Power distribution network broadband interference tracing method and system capable of resisting strong noise influence

Abstract

The invention provides a power distribution network broadband interference traceability method and system resistant to strong noise influence. The method comprises the steps of obtaining a voltage incidence matrix, a vector of a to-be-estimated quantity and a vector of a three-phase harmonic current; establishing a parameter estimation equation by using the voltage incidence matrix, the vector of the to-be-estimated quantity and the vector of the three-phase harmonic current, and processing the parameter estimation equation to establish a variable weight least square expression; iteratively solving parameters by aiming at the variable weight least square expression, and calculating a residual vector generated by k-th iteration; if the residual vector is within a tolerance range, outputting line parameters under harmonic waves estimated this time, obtaining self-impedance and earth admittance of each node, obtaining a harmonic wave position index by using a fuzzy logic method, inputting the harmonic wave position index into a statistical parameter calculator with abnormal values removed, obtaining a sequence value after the abnormal values are removed, and calculating a threshold value; and filtering the harmonic position index lower than the threshold value, and judging the node where the interference source is located.

Description

Technical Field

[0001] The present invention belongs to the technical field of broadband interference tracing of distribution networks, and in particular to a broadband interference tracing method and system for distribution networks that are resistant to strong noise influence. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Power electronic equipment will also generate harmonics when the power system is operating normally. Since the harmonics emitted by these devices have multiple orders, such as 3rd, 7th, and 11th harmonics, they are called broadband interference sources.

[0004] The harmonic source tracing method based on fuzzy logic can be used for convenient and accurate tracing, but this method relies on accurate distribution network parameters, especially broadband impedance parameters. Inaccurate parameters may lead to tracing failure. The existing distribution network line parameter estimation is only for fundamental wave parameters, and there is a lack of broadband impedance parameter estimation methods.

[0005] Ohm's law can be used to transform the parameter estimation of the distribution network into a series of linear model problem solving. The traditional least squares method (OLS) fits the data by minimizing the residual sum of squares. When there is strong noise interference in the broadband measurement data, the method of minimizing the residual sum of squares will lead to large errors in the estimated value, that is, the least squares method is less robust to outliers.

[0006] In order to deal with the impact of outliers, the weighted least squares method (WLS) is generally used for parameter estimation. Traditional methods often use fixed weights. However, the fixed weight method has two major disadvantages: first, fixed weights often require the numbering of outliers in the measurement sequence, which is often difficult to achieve; second, for different measurement data, the distribution of internal elements is often different, and a fixed value is difficult to process all measurement data, resulting in low accuracy in identifying outliers and poor processing capabilities. Some scholars have realized that weights should be adaptive to the statistical laws of the sequence, but no corresponding weight adaptive methods have been proposed for broadband measurement data and parameter estimation.

[0007] Considering the universality of outliers in broadband measurement data, one of the problems solved by the present application is: how to adaptively process the weights with strong robustness to outliers to improve the accuracy of distribution network line parameter estimation.

[0008] In addition, in the prior art, after obtaining the line parameter data under each harmonic, the fuzzy logic method can be used to locate the broadband interference source. The result of the fuzzy logic method is represented by the harmonic location index (HLI). The size of the HLI can be used as a basis for judging the existence of the interference source. However, under certain harmonic orders, the amplitude of the harmonic voltage and current is small, and the positive and negative sign characteristics of the active power and reactive power are not obvious, which may make the HLI of the interference source not prominent in the HLI of all nodes, affecting the judgment of the interference source. Therefore, another technical problem to be solved by this application is: how to locate the weak interference source, and then accurately judge the node where the interference source is located in the HLI of all nodes. Summary of the invention

[0009] In order to overcome the above-mentioned deficiencies of the prior art, the present invention provides a distribution network broadband interference tracing method that is resistant to strong noise influence and can accurately determine the node where the interference source is located.

[0010] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0011] In the first aspect, a method for tracing the source of broadband interference in a distribution network that is resistant to strong noise is disclosed, comprising:

[0012] Obtaining a voltage correlation matrix, a vector of quantities to be estimated, and a three-phase harmonic current vector;

[0013] The voltage correlation matrix, the vector of the quantity to be estimated and the three-phase harmonic current vector are used to establish the parameter estimation equation, and the parameter estimation equation is processed to establish the variable weight least square expression;

[0014] Iterate and solve the parameters for the variable weight least squares expression, and calculate the residual vector generated by the kth iteration;

[0015] If the residual vector is within the tolerance range, the line parameters under the estimated harmonics are output, the self-impedance and admittance to ground of each node are obtained, the harmonic position index is obtained using the fuzzy logic method, and the harmonic position index is input into the statistical parameter calculator for removing outliers. The sequence value is obtained after removing the outliers, the threshold value is calculated, the harmonic position index below the threshold value is filtered out, and the node where the interference source is located is determined.

[0016] As a further technical solution, the process of obtaining the voltage correlation matrix, the vector of the quantity to be estimated and the three-phase harmonic current vector is:

[0017] Obtain the harmonic voltage and current data at both ends of the three-phase line;

[0018] A first voltage matrix and a second voltage matrix are established based on the harmonic voltage data at both ends of the three-phase line, and the first voltage matrix and the second voltage matrix constitute a voltage correlation matrix;

[0019] A three-phase harmonic current vector is established based on the harmonic current data at both ends of the three-phase line;

[0020] A vector of quantities to be estimated is established according to the physical parameters of the three-phase line.

[0021] As a further technical solution, if the residual vector is not within the tolerance range, then:

[0022] Calculate the indicators, establish parameter selection principles based on the indicators, use the parameter selection principles to determine the parameters, input the residual vector into the statistical parameter calculator for removing outliers, obtain the sequence values ​​after removing outliers, use the parameters and sequence values ​​to determine the hyperparameters of this iteration, calculate the weight values ​​based on the hyperparameters, fill in the weight matrix, and re-estimate the line parameters under harmonics until the residual vector is within the tolerance range.

[0023] As a further technical solution, the process of processing the input data by the statistical parameter calculator for removing outliers is as follows:

[0024] For input data containing outliers, calculate the mean and standard deviation of the input data;

[0025] The threshold value of this iteration is determined based on the mean and standard deviation of the input data;

[0026] Determine whether there are elements greater than the threshold value in the residual vector. If so, remove the elements greater than the threshold value. If not, directly obtain the mean and standard deviation of the sequence without abnormal data.

[0027] As a further technical solution, the fuzzy logic method is used to obtain the harmonic position index, specifically:

[0028] According to the multiple harmonic active power, reactive power of a node and the obtained node self-impedance and ground admittance data, the harmonic position index of the interference source at the node can be obtained in the fuzzy reasoning system according to the positive and negative relationship of their signs.

[0029] As a further technical solution, after filtering out the harmonic position index below the threshold value, there are only a few larger values ​​in the harmonic position index, and the interference source can be found by querying the node number corresponding to the larger value.

[0030] In the second aspect, a distribution network broadband interference tracing system resistant to strong noise is disclosed, including:

[0031] The data acquisition module is configured to: acquire a voltage correlation matrix, a vector of quantities to be estimated, and a three-phase harmonic current vector;

[0032] The variable weight least square expression establishment module is configured to: establish a parameter estimation equation using a voltage correlation matrix, a vector of quantities to be estimated and a three-phase harmonic current vector, and process the parameter estimation equation to establish a variable weight least square expression;

[0033] The residual vector calculation module is configured to: iteratively solve the parameters for the variable weight least squares expression and calculate the residual vector generated by the kth iteration;

[0034] The node judgment module where the interference source is located is configured as follows: if the residual vector is within the tolerance range, the line parameters under the harmonics estimated this time are output, the self-impedance and admittance to ground of each node are obtained, the harmonic position index is obtained by using the fuzzy logic method, the harmonic position index is input into the statistical parameter calculator for removing outliers, the sequence value is obtained after removing the outliers, the threshold value is calculated, the harmonic position index below the threshold value is filtered out, and the node where the interference source is located is judged.

[0035] One or more of the above technical solutions have the following beneficial effects:

[0036] The technical solution of the present invention provides a distribution network broadband interference tracing method that is resistant to strong noise. It can use broadband synchronous measurement values ​​containing strong noise to accurately estimate the line parameters of the distribution network, and use the obtained line parameters under each harmonic to locate the harmonic source in the distribution network using fuzzy logic method; and for scenarios where weak interference sources exist, it can accurately determine the node where the interference source is located.

[0037] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0039] Figure 1 The present invention is an overall method flow chart of the embodiment of the present invention;

[0040] Figure 2 The flowchart of the statistical parameter calculator for removing outliers according to the embodiment of the present invention. DETAILED DESCRIPTION

[0041] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0042] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0043] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0044] Embodiment 1

[0045] This embodiment discloses a method for tracing the source of broadband interference in a distribution network that is resistant to strong noise, including:

[0046] Step 1: Build the model

[0047] Broadband measuring devices are installed at both ends of a certain three-phase line (respectively called terminal 1 and terminal 2) to obtain the voltage and current data of each harmonic.

[0048] As an implementation method, the broadband measurement device can be an existing measurement device, including: the broadband measurement device (synchronized wideband measurement unit, WMU) is mainly composed of a high-speed sampling module, a synchronous clock module, a broadband identification module and a high-speed communication module, and the measurement implementation process is: the high-speed sampling module obtains the voltage and current signals at the WMU installation node, the synchronous clock module receives the synchronous timing signal sent by the synchronous satellite, and the broadband identification module quickly identifies the broadband components of the collected voltage and current. Finally, the node voltage components with synchronous time and the current components of the line connected to the node are obtained, and the high-speed communication module sends these data to the master station.

[0049] According to actual needs, establish the estimated quantity vector X under the hth harmonic as shown in formula (1.1): h .

[0050] The h-order harmonic vector X h , consider B h and Y h To save computing resources and speed up the calculation and consider the convenience of subsequent use, only the upper triangular part of the matrix is ​​split out and rearranged into column vectors b h and h , and by b h and h Arrange in X h , taking into account the line parameters needed for broadband interference tracing.

[0051]

[0052] In the formula, They represent the harmonic impedance of the three-phase lines a, b, and c respectively. They represent the hth harmonic impedance between phases, B h represents the inverse matrix of the impedance matrix; It represents the h-th earth admittance of the three-phase line a, b, c, represents the hth phase-to-phase admittance, Y h is the admittance matrix.

[0053] Fill the harmonic voltage data at both ends of the line into the measurement vector, and the measurement vector is shown in formula (1.2):

[0054]

[0055] Where: represents the hth harmonic voltage matrix at line 1, represents the hth harmonic voltage matrix at line 2 terminal; They represent the hth harmonic voltage between the three phases a, b, c at terminal 1 and the ground respectively; They represent the hth harmonic voltage between the three phases a, b, and c at terminal 2 and the ground respectively.

[0056] According to formula (1.3), The voltage correlation matrix V h , which is convenient for establishing expressions for line parameter estimation.

[0057]

[0058] The h-order three-phase harmonic current data flowing from terminal 1 to the line and the h-order three-phase harmonic current data flowing from the line to segment 2 are filled into the measurement vector, and the measurement vector is shown in formula (1.4):

[0059]

[0060] Where: I h represents the hth order three-phase harmonic current vector, It represents the hth harmonic current of three phases a, b, c flowing from terminal 1 to the line; It represents the hth harmonic current of three phases a, b, and c flowing from the line to terminal 2.

[0061] Step 2: Establish parameter estimation equation

[0062] According to Ohm's law and Kirchhoff's law, the estimation equation can be expressed as:

[0063] V h ·X h =I h (0.5)

[0064] Decompose the real and imaginary parts of each part in equation (0.5) and use and Indicates that they include V h , X h ,I h The real and imaginary parts of , that is:

[0065]

[0066] According to formula (1.7), the estimation equation of single harmonic is expanded to multi-dimensional:

[0067]

[0068] Name the parts of equation (0.7) as I, V, and X respectively and introduce the deviation value vector ε:

[0069] ε=V·XI(0.8)

[0070] Establish the variable weight least squares expression (1.9), where W is the adaptive weight matrix, and its diagonal element is the weight of the i-th residual, as shown in formula (1.10)

[0071] X=(V T WV) -1 V T WI (0.9)

[0072] W ii =Θ i (0.10)

[0073] The adaptive weight matrix W is obtained according to (1.10). W is a diagonal matrix, the diagonal elements are obtained from (1.10), and the non-diagonal elements are 0.

[0074] Step 3: Iterate and solve the parameters of formula (1.8). The iterative process is the process of minimizing the deviation value vector ε.

[0075] Step 3.1: Normalization of residual vector

[0076] The residual vector ε generated by the kth iteration k Normalize all elements of to get the normalized residual

[0077]

[0078] The normalization parameter std satisfies formula (1.12)

[0079]

[0080] Among them: MAD means median absolute deviation, median means the operation of taking the median of the data.

[0081] Step 3.2: Solving important indicators

[0082] For ε n Conduct statistical law analysis and solve the important indicators IDR and IPR90 according to formula (1.13) and formula (1.14).

[0083] IDR and IPR90 are interquartile range and 5-95th percentile range respectively, and the calculation methods are shown in (1.13) and (1.14). Their numerical values ​​can reflect the number and intensity of outliers.

[0084] IDR=D9-D1(0.13)

[0085] Where: D1 is the first quantile. For a sequence of n points, the data at position (n+1)×0.1 after ascending order is D1; ​​D9 is the ninth quantile. For a sequence of n points, the data at position (n+1)×0.9 is D9. When (n+1)×0.1 or (n+1)×0.9 is not an integer, linear interpolation is used to obtain D1 and D9.

[0086] IPR90=P95-P5(0.14)

[0087] Where: P5 is the 5% quantile. For a sequence of n points, the data at position (n+1)×0.05 after ascending order is P5; P95 is the 95% quantile. For a sequence of n points, the data at position (n+1)×0.95 is P95. When (n+1)×0.05 or (n+1)×0.95 is not an integer, linear interpolation is required to obtain P5 and P95.

[0088] Step 3.3: Solve the normal value through adaptive threshold value and

[0089] Remove by following the steps below The influence of outliers in the residual sequence is eliminated, and the mean and standard deviation of normal broadband measurements in the residual sequence are solved to prevent them from affecting the stability of the system.

[0090] Step 3.3.1: Solve The mean μ and standard deviation σ of the sequence

[0091] Step 3.3.2: Determine the threshold value TH using the mean μ and standard deviation σ according to formula (1.15)

[0092] TH=μ+τ·σ(0.15)

[0093] Where: τ is a parameter. Considering the difference between the measurements of each harmonic quantity, τ=6.

[0094] Step 3.3.3: Detect ε k n Is there a value higher than TH in the ? If so, remove it If the value in is higher than TH, return to Step 3.3.1 to continue iteration; otherwise, end the iteration and output and That is, from The mean and standard deviation of the remaining values ​​after outliers are removed.

[0095] Step 3.4: Weight Adaptation

[0096] In this step, the adaptation is to adjust the weight of the outlier in the line parameter estimation according to its strength. The stronger the outlier, the lower its weight. Adaptation is achieved according to the indicators IDR and IPR90 proposed above. The advantages are: compared with fixed weights, it has the ability to "weaken" outliers of different strengths, and the "weakening" effect is better than fixed weights; it can significantly improve the noise resistance of line parameter estimation, thereby improving the accuracy of broadband interference positioning.

[0097] Considering that τ = 6 is taken in Step 3.3.2, it is impossible to remove all outliers, so the influence of outliers is further "weakened" through weight adaptation, further improving the robustness and accuracy of the estimation. Determine the hyperparameter δ according to formula (1.16): k , the value of the adjustment coefficient α in formula (1.16) is determined by Table 1

[0098]

[0099] Table 1 α selection principle

[0100]

[0101] Step 3.5: Calculate the weight Θ by formula (1.17) i And fill the weight matrix W according to formula (0.10).

[0102]

[0103] Step 3.6: Calculate formula (0.9) to get the estimated X d , calculate the residual ε according to formula (0.8) k+1 , if ε k+1 If it converges within the tolerance range, the process ends; otherwise, return to Step 3.1.

[0104] Step 4: Broadband interference tracing with weak interference source location capability

[0105] Step 4.1: Obtain line parameters for interference tracing

[0106] Interference tracing requires the node's self-impedance data and ground admittance data, which can be obtained through the following Step 4.1.1 to Step 4.1.3.

[0107] Step 4.1.1: Apply Step 1 to Step 3 to all nodes to obtain the data of each branch, including the X vector of each branch (X is the quantity in formula (1.9)). The X vector contains the line admittance under each harmonic, the three-phase admittance and the three-phase line to ground admittance.

[0108] Step 4.1.2: Select the required h-order harmonic estimation data, The real and imaginary parts of are combined, Restore to X h , solve for b in equation (0.1) h The reciprocal of each element in the vector is used to obtain the impedance data of each branch; according to y in formula (0.1) h , obtain the admittance data of each branch to the ground.

[0109] Step 4.1.3: Determine the self-impedance and ground admittance data of each node based on the line parameters connected to the node.

[0110] Step 4.2: Tracing the source of broadband interference

[0111] According to the multiple harmonic active power and reactive power P of a node h ,Q h The node self-impedance and ground admittance data obtained in Step 4.1 can be used to obtain the HLI of the interference source at the node in the fuzzy reasoning system according to the positive and negative relationship of their signs. The HLI of the interference source at the node obtained in the fuzzy reasoning system belongs to the prior art and will not be described in detail here. The fuzzy logic reasoning algorithm is applied to each node to obtain the HLI of each node.

[0112] Step 4.3: Process HLI data

[0113] The HLI data obtained from Step 4.2 often shows that some nodes have very high HLI and other nodes have low HLI. In order to facilitate the determination of the location of the interference source and further improve the robustness, the following method is used to filter out the low data to make the interference source more obvious.

[0114] Step 4.3.1: Calculate the mean μ and standard deviation σ of the HLI sequence of nodes 1 to n

[0115] Step 4.3.2: Determine the threshold value THR using the mean μ and standard deviation σ according to formula (1.18)

[0116] THR=μ+τ·σ(0.18)

[0117] Where: τ is a parameter, the distribution law of HLI, and τ=6.

[0118] Step 4.3.3: Check whether there is a value higher than THR in HLI. If so, remove the value higher than THR in HLI and return to Step 4.3.1 to continue iteration; otherwise, end the iteration and output and

[0119] Step 4.3.4: Use formula (1.19) to obtain and Calculating THR norm , filter out below THR norm HLI values, only those above THR are retained norm The HLI value of

[0120]

[0121] Step 4.4: Determine the location of the interference source based on the processed HLI data

[0122] Since the HLI data that may affect the judgment is removed in Step 4.3, there are only a few larger values ​​in the HLI. The interference source can be found by querying the node number corresponding to the larger value.

[0123] This example embodiment proposes a method for tracing the broadband interference of a distribution network that is resistant to strong noise. First, the technical solution of this example embodiment uses an adaptive weighting method to weaken the weight of strong noise while ensuring that normal measurement values ​​are not affected, thereby improving the accuracy of the estimation of distribution network line parameters. Secondly, based on fuzzy logic, broadband interference tracing is achieved using the obtained precise distribution network line parameters.

[0124] In broadband interference tracing, broadband line parameters are needed, so this method first proposes a method for obtaining broadband line parameters using broadband measurement data. In addition, in order to solve the problem that interference sources with weak indicators may appear under a certain harmonic, making the HLI of the interference source unclear in the HLI sequence of each node, a filtering method is designed, which can accurately filter out the indicators that may affect the location judgment of the interference source when the indicator difference between each node is not large, and realize the accurate positioning of the weak interference source.

[0125] Embodiment 2

[0126] The purpose of this embodiment is to provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the program.

[0127] Embodiment 3

[0128] The purpose of this embodiment is to provide a computer-readable storage medium.

[0129] A computer-readable storage medium stores a computer program, which executes the steps of the above method when executed by a processor.

[0130] Embodiment 4

[0131] The purpose of this embodiment is to provide a distribution network broadband interference tracing system that is resistant to strong noise, including:

[0132] The data acquisition module is configured to: acquire a voltage correlation matrix, a vector of quantities to be estimated, and a three-phase harmonic current vector;

[0133] The variable weight least square expression establishment module is configured to: establish a parameter estimation equation using a voltage correlation matrix, a vector of quantities to be estimated and a three-phase harmonic current vector, and process the parameter estimation equation to establish a variable weight least square expression;

[0134] The residual vector calculation module is configured to: iteratively solve the parameters for the variable weight least squares expression and calculate the residual vector generated by the kth iteration;

[0135] The node judgment module where the interference source is located is configured as follows: if the residual vector is within the tolerance range, the line parameters under the harmonics estimated this time are output, the self-impedance and admittance to ground of each node are obtained, the harmonic position index is obtained by using the fuzzy logic method, the harmonic position index is input into the statistical parameter calculator for removing outliers, the sequence value is obtained after removing the outliers, the threshold value is calculated, the harmonic position index below the threshold value is filtered out, and the node where the interference source is located is judged.

[0136] Embodiment 5

[0137] The purpose of this embodiment is to provide a computer program product containing instructions, which, when running on a computer, enables the computer to execute the methods and functions involved in any of the above embodiments.

[0138] The steps involved in the apparatus of the above embodiment correspond to the method embodiment 1, and the specific implementation method can refer to the relevant description part of embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode or carry an instruction set for execution by a processor and enable the processor to execute any method in the present invention.

[0139] Those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computer device, or alternatively, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0140] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A method for tracing the source of broadband interference in a distribution network that is resistant to strong noise, characterized in that: include: Obtaining a voltage correlation matrix, a vector of quantities to be estimated, and a three-phase harmonic current vector; The voltage correlation matrix, the vector of the quantity to be estimated and the three-phase harmonic current vector are used to establish the parameter estimation equation, and the parameter estimation equation is processed to establish the variable weight least square expression; Iterate and solve the parameters for the variable weight least squares expression, and calculate the residual vector generated by the kth iteration; If the residual vector is within the tolerance range, the line parameters under the estimated harmonics are output, the self-impedance and admittance to ground of each node are obtained, the harmonic position index is obtained using the fuzzy logic method, and the harmonic position index is input into the statistical parameter calculator for removing outliers. The sequence value is obtained after removing the outliers, the threshold value is calculated, the harmonic position index below the threshold value is filtered out, and the node where the interference source is located is determined.

2. The method for tracing the source of broadband interference in a distribution network resistant to strong noise as claimed in claim 1, characterized in that: The process of obtaining the voltage correlation matrix, the vector of the quantity to be estimated and the three-phase harmonic current vector is: Obtain the harmonic voltage and current data at both ends of the three-phase line; A first voltage matrix and a second voltage matrix are established based on the harmonic voltage data at both ends of the three-phase line, and the first voltage matrix and the second voltage matrix constitute a voltage correlation matrix; A three-phase harmonic current vector is established based on the harmonic current data at both ends of the three-phase line; A vector of quantities to be estimated is established according to the physical parameters of the three-phase line.

3. The method for tracing the source of broadband interference in a distribution network resistant to strong noise as claimed in claim 1, characterized in that: If the residual vector is not within the tolerance range, then: Calculate the indicators, establish parameter selection principles based on the indicators, use the parameter selection principles to determine the parameters, input the residual vector into the statistical parameter calculator for removing outliers, obtain the sequence values ​​after removing outliers, use the parameters and sequence values ​​to determine the hyperparameters of this iteration, calculate the weight values ​​based on the hyperparameters, fill in the weight matrix, and re-estimate the line parameters under harmonics until the residual vector is within the tolerance range.

4. The method for tracing the source of broadband interference in a distribution network resistant to strong noise as claimed in claim 1, characterized in that: The statistical parameter calculator for removing outliers processes the input data as follows: For input data containing outliers, calculate the mean and standard deviation of the input data; The threshold value of this iteration is determined based on the mean and standard deviation of the input data; Determine whether there are elements greater than the threshold value in the residual vector. If, greater than, remove the elements greater than the threshold value. If not, directly obtain the mean and standard deviation of the sequence without abnormal data.

5. The method for tracing the source of broadband interference in a distribution network resistant to strong noise as claimed in claim 1, characterized in that: The fuzzy logic method is used to obtain the harmonic position index, specifically: According to the multiple harmonic active power, reactive power of a node and the obtained node self-impedance and ground admittance data, the harmonic position index of the interference source at the node can be obtained in the fuzzy reasoning system according to the positive and negative relationship of their signs.

6. The method for tracing the source of broadband interference in a distribution network resistant to strong noise as claimed in claim 1, characterized in that: After filtering out the harmonic position indexes below the threshold value, only a few larger values ​​exist in the harmonic position indexes. The interference source can be found by querying the node numbers corresponding to the larger values.

7. A broadband interference tracing system for distribution network that is resistant to strong noise, characterized by comprising: The data acquisition module is configured to: acquire a voltage correlation matrix, a vector of quantities to be estimated, and a three-phase harmonic current vector; The variable weight least square expression establishment module is configured to: establish a parameter estimation equation using a voltage correlation matrix, a vector of quantities to be estimated and a three-phase harmonic current vector, and process the parameter estimation equation to establish a variable weight least square expression; The residual vector calculation module is configured to: iteratively solve the parameters for the variable weight least squares expression and calculate the residual vector generated by the kth iteration; The node judgment module where the interference source is located is configured as follows: if the residual vector is within the tolerance range, the line parameters under the harmonics estimated this time are output, the self-impedance and admittance to ground of each node are obtained, the harmonic position index is obtained by using the fuzzy logic method, the harmonic position index is input into the statistical parameter calculator for removing outliers, the sequence value is obtained after removing the outliers, the threshold value is calculated, the harmonic position index below the threshold value is filtered out, and the node where the interference source is located is judged.

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

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method described in any one of claims 1 to 6 are implemented.

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

Images