetic environment evaluation device for overhead power transmission corridors provided in the embodiments of the present invention;

[0058] Figure 3 This is a terminal function block diagram provided by an embodiment of the present invention. Detailed Implementation

[0059] In the following description, specific details such as particular system structures and techniques are set forth for illustrative purposes and not for limitation, so as to provide a thorough understanding of embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0060] To make the objectives, technical solutions, and advantages of the present invention clearer, specific embodiments will be described below in conjunction with the accompanying drawings.

[0061] The embodiments of the present invention will be described in detail below. These examples are implemented based on the technical solutions of the present invention, and detailed implementation methods and specific operation processes are given. However, the scope of protection of the present invention is not limited to the following embodiments.

[0062] Figure 1 A flowchart of an electromagnetic environment evaluation method for overhead power transmission corridors provided for embodiments of the present invention.

[0063] like Figure 1 As shown, a flowchart illustrating the implementation of the electromagnetic environment assessment method for overhead power transmission corridors provided by an embodiment of the present invention is illustrated below:

[0064] In step 101, multiple environmental monitoring datasets and multiple electromagnetic datasets are acquired. The environmental monitoring datasets include multiple environmental monitoring data acquired in the power transmission corridor based on different time points.

[0065] In step 102, based on the correlation between the multiple environmental monitoring datasets and the multiple electromagnetic datasets, multiple influencing factors and multiple influencing factor datasets corresponding to the multiple influencing factors are determined.

[0066] In some embodiments, step 102 includes:

[0067] For each of the plurality of environmental monitoring datasets, perform the following steps:

[0068] The environmental dataset is expanded to obtain environmental data row vectors, multiple difference row vectors, and multiple integral row vectors;

[0069] An environment matrix is ​​constructed based on the environmental data row vectors, the plurality of difference row vectors, and the plurality of integral row vectors;

[0070] Based on the environmental matrix, the multiple electromagnetic datasets, and the first formula, multiple correlation factors are obtained, wherein the first formula is:

[0071]

[0072] In the formula, A i Let B(j,:) be the i-th electromagnetic dataset, B(j,:) be the j-th row of the environment matrix, and A be the i-th electromagnetic dataset. i (k) is the k-th element of the i-th electromagnetic dataset, B(j,k) is the element in the j-th row and k-th column of the environment matrix, and R ij Let n be the correlation factor between the i-th electromagnetic dataset and the j-th row of the environment matrix, and n be the total number of elements in the electromagnetic dataset.

[0073] The influencing factors corresponding to the electromagnetic dataset are determined based on the target correlation factor, wherein the target correlation factor is a correlation factor whose absolute value is greater than a threshold.

[0074] The row vectors corresponding to the target correlation factors are added to the influencing factor dataset corresponding to the electromagnetic dataset.

[0075] In some implementations, multiple elements in the environmental data row vector are arranged in chronological order according to time nodes. Expanding the environmental dataset to obtain environmental data row vectors, multiple difference row vectors, and multiple integral row vectors includes:

[0076] The difference row vector is obtained based on the environmental data row vector and the second formula, wherein the second formula is:

[0077]

[0078] In the formula, B(D+1,k) is the kth element of the Dth difference, and X(k) is the kth element of the environmental data row vector;

[0079] Based on the environmental data row vector and the third formula, the integral row vector is obtained, wherein the third formula is:

[0080]

[0081] In the formula, B(I+D+1,k) is the kth element of the I-th integral.

[0082] For example, multiple environmental monitoring datasets monitor data from multiple aspects, such as: voltage and current of transmission lines, design parameters of transmission lines (such as assumed height, spacing between transmission lines, etc.), weather factors (such as temperature and humidity), ground conditions, etc. Starting from these monitoring directions, a monitoring data is obtained at regular intervals. According to the correspondence of time nodes, multiple environmental datasets are obtained. For example, the transmission line voltage dataset includes multiple transmission line voltage data arranged in chronological order of time nodes.

[0083] Similarly, electromagnetic monitoring can start from the following items: electric field, magnetic field, corona, discharge, radio interference, etc. Based on these items, the electromagnetic monitoring data obtained according to the predetermined time nodes constitute multiple electromagnetic datasets. For example, the electric field dataset includes data on the electric field strength of multiple fields arranged in chronological order.

[0084] Our general understanding is that electromagnetic data changes directly due to environmental monitoring data, and the equations of existing physical models are also constructed based on this view. However, it has been proven that the equations constructed based on this understanding are inaccurate, and if electromagnetic monitoring instructions are made based on the model, the results often deviate significantly from reality.

[0085] A more scientific understanding is that electromagnetic monitoring data is not only affected by current environmental monitoring data, but also by some seemingly insignificant but long-term monitoring data. It is also unrelated to some environmental monitoring data itself, but is related to the degree of change in environmental monitoring data. For example, the impact of drastic changes in humidity on discharge is much greater than that of humidity itself.

[0086] Therefore, when selecting influencing factors and their data, the impact of time processes should be given special consideration.

[0087] In this embodiment of the invention, the environmental dataset is expanded to obtain environmental data, differential data, and integral data.

[0088] The correlation between the expanded data and the electromagnetic data is verified using the first formula:

[0089]

[0090] In the formula, A i Let B(j,:) be the i-th electromagnetic dataset, B(j,:) be the j-th row of the environment matrix, and A be the i-th electromagnetic dataset. i (k) is the k-th element of the i-th electromagnetic dataset, B(j,k) is the element in the j-th row and k-th column of the environment matrix, and R ij Let be the correlation factor between the i-th electromagnetic dataset and the j-th row of the environment matrix, and n be the total number of elements in the electromagnetic dataset.

[0091] The correlation factors obtained through the first formula are used to determine the environmental monitoring quantities as influencing factors when the absolute value of the factor is large, and the corresponding data are defined as influencing factor data.

[0092] In the first formula, the difference and integral data are obtained through the second and third formulas. The second formula is:

[0093]

[0094] In the formula, B(D+1,k) is the kth element of the Dth difference, and X(k) is the kth element of the environmental data row vector;

[0095] The third formula is:

[0096]

[0097] In the formula, B(I+D+1,k) is the kth element of the I-th integral.

[0098] By constructing model equations from the influencing factors obtained, the amount of data collection and calculation required to construct the equations is reduced, and the complexity of the equations is also simplified.

[0099] In step 103, an electromagnetic evaluation model is constructed based on the multiple influencing factor datasets and the multiple electromagnetic datasets.

[0100] In some implementations, step 103 includes:

[0101] For each of the plurality of electromagnetic datasets, perform the following steps:

[0102] Obtain the dataset of influencing factors for the corresponding electromagnetic dataset;

[0103] Based on the first element of each row in the influencing factor dataset and the first element in the electromagnetic dataset, a model equation for the corresponding electromagnetic dataset is constructed, wherein the model equation contains multiple undetermined parameters.

[0104] By using the influencing factor dataset and the electromagnetic dataset, the model equation is solved to obtain solutions for multiple undetermined parameters of the model equation;

[0105] Substituting the solution into the model equation, the model corresponding to the electromagnetic dataset is obtained.

[0106] In some implementations, the model equations are:

[0107]

[0108] In the formula, f i (X i Let A be the model equation for the i-th electromagnetic dataset. i (1) is the first element of the i-th electromagnetic dataset, w m Let x be the m-th undetermined coefficient, M be the total number of series, n be the total number of elements in the electromagnetic dataset, and x be the undetermined coefficient. o Let C(o,1) be the element in the O-th row and 1-th column of the electromagnetic dataset.

[0109] In some implementations, the total number of series is greater than or equal to the number of rows in the electromagnetic dataset.

[0110] In some implementations, solving the model equations using the influencing factor dataset and the electromagnetic dataset to obtain solutions for multiple undetermined parameters of the model equations includes:

[0111] Determine a predetermined position, wherein the predetermined position is the position from which data is extracted from each row of the electromagnetic dataset and the influencing factor dataset;

[0112] Data retrieval steps: According to predetermined positions, retrieve multiple data points from each row of the electromagnetic dataset and the influencing factor dataset;

[0113] Multiple data points extracted from each row of the influencing factor dataset are input into the model equation to obtain the output of the model equation;

[0114] The difference between the output result and the data taken from the electromagnetic dataset is calculated;

[0115] If the difference is greater than the threshold, then multiple undetermined parameters in the model equation are adjusted according to the difference, and after adjusting the predetermined position according to the predetermined procedure, the process jumps to the data retrieval step.

[0116] For example, the equation is constructed based on the independent variable data: the influencing factors dataset and the dependent variable data: the electromagnetic dataset, and then solved using the independent variable data and the dependent variable data, thereby clarifying the structure of the equation.

[0117] Specifically, one possible equation is as follows:

[0118]

[0119] In the formula, f i (X i Let A be the model equation for the i-th electromagnetic dataset. i (1) is the first element of the i-th electromagnetic dataset, w m Let x be the m-th undetermined coefficient, M be the total number of series, n be the total number of elements in the electromagnetic dataset, and x be the undetermined coefficient. o Let C(o,1) be the o-th dependent variable, and let C(o,1) be the element in the o-th row and 1-th column of the electromagnetic dataset.

[0120] In order to achieve a faster iteration process, the total number of series is often set to be relatively small. This approach comes at the cost of sacrificing the fitting results of the equation. Therefore, it is necessary to make reasonable choices about the number of series. Generally speaking, the number of series should not be less than the number of rows in the electromagnetic dataset.

[0121] The iterative approach involves substituting known data into the equation, obtaining the result, comparing the result with the measured data, and adjusting the undetermined coefficients of the equation based on the deviation between the two. Of course, it is also possible to solve for the undetermined coefficients using gradient descent, genetic algorithms, or particle swarm optimization algorithms.

[0122] In step 104, multiple typical datasets are input into the electromagnetic evaluation model, and multiple outputs of the electromagnetic evaluation model are obtained as scores of the electromagnetic environment of the overhead power transmission corridor. The typical datasets are obtained based on the multiple influencing factors.

[0123] After the model is built, a typical dataset is obtained based on the influencing factors. The dataset is then expanded using the dataset expansion method in step 102 and input into the model to obtain the evaluation results of the electromagnetic environment of the overhead power transmission corridor under typical scenarios.

[0124] This invention discloses an implementation method for evaluating the electromagnetic environment of overhead power transmission corridors. First, it acquires multiple environmental monitoring datasets and multiple electromagnetic datasets. The environmental monitoring datasets include multiple environmental monitoring data acquired at different time points within the transmission corridor. Then, based on the correlation between the multiple environmental monitoring datasets and the multiple electromagnetic datasets, it determines multiple influencing factors and multiple influencing factor datasets corresponding to these factors. Next, it constructs an electromagnetic evaluation model based on the multiple influencing factor datasets and the multiple electromagnetic datasets. Finally, it inputs multiple typical datasets into the electromagnetic evaluation model and obtains multiple outputs from the model as scores for the electromagnetic environment of the overhead power transmission corridor. The typical datasets are obtained based on the multiple influencing factors. This implementation method constructs and solves the model based on measured data; therefore, the model constructed based on environmental monitoring data has high accuracy, and the deviation between the model output results and the data obtained from the actual environment is small.

[0125] In this embodiment of the invention, when constructing the electromagnetic evaluation model, the influence of time on electromagnetic data is considered. Factors with small short-term impact but long-lasting effects and rapidly changing factors that can have an impact are taken as influencing factors. After correlation and new judgment, they are taken as influencing factors. Therefore, the model construction is more accurate.

[0126] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0127] The following are embodiments of the apparatus of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0128] Figure 2 This is a functional block diagram of the electromagnetic environment assessment device for overhead power transmission corridors provided in an embodiment of the present invention, with reference to... Figure 2 The electromagnetic environment assessment device 2 for overhead power transmission corridors includes: a data acquisition module 201, a correlation determination module 202, a model construction module 203, and an evaluation output module 204, wherein:

[0129] The data acquisition module 201 is used to acquire multiple environmental monitoring datasets and multiple electromagnetic datasets. The environmental monitoring datasets include multiple environmental monitoring data acquired in the power transmission corridor based on different time points.

[0130] The correlation determination module 202 is used to determine multiple influencing factors and multiple influencing factor datasets corresponding to the multiple influencing factors based on the correlation between the multiple environmental monitoring datasets and the multiple electromagnetic datasets.

[0131] The model building module 203 is used to build an electromagnetic evaluation model based on the multiple influencing factor datasets and the multiple electromagnetic datasets.

[0132] The evaluation output module 204 is used to input multiple typical datasets into the electromagnetic evaluation model and obtain multiple outputs of the electromagnetic evaluation model as scores of the electromagnetic environment of the overhead power transmission corridor, wherein the typical datasets are obtained based on the multiple influencing factors.

[0133] Figure 3 This is a functional block diagram of the terminal provided in an embodiment of the present invention. For example... Figure 3 As shown, the terminal 3 in this embodiment includes a processor 300 and a memory 301, wherein the memory 301 stores a computer program 302 that can run on the processor 300. When the processor 300 executes the computer program 302, it implements the steps in the above-described methods and embodiments for evaluating the electromagnetic environment of overhead power transmission corridors, for example... Figure 1 Steps 101 to 104 are shown.

[0134] For example, the computer program 302 may be divided into one or more modules / units, which are stored in the memory 301 and executed by the processor 300 to complete the present invention.

[0135] The terminal 3 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. The terminal 3 may include, but is not limited to, a processor 300 and a memory 301. Those skilled in the art will understand that... Figure 3 This is merely an example of terminal 3 and does not constitute a limitation on terminal 3. It may include more or fewer components than shown, or combine certain components, or different components. For example, terminal 3 may also include input / output devices, network access devices, buses, etc.

[0136] The processor 300 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0137] The memory 301 can be an internal storage unit of the terminal 3, such as a hard disk or memory of the terminal 3. The memory 301 can also be an external storage device of the terminal 3, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the terminal 3. Furthermore, the memory 301 can include both internal storage units and external storage devices of the terminal 3. The memory 301 is used to store the computer program 302 and other programs and data required by the terminal 3. The memory 301 can also be used to temporarily store data that has been output or will be output.

[0138] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the aforementioned method embodiments, and will not be repeated here.

[0139] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0140] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0141] In the embodiments provided by this invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0142] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0143] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0144] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-described embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various methods and apparatus embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0145] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for evaluating electromagnetic environment of overhead power transmission corridor, characterized in that, include: Multiple environmental monitoring datasets and multiple electromagnetic datasets were acquired. The environmental monitoring datasets included multiple environmental monitoring data acquired in the power transmission corridor at different time points. Based on the correlation between the multiple environmental monitoring datasets and the multiple electromagnetic datasets, multiple influencing factors and multiple influencing factor datasets corresponding to the multiple influencing factors are determined; Based on the multiple influencing factor datasets and the multiple electromagnetic datasets, an electromagnetic evaluation model is constructed, including: For each of the plurality of electromagnetic datasets, perform the following steps: Obtain the dataset of influencing factors for the corresponding electromagnetic dataset; Based on the first element of each row in the influencing factor dataset and the first element in the electromagnetic dataset, a model equation for the corresponding electromagnetic dataset is constructed, wherein the model equation contains multiple undetermined parameters. By using the influencing factor dataset and the electromagnetic dataset, the model equation is solved to obtain solutions for multiple undetermined parameters of the model equation; Substitute the solution into the model equation to obtain the model for the corresponding electromagnetic dataset; Multiple typical datasets are input into the electromagnetic evaluation model, and multiple outputs of the electromagnetic evaluation model are obtained as scores of the electromagnetic environment of the overhead power transmission corridor. The typical datasets are obtained based on the multiple influencing factors. The model equation is as follows: In the formula, For the first Model equations for an electromagnetic dataset, For the first The first element of an electromagnetic dataset, For the first One undetermined coefficient The total number of series, This represents the total number of elements in the electromagnetic dataset. For the first One dependent variable, The first influencing factor dataset The element in the first row and first column.

2. The overhead power transmission corridor electromagnetic environmental evaluation method according to claim 1, characterized by, The step of determining multiple influencing factors and corresponding datasets of influencing factors based on the correlation between the multiple environmental monitoring datasets and the multiple electromagnetic datasets includes: For each of the plurality of environmental monitoring datasets, perform the following steps: The environmental monitoring dataset is expanded to obtain environmental data row vectors, multiple difference row vectors, and multiple integral row vectors. An environment matrix is ​​constructed based on the environmental data row vector, the plurality of difference row vectors, and the plurality of integral row vectors. Based on the environmental matrix, the multiple electromagnetic datasets, and the first formula, multiple correlation factors are obtained, wherein the first formula is: In the formula, For the first Electromagnetic datasets The first of the environment matrix OK, For the first The first electromagnetic dataset One element, The first of the environment matrix Line number Column elements, For the first The first electromagnetic dataset and the environment matrix The correlation factor of the row, This represents the total number of elements in the electromagnetic dataset. The influencing factors corresponding to the electromagnetic dataset are determined based on the target correlation factor, wherein the target correlation factor is a correlation factor whose absolute value is greater than a threshold. The row vectors corresponding to the target correlation factors are added to the influencing factor dataset corresponding to the electromagnetic dataset.

3. The overhead power transmission corridor electromagnetic environmental evaluation method according to claim 2, characterized by, The elements in the environmental data row vector are arranged in chronological order according to time nodes. The expansion of the environmental monitoring dataset to obtain environmental data row vectors, multiple difference row vectors, and multiple integral row vectors includes: The difference row vector is obtained based on the environmental data row vector and the second formula, wherein the second formula is: wherein is the first difference of the first element of the second is the first element of the environmental data row vector; Based on the environmental data row vector and the third formula, the integral row vector is obtained, wherein the third formula is: wherein is the first element of the first integration.

4. The overhead power transmission corridor electromagnetic environmental evaluation method of claim 1, wherein, The total number of series is greater than or equal to the number of rows in the electromagnetic dataset.

5. The overhead power line corridor electromagnetic environmental assessment method of claim 1, wherein, The step of solving the model equations using the influencing factor dataset and the electromagnetic dataset to obtain solutions for multiple undetermined parameters of the model equations includes: Determine a predetermined position, wherein the predetermined position is the position from which data is extracted from each row of the electromagnetic dataset and the influencing factor dataset; Data retrieval steps: According to predetermined positions, retrieve multiple data points from each row of the electromagnetic dataset and the influencing factor dataset; Multiple data points extracted from each row of the influencing factor dataset are input into the model equation to obtain the output of the model equation; The difference between the output result and the data taken from the electromagnetic dataset is calculated; If the difference is greater than the threshold, then multiple undetermined parameters in the model equation are adjusted according to the difference, and after adjusting the predetermined position according to the predetermined procedure, the process jumps to the data retrieval step.

6. An overhead power transmission corridor electromagnetic environment evaluation device, characterized by, For implementing the electromagnetic environment assessment method for overhead power transmission corridors as described in any one of claims 1-5, the electromagnetic environment assessment device for overhead power transmission corridors comprises: The data acquisition module is used to acquire multiple environmental monitoring datasets and multiple electromagnetic datasets. The environmental monitoring datasets include multiple environmental monitoring data acquired in the power transmission corridor at different time points. The correlation determination module is used to determine multiple influencing factors and multiple influencing factor datasets corresponding to the multiple influencing factors based on the correlation between the multiple environmental monitoring datasets and the multiple electromagnetic datasets. The model building module is used to build an electromagnetic evaluation model based on the multiple influencing factor datasets and the multiple electromagnetic datasets. as well as, The evaluation output module is used to input multiple typical datasets into the electromagnetic evaluation model and obtain multiple outputs of the electromagnetic evaluation model as scores of the electromagnetic environment of the overhead power transmission corridor, wherein the typical datasets are obtained based on the multiple influencing factors.

7. A terminal comprising a memory and a processor, said memory having stored therein a computer program executable on said processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 5 above.

8. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 7. When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5 above.

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