Harmonic source current estimation method, device, equipment, medium and product

Abstract

The invention relates to a harmonic source current estimation method, device and equipment, a medium and a product. The method comprises the following steps: obtaining harmonic observation current corresponding to a plurality of harmonic load nodes; the multiple harmonic observation currents are input into a source current estimation model, harmonic source currents corresponding to all harmonic current sources are obtained, the source current estimation model comprises a target function, and the target function is used for restraining mutual information among the multiple harmonic source currents to be minimum. By adopting the method, the accuracy of harmonic source current estimation can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of harmonic current, in particular to a harmonic source current estimation method, device, equipment, medium and product. BACKGROUND

[0002] With the increasing of high proportion of renewable energy and high proportion of power electronic equipment in the power system, the harmonic problem in the power grid is increasingly prominent, which constitutes a threat to power quality that cannot be ignored. Therefore, it is necessary to evaluate the harmonic source current corresponding to each harmonic current source.

[0003] The current harmonic source current estimation method is to measure the original harmonic current at the harmonic load, and then separate the original harmonic current based on the Fast Independent Component Analysis (FastICA) method, multivariate linear regression method or complex independent component analysis method to obtain the harmonic source current corresponding to each harmonic current source.

[0004] However, the current harmonic source current estimation method has the problem of low accuracy. SUMMARY

[0005] Therefore, it is necessary to provide a harmonic source current estimation method, device, equipment, medium and product capable of improving accuracy in view of the above technical problems.

[0006] In a first aspect, the present application provides a harmonic source current estimation method, comprising:

[0007] Obtaining harmonic observation currents corresponding to a plurality of harmonic load nodes;

[0008] Inputting the plurality of harmonic observation currents into a source current estimation model to obtain harmonic source currents corresponding to each harmonic current source, the source current estimation model comprising an objective function, the objective function being used to constrain the mutual information between the plurality of harmonic source currents to be minimum.

[0009] In one of the embodiments, inputting the plurality of harmonic observation currents into the source current estimation model to obtain the harmonic source currents corresponding to each harmonic current source comprises:

[0010] According to the harmonic source currents to be solved, an initial mutual information ratio matrix is constructed;

[0011] Based on the objective function and the plurality of harmonic observation currents, the initial mutual information ratio matrix is optimized and solved to obtain a target mutual information ratio matrix;

[0012] According to the target mutual information ratio matrix, the harmonic source currents are calculated.

[0013] In one of the embodiments, based on the objective function and the multiple harmonic observation currents, the initial mutual information ratio matrix is solved and optimized to obtain a target mutual information ratio matrix, including:

[0014] Based on the initial mutual information ratio matrix, a reference harmonic source current and a to-be-optimized harmonic source current are determined from the to-be-solved harmonic source currents;

[0015] The to-be-optimized harmonic source current is optimized by using the objective function, the harmonic observation current and the reference harmonic source current to obtain an optimized mutual information ratio corresponding to the to-be-optimized harmonic source current;

[0016] In the initial mutual information ratio matrix, the mutual information ratio corresponding to the to-be-optimized harmonic source current is updated by using the optimized mutual information ratio to obtain an intermediate mutual information ratio matrix;

[0017] The step of determining the reference harmonic source current and the to-be-optimized harmonic source current from the to-be-solved harmonic source currents based on the initial mutual information ratio matrix is returned to be executed until all the to-be-solved harmonic source currents are optimized to obtain the target mutual information ratio matrix.

[0018] In one of the embodiments, based on the initial mutual information ratio matrix, a reference harmonic source current and a to-be-optimized harmonic source current are determined from the to-be-solved harmonic source currents, including:

[0019] The initial mutual information ratio matrix is summed row by row to obtain multiple row sums;

[0020] The harmonic source current corresponding to the maximum row sum is selected as the reference harmonic source current from the multiple row sums;

[0021] The maximum mutual information ratio corresponding to the to-be-optimized harmonic source current is determined from the multiple mutual information ratios corresponding to the reference harmonic source current.

[0022] In one of the embodiments, the admittance parameter is included in the objective function; the to-be-optimized harmonic source current is optimized by using the objective function, the harmonic observation current and the reference harmonic source current to obtain the optimized mutual information ratio corresponding to the to-be-optimized harmonic source current, including:

[0023] Based on the reference harmonic source current and a pre-established current relationship matrix, multiple sample admittance parameters are generated, and the current relationship matrix includes the relationship between the harmonic source current and the admittance parameter and the harmonic observation current;

[0024] Each sample admittance parameter is covariance calculated by using a pre-set Gaussian model to obtain a covariance corresponding to each sample admittance parameter;

[0025] An intermediate admittance parameter is determined from the sample admittance parameters by using a pre-set collection function and the covariances.

[0026] The intermediate mutual information ratio corresponding to the intermediate admittance parameter is obtained by calculating and processing the intermediate admittance parameter by using the current relationship matrix and the harmonic observation current, and the updated Gaussian model is obtained based on the intermediate admittance parameter.

[0027] Returning to the step of generating a plurality of sample admittance parameters, in a case where the intermediate mutual information ratio corresponding to the intermediate admittance parameter is less than the ratio threshold, the iteration is terminated, and the intermediate admittance parameter at the time of termination of the iteration is output as the target admittance parameter, and the intermediate mutual information ratio at the time of termination of the iteration is output as the optimized mutual information ratio.

[0028] In one of the embodiments, the intermediate admittance parameter is determined from the sample admittance parameters by using the preset acquisition function and the respective covariance, comprising:

[0029] The expected value and the variance corresponding to the respective covariance are calculated respectively;

[0030] The expected value and the variance are substituted into the acquisition function, and the sample admittance parameter corresponding to the covariance at the time when the value of the acquisition function is maximum is taken as the intermediate admittance parameter.

[0031] In a second aspect, the present application further provides a harmonic source current estimation device, which comprises:

[0032] A data acquisition module is configured to acquire harmonic observation currents corresponding to a plurality of harmonic load nodes;

[0033] A current estimation module is configured to input the plurality of harmonic observation currents into a source current estimation model to obtain harmonic source currents corresponding to a plurality of harmonic current sources, wherein the source current estimation model comprises an objective function, and the objective function is configured to constrain the mutual information between the plurality of harmonic source currents to be minimum.

[0034] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the harmonic source current estimation method of the first aspect when executing the computer program.

[0035] In a fourth aspect, the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the harmonic source current estimation method of the first aspect.

[0036] In a fifth aspect, the present application further provides a computer program product comprising a computer program, and the computer program is executed by a processor to implement the harmonic source current estimation method of the first aspect.

[0037] The harmonic source current estimation method, device, equipment, medium and product have the advantages that in the process of estimating the harmonic source current, the differences between the harmonic source current and the harmonic observation current are distinguished, and the harmonic source current separation and estimation are realized based on the minimum mutual information criterion. Compared with the harmonic source current estimation in the prior art by using the multivariate linear regression method or the complex independent component analysis method, the harmonic source current estimation method in the application can reflect the linear correlation and the nonlinear correlation between the harmonic source currents, so that the harmonic problem caused by the complex nonlinear load can be processed with higher robustness and accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the application or the related art, the drawings needed to be used in the description of the embodiments of the application or the related art will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the application, and for those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0039] Figure 1 The application environment diagram of the harmonic source current estimation method in one embodiment;

[0040] Figure 2 The flowchart of the harmonic source current estimation method in one embodiment;

[0041] Figure 3 The Norton equivalent circuit diagram of the centralized multi-harmonic source system in one embodiment;

[0042] Figure 4 The flowchart of the steps of obtaining the harmonic source current in one embodiment;

[0043] Figure 5 The flowchart of the steps of obtaining the optimized mutual information ratio in one embodiment;

[0044] Figure 6 The flowchart of the logical relationship change of the parameters in the optimization process in one embodiment;

[0045] Figure 7 The flowchart of the harmonic source current estimation method in another embodiment;

[0046] Figure 8 The structural block diagram of the harmonic source current estimation device in one embodiment;

[0047] Figure 9 The internal structure diagram of the computer equipment in one embodiment. DETAILED DESCRIPTION

[0048] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not intended to limit the present application.

[0049] It should be noted that the terms "first", "second", etc. used in the present application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "include" and "have" and any variations thereof used in the present application are intended to cover non-exclusive inclusion. The term "multiple" used in the present application refers to two and more than two. The term "and / or" used in the present application refers to one of the options or any combination of multiple options.

[0050] The harmonic source current estimation method provided by the embodiments of the present application can be applied to the application environment as shown in Figure 1 . Among them, the terminal 102 is a harmonic measurement device, which is used to collect harmonic observation currents and communicate with the server 104 through a network. The data storage system can store the data required to be processed by the server 104. The data storage system can be integrated on the server 104, or placed on the cloud or other network servers.

[0051] The server 104 is used to obtain the harmonic observation currents corresponding to a plurality of harmonic load nodes from the terminal 102; input the plurality of harmonic observation currents into a source current estimation model to obtain the harmonic source currents corresponding to each harmonic current source, the source current estimation model including an objective function, the objective function being used to constrain the mutual information between the plurality of harmonic source currents to be minimum.

[0052] Among them, the server 104 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0053] In an exemplary embodiment, as shown in Figure 2 , a harmonic source current estimation method is provided. Taking the server 104 in Figure 1 as an example, the method includes the following steps 202 to 204. Among them:

[0054] Step 202, obtaining the harmonic observation currents corresponding to a plurality of harmonic load nodes.

[0055] Figure 3 It is the Norton equivalent circuit diagram of the centralized multi-harmonic source system. Referring to Figure 3 , and represent the nonlinear loads of the system side and the user side harmonic nodes, respectively; and are the harmonic impedances of the i-th user node on the system side and the user side respectively. The total harmonic current emitted by the node without the harmonic measurement device is the background harmonic current, that is, Figure 3 I0 in , and Z0 represents the equivalent harmonic impedance of these nodes. pcc and I pcc are the harmonic voltage and current measured at the point of common coupling (PCC), respectively; ~ It is the harmonic observation current observed by the harmonic monitoring device at the harmonic load node. coi and I pcc It is the harmonic current actually measured by the harmonic monitoring device at the harmonic load node, that is, the port current in the Norton equivalent circuit.

[0056] Step 204 : Input the multiple harmonic observation currents into the source current estimation model to obtain the harmonic source current corresponding to each harmonic current source.

[0057] The source current estimation model includes an objective function, which is used to constrain the mutual information between multiple harmonic source currents to be minimum.

[0058] In a centralized multi-harmonic source system, the harmonic source current is I ci , I s I and I0 are the current sources in the Norton equivalent circuit of the harmonic load node, representing the harmonic emission capability of the nonlinear load, which is an inherent property of the harmonic load. Each harmonic source current is only related to the harmonic observation current of its node and the harmonic observation voltage at the PCC. This is an inherent constraint that needs to be followed when estimating the harmonic source current based on the harmonic observation current. Figure 3 Harmonic observation current I coi For example, the relationship between it and each harmonic source current is:

[0059] ,

[0060] Among them, Z p is the parallel impedance of all harmonic impedances; Z p-i is the parallel impedance of all harmonic impedances except node i. When there is only one harmonic load node in the system, that is, N=1, the harmonic observation current I co1 That is the harmonic source current I c1 However, when there are multiple harmonic load nodes in the system, the harmonic observation current I co1 Is the equivalent harmonic current source I of all harmonic loads c1 ~ I cN Harmonic current superimposed on this node.

[0061] Mutual Information is a measure of the degree of mutual dependence between random variables, which means the amount of information contained in one random variable about another random variable. The objective function in the embodiments of the present application can be understood as finding a set of harmonic source currents, so that the mutual information between the harmonic source currents reaches a minimum.

[0062] In the above harmonic source current estimation method, the difference between the harmonic source current and the harmonic observation current is explicitly distinguished in the process of estimating the harmonic source current, and the harmonic source current separation and estimation are realized based on the minimum mutual information criterion. Compared with the harmonic source current estimation in the prior art using multivariate linear regression method or complex independent component analysis method, the harmonic source current estimation method in the embodiments of the present application can not only reflect the linear correlation between the harmonic source currents, but also reflect the nonlinear correlation, so that when dealing with the harmonic problem generated by complex nonlinear load, the harmonic source current estimation method has higher robustness and accuracy.

[0063] In an exemplary embodiment, based on Figure 2 As shown in the embodiment shown in Figure 4 , the plurality of harmonic observation currents are input into the source current estimation model to obtain the harmonic source currents corresponding to each harmonic current source, comprising:

[0064] Step 402, constructing an initial mutual information ratio matrix according to each harmonic source current to be solved.

[0065] Wherein, the mutual information between the harmonic source currents I c1 and I c2 can be calculated by the following formula:

[0066] ,

[0067] Wherein, e(I c1 ) and e(I c2 ) are the entropies of the harmonic source currents I c1 and I c2 ; e(I c1， I c2 ) is the joint entropy of the harmonic source currents I c1 and I c2 .

[0068] Since has no dimension, the ratio of to the sum of the information carried by I c1 and I c2 is used to measure I c1 and I c2a dependency between the harmonic sources, which is referred to as the Mutual Information Ratio (MIR) below. The MIR between all harmonic sources is denoted as m 12 (N+1)N Then m ij is defined as:

[0069] ,

[0070] The initial MIR matrix M between the harmonic source currents can be obtained as:

[0071] ,

[0072] In the initial MIR matrix M, the off-diagonal elements satisfy: m ij = m ji . And since e(x) = e (x;x), the diagonal elements of the matrix M are 0.5.

[0073] At step 404, the initial MIR matrix is optimized based on the objective function and the multiple harmonic observation currents, to obtain a target MIR matrix.

[0074] In one possible implementation, step 404 can further include:

[0075] At step 4042, a reference harmonic source current and a to-be-optimized harmonic source current are determined from the to-be-solved harmonic source currents based on the initial MIR matrix.

[0076] In some embodiments, step 4042 can further include: performing a row-wise summation on the initial MIR matrix to obtain multiple row-wise sums; selecting a harmonic source current corresponding to a maximum row-wise sum from the multiple row-wise sums as the reference harmonic source current I st ; and determining a maximum MIR from the multiple MIRs corresponding to the reference harmonic source current, and selecting a harmonic source current corresponding to the maximum MIR as the to-be-optimized harmonic source current I op .

[0077] wherein the row-wise sum represents a sum of the MIRs of one harmonic source current with respect to all other harmonic source currents, and can be understood as a total dependency degree between the harmonic current source corresponding to the harmonic source current and other harmonic current sources. The selection manner of the reference harmonic source current and the to-be-optimized harmonic source current can be expressed as:

[0078] ,

[0079] wherein, is a row coordinate corresponding to the maximum row-wise sum; is a column coordinate corresponding to the maximum MIR.​ In the embodiment of the present application, a pair of harmonic source currents with the highest correlation in the current system can be identified as the reference harmonic source current I st and the harmonic source current to be optimized I op , thereby improving the efficiency of the optimization solution process.

[0080] Step 4044 , optimizing the harmonic source current to be optimized using the objective function, the harmonic observation current, and the reference harmonic source current, to obtain an optimized mutual information ratio corresponding to the harmonic source current to be optimized.

[0081] Among them, the harmonic source current I op The essence of the optimization process is to reduce I st and I op Assume that in a certain round of optimization, the nth and mth harmonic source currents are selected as I st and I op , then the goal of this round of optimization is to make the mutual information ratio m nm Not higher than the target value J nm , take the average mutual information ratio of other nodes as the optimization target value J nm , as follows:

[0082] .

[0083] Step 4046: In the initial mutual information ratio matrix, the mutual information ratio corresponding to the harmonic source current to be optimized is updated using the optimized mutual information ratio to obtain an intermediate mutual information ratio matrix.

[0084] Step 4048, returning to the step of determining the reference harmonic source current and the harmonic source current to be optimized from the harmonic source currents to be solved based on the initial mutual information ratio matrix, until all the harmonic source currents to be solved are optimized, and the target mutual information ratio matrix is ​​obtained.

[0085] Step 406 : Calculate and obtain the current of each harmonic source according to the target mutual information ratio matrix.

[0086] In an embodiment of the present application, the reference harmonic source current and the harmonic source current to be optimized are determined by a row-by-row summation and maximum mutual information ratio selection mechanism, ensuring that the optimization process can gradually reduce the dependency between the harmonic current sources and eventually converge to the optimal solution, effectively avoiding the problems of excessive computational complexity and unstable convergence caused by a one-time overall solution, thereby achieving a gradual and accurate estimation of the current of each harmonic source and improving the accuracy and robustness of the harmonic source current estimation.

[0087] In an exemplary embodiment, based on Figure 4 In the embodiment shown, the objective function includes the admittance parameter;Figure 5 As shown, the target function, the harmonic observation current and the reference harmonic source current are used to optimize the to-be-optimized harmonic source current, to obtain an optimized mutual information ratio corresponding to the to-be-optimized harmonic source current, including:

[0088] In step 502, based on the reference harmonic source current and a pre-established current relationship matrix, a plurality of sample admittance parameters are generated, the current relationship matrix including the relationship between the harmonic source current and the admittance parameters and the harmonic observation current.

[0089] Wherein, for a multi-harmonic source system installed with N harmonic measurement devices, the relationship between the harmonic source current and the harmonic observation current can be represented as a current relationship matrix as follows:

[0090] ,

[0091] Wherein, , , A is a matrix composed of admittance parameters The current relationship matrix can be further represented as:

[0092] ,

[0093] Wherein, the admittance parameter is the harmonic admittance of the harmonic load node, that is:

[0094] .

[0095] In the process of optimizing the to-be-optimized harmonic source current, p groups of sample admittance parameter samples are generated .

[0096] In step 504, the covariance of each sample admittance parameter is calculated by using a preset Gaussian model, to obtain the covariance corresponding to each sample admittance parameter.

[0097] Wherein, the Gaussian model is used to calculate the covariance by using a Gaussian kernel function, and the covariance k ij is calculated according to the following formula:

[0098] ,

[0099] Wherein, , are the real part and the imaginary part of the sample admittance parameter sample , respectively; , are the real part and the imaginary part of the sample admittance parameter sample , respectively.

[0100] Step 506, determining the intermediate admittance parameter from the sample admittance parameter by using the preset acquisition function and each covariance.

[0101] In a possible implementation, step 506 can further include: respectively calculating the expectation value and the variance corresponding to each covariance; substituting the expectation value and the variance into the acquisition function, and taking the sample admittance parameter corresponding to the covariance at which the value of the acquisition function is maximum as the intermediate admittance parameter.

[0102] Determining the intermediate admittance parameter according to the acquisition function AF The determination process can be represented as:

[0103] ,

[0104] In the implementation of the present application, the principle of determining the intermediate admittance parameter is to comprehensively evaluate the expectation and the variance of the parameter , which respectively represent the average level and the uncertainty of the mutual information ratio corresponding to the parameter .

[0105] Step 508, performing calculation and processing on the intermediate admittance parameter by using the current relationship matrix and the harmonic observation current, obtaining the intermediate mutual information ratio corresponding to the intermediate admittance parameter, and updating the Gaussian model based on the intermediate admittance parameter to obtain the updated Gaussian model.

[0106] In some embodiments, due to the lack of prior information, it is assumed that the mutual information ratio ~ corresponding to the sample admittance parameter ~ obeys a multi-dimensional Gaussian distribution with zero expectation, which can be represented as:

[0107] ,

[0108] wherein K is a covariance matrix composed of each covariance, and can be represented as:

[0109] ,

[0110] The process of updating the Gaussian model by using the intermediate admittance parameter includes adding the mutual information ratio corresponding to the intermediate admittance parameter to the joint Gaussian distribution , and the joint Gaussian distribution can be specifically represented as:

[0111] ,

[0112] wherein , the intermediate admittance parameter obeys the following Gaussian distribution:

[0113] ,

[0114] wherein, , .

[0115] Step 510, return to execute the step of generating a plurality of sample admittance parameters, terminate the iteration in the case that the intermediate mutual information ratio corresponding to the intermediate admittance parameter is less than the ratio threshold, output the intermediate admittance parameter at the termination of the iteration as the target admittance parameter, and the intermediate mutual information ratio at the termination of the iteration as the optimized mutual information ratio.

[0116] Figure 6 The optimization process and the logical relationship of each parameter in the optimization process are shown. As shown in Figure 6 In the embodiment of the present application, in order to solve the problem that the mutual information ratio calculation complexity is high and it is difficult to use gradient descent method, a non-gradient optimization method such as Gaussian model and acquisition function is adopted, so that the optimization process can effectively find the minimum point of the mutual information ratio without relying on gradient information, thereby improving the practicability and solving efficiency of the algorithm.

[0117] In an exemplary embodiment, as Figure 7 shown, a harmonic source current estimation method is provided, which includes the following steps 701 to 713. Among them:

[0118] Step 701, obtaining a plurality of harmonic load node corresponding harmonic observation currents.

[0119] Step 702, constructing an initial mutual information ratio matrix according to each harmonic source current to be solved.

[0120] Step 703, determining a reference harmonic source current and a harmonic source current to be optimized from each harmonic source current to be solved based on the initial mutual information ratio matrix.

[0121] Among them, step 703 can further include: summing the initial mutual information ratio matrix row by row to obtain a plurality of row sums; selecting the harmonic source current corresponding to the maximum row sum from the plurality of row sums as the reference harmonic source current; determining the maximum mutual information ratio from the plurality of mutual information ratios corresponding to the reference harmonic source current, and selecting the harmonic source current corresponding to the maximum mutual information ratio as the harmonic source current to be optimized.

[0122] Step 704, generating a plurality of sample admittance parameters based on the reference harmonic source current and a pre-established current relationship matrix, the current relationship matrix including the relationship between the harmonic source current and the admittance parameter and the harmonic observation current.

[0123] Step 705, covariance of each sample admittance parameter is calculated by using a preset Gaussian model, and a covariance corresponding to each sample admittance parameter is obtained.

[0124] Step 706, an intermediate admittance parameter is determined from the sample admittance parameters by using a preset collection function and each covariance.

[0125] The step 706 can further include: respectively calculating an expected value and a variance corresponding to each covariance; substituting the expected value and the variance into the collection function; and taking the sample admittance parameter corresponding to the covariance at which the value of the collection function is maximum as the intermediate admittance parameter.

[0126] Step 707, the intermediate admittance parameter is calculated and processed by using a current relationship matrix and a harmonic observation current, an intermediate mutual information ratio corresponding to the intermediate admittance parameter is obtained, and the Gaussian model is updated based on the intermediate admittance parameter, and an updated Gaussian model is obtained.

[0127] Step 708, it is judged whether the intermediate mutual information ratio corresponding to the intermediate admittance parameter is less than a ratio threshold value.

[0128] Step 709, in the case that the intermediate mutual information ratio corresponding to the intermediate admittance parameter is less than the ratio threshold value, the iteration is terminated, the intermediate admittance parameter at the time of termination of the iteration is output as a target admittance parameter, and the intermediate mutual information ratio at the time of termination of the iteration is output as an optimized mutual information ratio.

[0129] Step 710, in the initial mutual information ratio matrix, the mutual information ratio corresponding to the harmonic source current to be optimized is updated by using the optimized mutual information ratio, and an intermediate mutual information ratio matrix is obtained.

[0130] Step 711, it is judged whether all the harmonic source currents to be solved are optimized.

[0131] Step 712, in the case that all the harmonic source currents to be solved are optimized, a target mutual information ratio matrix is obtained.

[0132] Step 713, each harmonic source current is calculated according to the target mutual information ratio matrix.

[0133] In an exemplary embodiment, a MATLAB is used to build a system as shown in FIG. 1. Figure 3The circuit model of the two harmonic load nodes shown verifies the method proposed in the embodiments of the present application. Through simulation experiments, the relative amplitude errors of the method proposed in the embodiments of the present application for harmonic load node 1, harmonic load node 2 and the system side are 8.51%, 6.48% and 5.80% respectively. In the case of keeping other simulation parameters unchanged, the amplitudes of the background harmonics are respectively amplified to 1.5, 2.0 and 2.5 times of the original values, in order to test the influence of the fluctuation of the background harmonic current on the method proposed in the embodiments of the present application. The average relative errors of the method proposed in the embodiments of the present application are 5.29%, 6.1% and 7.93% respectively, which are always less than 8%, thus proving that the method is less affected by the fluctuation of the background harmonic. This is because the method proposed separates the harmonic current source according to the statistical characteristic of mutual information, without making assumptions and constraints on the relative size relationship of the harmonic currents of the harmonic load and the background harmonic source.

[0134] It should be understood that, although the steps in the flowcharts involved in the above embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, at least part of the steps in the flowcharts involved in the above embodiments can include multiple steps or stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but can be alternately executed with at least part of other steps or stages. It can be understood that the steps in different embodiments can be freely combined as needed, and various non-contradictory schemes formed by the combination are within the scope of protection of the present application.

[0135] Based on the same inventive concept, the embodiments of the present application also provide a harmonic source current estimation device for implementing the harmonic source current estimation method described above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so the specific limitations in one or more harmonic source current estimation device embodiments provided below can refer to the limitations of the harmonic source current estimation method in the above text, which will not be repeated here.

[0136] In one exemplary embodiment, as shown in Figure 8 A harmonic source current estimation device is provided, comprising: a data acquisition module 802 and a current estimation module 804, wherein:

[0137] The data acquisition module 802 is configured to acquire harmonic observation currents corresponding to a plurality of harmonic load nodes.

[0138] The current estimation module 804 is configured to input the plurality of harmonic observation currents into a source current estimation model to obtain harmonic source currents corresponding to the plurality of harmonic sources, and the source current estimation model comprises an objective function configured to constrain mutual information among the plurality of harmonic source currents to be minimum.

[0139] In one of the embodiments, the current estimation module 804 is further configured to construct an initial mutual information ratio matrix according to the plurality of harmonic source currents to be solved;

[0140] The initial mutual information ratio matrix is optimized and solved based on the objective function and the plurality of harmonic observation currents to obtain a target mutual information ratio matrix.

[0141] The plurality of harmonic source currents are calculated according to the target mutual information ratio matrix.

[0142] In one of the embodiments, the current estimation module 804 is further configured to determine a reference harmonic source current and a harmonic source current to be optimized from the plurality of harmonic source currents to be solved based on the initial mutual information ratio matrix; optimize the harmonic source current to be optimized by using the objective function, the harmonic observation current and the reference harmonic source current to obtain an optimized mutual information ratio corresponding to the harmonic source current to be optimized; update, in the initial mutual information ratio matrix, a mutual information ratio corresponding to the harmonic source current to be optimized by using the optimized mutual information ratio to obtain an intermediate mutual information ratio matrix; return to execute the step of determining the reference harmonic source current and the harmonic source current to be optimized from the plurality of harmonic source currents to be solved based on the initial mutual information ratio matrix until all the harmonic source currents to be solved are optimized to obtain the target mutual information ratio matrix.

[0143] In one of the embodiments, the current estimation module 804 is further configured to perform row-wise summation on the initial mutual information ratio matrix to obtain a plurality of row-wise sums; select a harmonic source current corresponding to a maximum row-wise sum from the plurality of row-wise sums as the reference harmonic source current; and determine a maximum mutual information ratio from a plurality of mutual information ratios corresponding to the reference harmonic source current, and select a harmonic source current corresponding to the maximum mutual information ratio as the harmonic source current to be optimized.

[0144] In one of the embodiments, the target function includes the admittance parameter; the current estimation module 804 is further configured to generate a plurality of sample admittance parameters based on the reference harmonic source current and a pre-established current relationship matrix, the current relationship matrix including a relationship between the harmonic source current and the admittance parameter and the harmonic observation current; perform covariance calculation on each sample admittance parameter by using a pre-established Gaussian model to obtain a covariance corresponding to each sample admittance parameter; determine an intermediate admittance parameter from the sample admittance parameters by using a pre-established acquisition function and each covariance; perform calculation and processing on the intermediate admittance parameter by using the current relationship matrix and the harmonic observation current to obtain an intermediate mutual information ratio corresponding to the intermediate admittance parameter, and update the Gaussian model based on the intermediate admittance parameter to obtain an updated Gaussian model; return to perform the step of generating the plurality of sample admittance parameters, and terminate iteration in a case where the intermediate mutual information ratio corresponding to the intermediate admittance parameter is less than a ratio threshold value, and output the intermediate admittance parameter at the time of termination of iteration as the target admittance parameter and the intermediate mutual information ratio at the time of termination of iteration as the optimized mutual information ratio.

[0145] In one of the embodiments, the current estimation module 804 is further configured to respectively calculate an expected value and a variance corresponding to each covariance; and substitute the expected value and the variance into the acquisition function, and take the sample admittance parameter corresponding to the covariance at which the value of the acquisition function is maximum as the intermediate admittance parameter.

[0146] Each of the modules in the harmonic source current estimation device can be realized by software, hardware, or a combination thereof, in whole or in part. Each of the modules can be embedded in or independent of a processor in a computer device in a hardware form, or can be stored in a memory in a computer device in a software form, so as to be called and executed by a processor to perform operations corresponding to each of the modules.

[0147] In one exemplary embodiment, a computer device is provided, which can be a server, and an internal structure diagram of the computer device can be as shown in Figure 9 The computer device includes a processor, a memory, an input / output interface (I / O), and a communication interface. The processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. 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, a computer program, and a database. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The database of the computer device is configured to store the harmonic observation current. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to communicate with external terminals through a network connection. The computer program is executed by the processor to implement a harmonic source current estimation method.

[0148] Those skilled in the art can understand, Figure 9 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0149] In an exemplary embodiment, a computer device is also provided, including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps in the above method embodiments.

[0150] In an exemplary embodiment, a computer readable storage medium is provided, storing a computer program, and the computer program is executed by a processor to implement the steps in the above method embodiments.

[0151] In an exemplary embodiment, a computer program product is provided, including a computer program, and the computer program is executed by a processor to implement the steps in the above method embodiments.

[0152] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing relevant hardware. The computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, the processes of the above-mentioned embodiment methods can be included. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. The non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. The volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, the RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., without being limited thereto.

[0153] The technical features of the above embodiments can be combined arbitrarily. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combinations of the technical features do not exist contradictory, it should be considered as the scope of the present application.

[0154] The above embodiments only express several implementation ways of the present application, and the description is specific and detailed, but it should not be understood as a limitation to the patent scope of the present application. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, several modifications and improvements can be made, which all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A harmonic source current estimation method, characterized in that: The method comprises: Obtain harmonic observation currents corresponding to multiple harmonic load nodes; The plurality of harmonic observation currents are input into a source current estimation model to obtain a harmonic source current corresponding to each harmonic current source. The source current estimation model includes an objective function, which is used to constrain the mutual information between the plurality of harmonic source currents to be minimum.

2. The method according to claim 1, characterized in that Inputting the plurality of harmonic observation currents into a source current estimation model to obtain harmonic source currents corresponding to each harmonic current source includes: Constructing an initial mutual information ratio matrix based on the currents of each harmonic source to be solved; Based on the objective function and the plurality of harmonic observation currents, the initial mutual information ratio matrix is ​​optimized and solved to obtain a target mutual information ratio matrix; The harmonic source currents are obtained by calculation according to the target mutual information ratio matrix.

3. The method according to claim 2, characterized in that The optimizing and solving the initial mutual information ratio matrix based on the objective function and the plurality of harmonic observation currents to obtain a target mutual information ratio matrix includes: Determining a reference harmonic source current and a harmonic source current to be optimized from the harmonic source currents to be solved based on the initial mutual information ratio matrix; Optimizing the harmonic source current to be optimized using the objective function, the harmonic observation current, and the reference harmonic source current to obtain an optimized mutual information ratio corresponding to the harmonic source current to be optimized; In the initial mutual information ratio matrix, the mutual information ratio corresponding to the harmonic source current to be optimized is updated using the optimized mutual information ratio to obtain an intermediate mutual information ratio matrix; Return to executing the step of determining a reference harmonic source current and a harmonic source current to be optimized from each harmonic source current to be solved based on the initial mutual information ratio matrix, until all harmonic source currents to be solved are optimized, and obtain the target mutual information ratio matrix.

4. The method according to claim 3, characterized in that The determining of a reference harmonic source current and a harmonic source current to be optimized from each harmonic source current to be solved based on the initial mutual information ratio matrix includes: Summing the initial mutual information ratio matrix row by row to obtain a plurality of row by row sums; Selecting the harmonic source current corresponding to the largest row-by-row sum from the plurality of row-by-row sums as the reference harmonic source current; A maximum mutual information ratio is determined from a plurality of mutual information ratios corresponding to the reference harmonic source current, and the harmonic source current corresponding to the maximum mutual information ratio is used as the harmonic source current to be optimized.

5. The method according to claim 3, characterized in that The objective function includes an admittance parameter; optimizing the harmonic source current to be optimized using the objective function, the harmonic observation current, and the reference harmonic source current to obtain an optimized mutual information ratio corresponding to the harmonic source current to be optimized includes: generating a plurality of sample admittance parameters based on the reference harmonic source current and a pre-established current relationship matrix, wherein the current relationship matrix includes a relationship between the harmonic source current, the admittance parameters, and the harmonic observation current; Calculating the covariance of each of the sample admittance parameters using a preset Gaussian model to obtain the covariance corresponding to each of the sample admittance parameters; Determining an intermediate admittance parameter from the sample admittance parameters using a preset acquisition function and the covariances; Calculating the intermediate admittance parameter using the current relationship matrix and the harmonic observation current to obtain an intermediate mutual information ratio corresponding to the intermediate admittance parameter, and updating the Gaussian model based on the intermediate admittance parameter to obtain an updated Gaussian model; Return to the step of generating multiple sample admittance parameters, terminate the iteration when the intermediate mutual information ratio corresponding to the intermediate admittance parameter is less than the ratio threshold, output the intermediate admittance parameter at the time of termination of the iteration as the target admittance parameter, and output the intermediate mutual information ratio at the time of termination of the iteration as the optimized mutual information ratio.

6. The method according to claim 5, characterized in that The determining of the intermediate admittance parameter from the sample admittance parameters by using a preset acquisition function and each of the covariances includes: Calculate the expected value and variance corresponding to each covariance respectively; The expected value and the variance are substituted into the acquisition function, and the sample admittance parameter corresponding to the covariance when the value of the acquisition function is maximum is used as the intermediate admittance parameter.

7. A harmonic source current estimation device, characterized in that: The device comprises: A data acquisition module is used to obtain harmonic observation currents corresponding to multiple harmonic load nodes; The current estimation module is used to input the multiple harmonic observation currents into the source current estimation model to obtain the harmonic source current corresponding to each harmonic current source. The source current estimation model includes an objective function, which is used to constrain the mutual information between the multiple harmonic source currents to be minimum.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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