Subsynchronous oscillation suppression method and system for mine field mining area power supply system

Abstract

The invention relates to the technical field of smart power grids, and provides a subsynchronous oscillation suppression method and system for a mine mining area power supply system, and the method comprises the steps: collecting different types of electric data of each electric shovel in the mine mining area power supply system, and obtaining an electric data sequence of each electric shovel; marking a target electric shovel, performing multilayer wavelet decomposition on an electric data sequence of the target electric shovel, obtaining all detail coefficients of each layer, and determining an adaptive adjustment threshold value of the detail coefficients of the same layer; determining a consistency characteristic value of each type of electric data of the target electric shovel, obtaining an adjustment value of a detail coefficient of each layer of the same type of electric data of the electric shovel, and obtaining a de-noised electric data sequence of the electric shovel according to the detail coefficient and inverse discrete wavelet transform; and separating subsynchronous oscillation fault data according to the de-noised electric data sequence to realize subsynchronous oscillation suppression of the mine field mining area power supply system. The subsynchronous oscillation suppression effect of the power supply system can be improved.

Description

Technical Field

[0001] This invention relates to the field of smart grid technology, specifically to a method and system for suppressing subsynchronous oscillations in a power supply system for a mining area. Background Technology

[0002] Subsynchronous oscillations refer to an oscillation phenomenon in a power system that occurs below the normal synchronization frequency. Subsynchronous oscillations can cause abnormal vibrations in critical equipment such as motors and transformers in mining areas, as well as fluctuations in the voltage and frequency of the power supply system, potentially even affecting safe production in the mining area. Due to the influence of electric shovels operating in different states within the mining area, the electrical signals collected from the power supply system often contain spike interference and mode aliasing, making it difficult for SPDMD (Sparse Enhancement Dynamic Mode Decomposition) to accurately identify dominant oscillations from spurious oscillations. Therefore, to accurately extract electrical signals, it is necessary to eliminate the influence of noise interference in the collected signals.

[0003] Wavelet denoising, which has strong time-frequency localization capabilities, is generally used to denoise electrical signals. However, wavelet denoising requires processing electrical signals of the same type separately and cannot combine the correlation of different types of electrical signals for denoising. Furthermore, the peaks and high frequencies of electrical signals are close to the frequencies of the dominant mode. When the frequency domain threshold is not selected properly, the true oscillation mode is easily misjudged as noise and removed or weakened, while invalid interference signals are retained. This affects the data quality of the denoised electrical signal, which in turn leads to inaccurate identification of the dominant oscillation and spurious oscillation, affecting the effect of suppressing subsynchronous oscillations in the power supply system. Summary of the Invention

[0004] This invention provides a method and system for suppressing subsynchronous oscillations in a power supply system for a mining area. The solution addresses the problem that the power supply system's electrical signals, due to the lack of consideration for the correlation between different types of electrical signals, result in unreasonable frequency domain threshold selection, affecting the denoising effect of the electrical signals and leading to inaccurate identification of dominant oscillations and spurious oscillations, thus impacting the effectiveness of subsynchronous oscillation suppression. The specific technical solution adopted is as follows:

[0005] In a first aspect, one embodiment of the present invention provides a method for suppressing subsynchronous oscillations in a power supply system for a mining area, the method comprising the following steps:

[0006] Collect different types of electrical data from each electric shovel in the power supply system of the mining area, and obtain the electrical data sequence of each electric shovel;

[0007] Denote any electric shovel among all electric shovels as the target electric shovel. Perform multi-level wavelet decomposition on the electric data sequence of the target electric shovel to obtain all detail coefficients of each level. Based on the differences between all detail coefficients of the same level, determine the adaptive adjustment threshold of the detail coefficients of the same level.

[0008] Based on the differences between all electrical data of the same type for the target electric shovel, determine the consistency feature value of electrical data of each type for the target electric shovel. Based on the numerical relationship between the detail coefficients of each layer of electrical data of the same type for the electric shovel and the corresponding adaptive adjustment threshold, and the consistency feature value of electrical data of the same type for the electric shovel, obtain the adjustment value of the detail coefficients of each layer of electrical data of the same type for the electric shovel. Assign the detail coefficients to the values ​​of the corresponding adjustment values ​​of detail coefficients. Use inverse discrete wavelet transform to obtain the denoised electrical data sequence of each electric shovel.

[0009] Subsynchronous oscillation fault data is separated from the denoised electrical data sequence, and subsynchronous oscillation suppression is achieved in the power supply system of the mining area based on the subsynchronous oscillation fault data.

[0010] Furthermore, the method for obtaining the electrical data sequence of the electric shovel is as follows:

[0011] Reconstruct all types of electrical data collected by the same electric shovel to obtain the electrical data sequence of the same electric shovel.

[0012] Furthermore, the method for determining the adaptive adjustment threshold of the detail coefficients of the same layer based on the differences among all detail coefficients of the same layer includes the following specific methods:

[0013] The mean of all detail coefficients in the same layer is denoted as the first feature value of the same layer;

[0014] Based on the differences among all detail coefficients of the same layer, the second and third eigenvalues ​​of the same layer are determined respectively;

[0015] The positive correlation processing results of the first, second, and third eigenvalues ​​of the same layer are denoted as the adaptive adjustment threshold of the detail coefficients of the same layer.

[0016] Furthermore, the method for obtaining the second feature value is as follows:

[0017] Based on all detail coefficients of the same layer, obtain the detail coefficient sequence of the same layer, and denote the mean of all values ​​contained in the first difference sequence of the detail coefficient sequence of the same layer as the second feature value of the same layer.

[0018] Furthermore, the method for obtaining the third feature value is as follows:

[0019] The normalized value of the information entropy of all detail coefficients in the same layer is denoted as the third feature value of the same layer.

[0020] Furthermore, the method for determining the consistency characteristic value of the electrical data for each type of the target electric shovel is as follows:

[0021] Based on the differences between electrical data of the same type of target electric shovel, determine the degree of interference of electrical data of the same type of target electric shovel;

[0022] The type of any electrical data is denoted as the target type. The sum of the absolute values ​​of the differences between the interference degree of the target type of electrical data and the interference degree of other types of electrical data is denoted as the interference degree difference of the target type of electrical data.

[0023] The sum of the interference difference of the electrical data of the target electric shovel for the target type and the interference difference of the electrical data of all other electric shovels for the target type is denoted as the cumulative interference difference.

[0024] The ratio of the difference in interference level to the cumulative difference in interference level of the electrical data of the target type of the electric shovel is denoted as the consistency characteristic value of the electrical data of the target type of the electric shovel.

[0025] Furthermore, the method for obtaining the interference level of the same type of electrical data of the target electric shovel is as follows:

[0026] Arrange the electrical data of the same type of target electric shovel in the order of collection to obtain the electrical data sequence of the same type of electrical data. The mean of all values ​​contained in the first difference sequence of the electrical data sequence of the same type is recorded as the first mean of the electrical data of the same type.

[0027] The variance of all values ​​contained in the first difference sequence of electrical data sequences of the same type is denoted as the first variance of the electrical data of the same type.

[0028] The sum of the first mean and the first variance of electrical data of the same type is denoted as the interference degree of the electrical data of the same type of target electric shovel.

[0029] Furthermore, the formula for calculating the adjustment value of the detail coefficient for each layer of the same type of electrical data of the electric shovel is as follows:

[0030]

[0031] in, This represents the adjustment value of the t-th detail coefficient at the j-th layer of the electrical data of the c-th type of the n-th electric shovel; d n,c,j,t τ represents the j-th level t-th detail coefficient of the c-th type of electrical data for the n-th electric shovel; n,c,j The adaptive adjustment threshold for the detail coefficients of the c-th type of electrical data for the nth electric shovel at the j-th layer; sgn() represents the sign function; ω n,c This represents the consistency characteristic value of the electrical data of the c-th type of the nth electric shovel.

[0032] Furthermore, the specific method for separating the subsynchronous oscillation fault data based on the denoised electrical data sequence includes:

[0033] The SPDMD algorithm was used to separate subsynchronous oscillation fault data from a denoised electrical data sequence.

[0034] Secondly, embodiments of the present invention also provide a subsynchronous oscillation suppression system for a power supply system in a mining area, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of any of the methods described above.

[0035] The beneficial effects of this invention are:

[0036] This invention first reconstructs the electrical data sequence of an electric shovel based on electrical data from different types of shovels. To avoid excessively high threshold values ​​for wavelet denoising, which would distort the denoised data, and to avoid excessively low threshold values, which would result in incomplete noise removal, an adaptive adjustment threshold for the detail coefficients of the corresponding layer is determined by considering the overall average intensity, overall variation, and complexity of the values ​​of the detail coefficients within the same layer. When strong spike interference appears in the electrical data, the adaptive adjustment threshold is increased to suppress the impact of spike interference. Conversely, when the electrical data values ​​are stable and concentrated, the adaptive adjustment threshold is decreased to avoid the problem of eliminating oscillating mode signals. Furthermore, the electrical data from different types acquired by the wide-area measurement system exhibits strong modal consistency, showing synchronous amplitude and phase responses under the same oscillation mode. Other noise influences can disrupt this consistency. Based on the differences between all electrical data of the same type for the target electric shovel, the electrical data is evaluated. Based on the significance of modal consistency, the consistency feature value of electrical data for each type of target electric shovel is determined. Then, based on the numerical relationship between the detail coefficients of each layer of electrical data for the same type of electric shovel and the corresponding adaptive adjustment threshold, as well as the consistency feature value of electrical data for the same type of electric shovel, the detail coefficients are adjusted to obtain the adjustment value of the detail coefficients of each layer of electrical data for the same type of electric shovel, thereby obtaining the denoised electrical data sequence for each electric shovel. Finally, subsynchronous oscillation fault data is separated from the denoised electrical data sequence. Based on the subsynchronous oscillation fault data, subsynchronous oscillation suppression is achieved in the power supply system of the mining area. This solves the problem that the power supply system's electrical signals, due to the lack of consideration for the correlation of different types of electrical signals, result in unreasonable frequency domain threshold selection, affecting the denoising effect of the electrical signals, leading to inaccurate identification of dominant oscillations and spurious oscillations, and affecting the subsynchronous oscillation suppression effect of the power supply system, thus improving the accuracy of subsynchronous oscillation suppression in the power supply system. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a flowchart illustrating a method for suppressing subsynchronous oscillations in a mine power supply system according to an embodiment of the present invention.

[0039] Figure 2 This is a flowchart illustrating the adaptive threshold acquisition process provided in one embodiment of the present invention. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] Please see Figure 1 The diagram illustrates a flowchart of a method for suppressing subsynchronous oscillations in a mine power supply system according to an embodiment of the present invention. The method includes the following steps:

[0042] Step S001: Collect different types of electrical data from each electric shovel in the power supply system of the mining area, and obtain the electrical data sequence of each electric shovel.

[0043] The wide-area measurement system collects electrical data from different types of electric shovels in the mining area.

[0044] The electrical data includes the voltage phasor and current phasor of the electric shovel, the total voltage and current of the power supply system, the voltage THD and current THD of the electric shovel. Collecting different types of electrical data through a wide-area measurement system is a well-known technique and will not be elaborated further. In this embodiment, the electrical data sampling frequency is 5kHz, and electrical data is collected over a period of 10 minutes. In practical applications, as other implementation methods, implementers can determine the data sampling frequency and the number of samples according to the actual situation, provided that the sampling frequency setting satisfies the Nyquist sampling theorem. This invention does not impose special restrictions. The number of samples can be calculated based on the data sampling frequency and sampling duration.

[0045] Preprocessing is performed on all types of electrical data. This preprocessing includes format conversion, standardization, and outlier interpolation for each type of electrical data, and alignment of all types of electrical data sequences. Specifically, format conversion involves decomposing complex phasors into real numbers represented by real and imaginary parts. Standardization is performed to avoid dimensional interference; in this embodiment, the Z-Score normalization method is used to remove dimensions from each type of electrical data. Moving average interpolation with a window width of 2 is used for outlier interpolation. Dynamic time warping is used to align all types of electrical data. Preprocessing of electrical data is a well-known technique and will not be elaborated further.

[0046] The sinc interpolation method is used to reconstruct all types of electrical data collected by the same electric shovel, thereby obtaining the electrical data sequence of the same electric shovel.

[0047] The electrical data sequence for each electric shovel is a continuous time series. The use of sinc interpolation to obtain the time series is a well-known technique and will not be elaborated further.

[0048] At this point, the electrical data sequence of each electric shovel in the power supply system of the mining area has been collected.

[0049] Step S002: Denote any one of the electric shovels as the target electric shovel. Perform multi-level wavelet decomposition on the electrical data sequence of the target electric shovel to obtain all detail coefficients of each level. Based on the differences between all detail coefficients of the same level, determine the adaptive adjustment threshold of the detail coefficients of the same level.

[0050] In mining areas, multiple electric shovels may operate simultaneously. When the shovels start and stop rapidly or experience sudden load changes, the current fluctuates drastically. This causes non-stationary disturbances such as spike interference and harmonic voltage distortion in the electrical data collected by the power supply system. These disturbances can overlap with the system's oscillation mode frequencies. Furthermore, the operating states of different shovels constantly change, with loads at low, medium, and high frequencies coexisting, creating strong load impacts and frequency disturbances. This results in significant mode overlap and non-uniform distribution of mode energy in the frequency domain of the collected electrical signals. Consequently, weak but important dominant oscillation mode characteristics in the electrical data collected in mining areas are easily masked.

[0051] To avoid setting the wavelet denoising threshold too high, which would distort the denoised data, and to avoid setting the wavelet denoising threshold too low, which would result in incomplete noise removal, the threshold value for wavelet denoising needs to be determined based on the stability and concentration of the electrical data values.

[0052] Designate any one of the electric shovels as the target shovel. Perform multi-level wavelet decomposition on the electrical data sequence of the target shovel using the sym5 wavelet basis function to obtain all detail coefficients at each level. In this embodiment, the number of wavelet decomposition levels is set to 5.

[0053] Among them, the use of wavelet decomposition to obtain the detail coefficients of each layer is a well-known technique and will not be elaborated further. The detail coefficients represent the high-frequency part of the data at a finer time scale. They contain the detailed features of the data, such as abrupt changes, spikes, or short-period fluctuations.

[0054] The mean of all detail coefficients in the same layer is recorded as the first feature value of the same layer; all detail coefficients in the same layer are arranged sequentially to obtain the detail coefficient sequence of the same layer; the mean of all values ​​contained in the first difference sequence of the detail coefficient sequence of the same layer is recorded as the second feature value of the same layer; and the normalized value of the information entropy of all detail coefficients in the same layer is recorded as the third feature value of the same layer.

[0055] The calculation of the first-order difference sequence and the calculation of information entropy are well-known techniques and will not be elaborated further.

[0056] It should be noted that this embodiment uses the Z-Score standard normalization method to calculate the normalized value. In practical applications, implementers may use other methods of existing technology, such as the maximum-minimum normalization method or the sigmoid function, to calculate the normalized value, and no limitation is made here.

[0057] The first eigenvalue is used to evaluate the overall average intensity of the detail coefficients of the corresponding layer. The second eigenvalue is used to evaluate the overall degree of change of the detail coefficients of the corresponding layer. The third eigenvalue is used to evaluate the complexity of the values ​​of the detail coefficients of the corresponding layer. During the start-up and shutdown phase of the electric shovel, strong spike interference will occur and the distribution frequency band of the spike interference is wide. The first, second, and third eigenvalues ​​are all large.

[0058] The positive correlation processing results of the first, second, and third eigenvalues ​​of the same layer are denoted as the adaptive adjustment threshold of the detail coefficients of the same layer.

[0059] The flowchart for adaptive threshold adjustment is as follows: Figure 2 As shown.

[0060] It is understood that positive correlation processing is applied to the first, second, and third eigenvalues ​​of the same layer, ensuring that each eigenvalue is positively correlated with the adaptive adjustment threshold of the detail coefficients of the same layer. It is also understood that the positive correlation in this invention refers to the relationship between the independent and dependent variables, where the independent variables are the first, second, and third eigenvalues ​​of the same layer, and the dependent variable is the adaptive adjustment threshold of the detail coefficients of the same layer. The positive correlation means that the dependent variable increases (decreases) as the independent variable increases (decreases), and can be an additive or multiplicative relationship.

[0061] Preferably, as an embodiment of the present invention, the formula for calculating the adaptive adjustment threshold of the detail coefficients of the same layer is:

[0062]

[0063] Where, τ j α represents the adaptive adjustment threshold of the detail coefficients of the j-th layer; α represents the preset first weight; β represents the preset second weight, the sum of the first weight and the second weight is 1, and in this embodiment, the values ​​of the first weight and the second weight are 0.4 and 0.6 respectively; a j b represents the first eigenvalue of the j-th layer; j θ represents the second eigenvalue of the j-th layer; j represents the third eigenvalue of the j-th layer; e represents the natural constant.

[0064] By considering the overall average intensity, overall degree of variation, and complexity of the values ​​of the detail coefficients at the same layer, the adaptive adjustment threshold of the detail coefficients at the corresponding layer can be determined. When strong spike interference occurs in the electrical data, the value of the adaptive adjustment threshold can be increased to suppress the impact of spike interference. At the same time, when the values ​​of the electrical data are stable and concentrated, the value of the adaptive adjustment threshold can be decreased to avoid the problem of eliminating oscillating mode signals.

[0065] At this point, the adaptive adjustment threshold for the detail coefficient of each layer of the target electric shovel is obtained.

[0066] The same method can be used to obtain the adaptive adjustment threshold of the detail coefficient for each layer of each electric shovel in all electric shovels.

[0067] At this point, the adaptive adjustment threshold for the detail coefficient of each layer of each electric shovel in all electric shovels is obtained.

[0068] Step S003: Based on the differences between all electrical data of the same type for the target electric shovel, determine the consistency feature value of electrical data of each type for the target electric shovel. Based on the numerical relationship between the detail coefficients of each layer of electrical data of the same type for the electric shovel and the corresponding adaptive adjustment threshold, and the consistency feature value of electrical data of the same type for the electric shovel, obtain the adjustment value of the detail coefficients of each layer of electrical data of the same type for the electric shovel. Assign the detail coefficients to the values ​​of the corresponding adjustment values ​​of the detail coefficients. Use inverse discrete wavelet transform to obtain the denoised electrical data sequence of each electric shovel.

[0069] Furthermore, the different types of electrical data collected by the wide-area measurement system exhibit strong modal consistency, showing synchronous amplitude and phase responses under the same oscillation mode. Local oscillation modes can gradually affect the entire power supply system, causing damage. Therefore, evaluating the consistency between different types of point data is crucial for improving the denoising effect of electrical signals.

[0070] Based on the differences in electrical data between the same type of target electric shovels, determine the degree of interference of the electrical data of the same type of target electric shovels.

[0071] The electrical data of the same type from the target electric shovel are arranged in the order of collection to obtain the electrical data sequence of the same type. The mean of all values ​​contained in the first difference sequence of the electrical data sequence of the same type is denoted as the first mean of the electrical data of the same type. The variance of all values ​​contained in the first difference sequence of the electrical data sequence of the same type is denoted as the first variance of the electrical data of the same type. The sum of the first mean and the first variance of the electrical data of the same type is denoted as the interference degree of the electrical data of the same type from the target electric shovel.

[0072] The degree of interference is obtained based on the degree of variation in the values ​​of electrical data of the same type, and is used to evaluate the likelihood of interference to electrical data of the same type. The lower the degree of interference, the less likely the corresponding type of electrical data is to be interfered with, and the more stable the value of the electrical data is.

[0073] Based on the differences in the interference levels of the electrical data for each type of target electric shovel, the consistency characteristic value of the electrical data for each type of target electric shovel is determined.

[0074] Let any type of electrical data be denoted as the target type. Let the sum of the absolute values ​​of the differences between the interference degree of the target electric shovel's target type electrical data and the interference degree of other types of electrical data be denoted as the interference degree difference of the target electric shovel's target type electrical data. Let the sum of the interference degree difference of the target electric shovel's target type electrical data and the interference degree differences of all other electric shovels' target type electrical data be denoted as the cumulative interference degree difference. Let the ratio of the interference degree difference of the target electric shovel's target type electrical data to the cumulative interference degree difference be denoted as the consistency characteristic value of the target electric shovel's target type electrical data.

[0075] The same method can be used to obtain the consistency characteristic values ​​of the electrical data for each type of electric shovel in all electric shovels.

[0076] Based on the numerical relationship between the detail coefficients of each layer of the same type of electrical data of the electric shovel and the corresponding adaptive adjustment threshold, as well as the consistency feature values ​​of the same type of electrical data of the electric shovel, the adjustment value of the detail coefficients of each layer of the same type of electrical data of the electric shovel is obtained.

[0077]

[0078] in, This represents the adjustment value of the t-th detail coefficient at the j-th layer of the electrical data of the c-th type of the n-th electric shovel; d n,c,j,t τ represents the j-th level t-th detail coefficient of the c-th type of electrical data for the n-th electric shovel; n,c,j The adaptive adjustment threshold for the detail coefficients of the c-th type of electrical data for the nth electric shovel at the j-th layer; sgn() represents the sign function; ω n,c This represents the consistency characteristic value of the electrical data of the c-th type of the nth electric shovel.

[0079] Among them, the symbolic function is a well-known mathematical function, and will not be elaborated further.

[0080] The adjustment value of the detail coefficient can be based on the value of the detail coefficient and combined with the consistency evaluation between different types of point data. This can suppress strong spike interference and avoid eliminating oscillating mode signals.

[0081] The detail coefficients are assigned the corresponding adjustment values, and the inverse discrete wavelet transform is used to obtain the denoised electrical data sequence for each electric shovel.

[0082] Denoising electrical data sequences can suppress strong spike interference while avoiding the elimination of oscillation mode signals, thereby improving data quality and increasing the accuracy of subsequent identification of subsynchronous oscillation signals.

[0083] At this point, the denoised electrical data sequence for each electric shovel is obtained.

[0084] Step S004: Separate the subsynchronous oscillation fault data from the denoised electrical data sequence, and suppress the subsynchronous oscillation of the power supply system in the mining area based on the subsynchronous oscillation fault data.

[0085] For each electric shovel, the SPDMD algorithm is used to separate the dominant oscillation mode and the spurious mode from the denoised electrical data sequence. The electrical data corresponding to the separated dominant oscillation mode is recorded as the subsynchronous oscillation fault data.

[0086] The use of the SPDMD algorithm to separate the data corresponding to the dominant oscillation mode is a well-known technique and will not be elaborated further.

[0087] For subsynchronous oscillation fault data, a combined approach of "system defense" and "tiered management" is adopted at both the power supply system and load levels to suppress subsynchronous oscillations in the power supply system while providing localized protection for key loads. Specifically, at the power supply system level, a subsynchronous low-frequency oscillation suppression device (SLOP-06 / 1000T) is installed in the feeder circuit of the electric shovel containing the electrical data corresponding to the subsynchronous oscillation fault data. At the load level, a voltage transient protection device (TOVS) is installed in the control circuit of the electric shovel containing the electrical data corresponding to the subsynchronous oscillation fault data, ensuring key protection for the secondary control circuit while suppressing oscillations in the main circuit.

[0088] This achieves the suppression of subsynchronous oscillations in the power supply system of the mining area.

[0089] Based on the same inventive concept as the above method, this embodiment of the invention also provides a subsynchronous oscillation suppression system for a power supply system in a mining area, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described methods for suppressing subsynchronous oscillations in a power supply system in a mining area.

[0090] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for suppressing subsynchronous oscillations in a power supply system for a mining area, characterized in that, The method includes the following steps: Collect different types of electrical data from each electric shovel in the power supply system of the mining area, and obtain the electrical data sequence of each electric shovel; Denote any electric shovel among all electric shovels as the target electric shovel. Perform multi-level wavelet decomposition on the electric data sequence of the target electric shovel to obtain all detail coefficients of each level. Based on the differences between all detail coefficients of the same level, determine the adaptive adjustment threshold of the detail coefficients of the same level. Based on the differences between all electrical data of the same type for the target electric shovel, determine the consistency feature value of electrical data of each type for the target electric shovel. Based on the numerical relationship between the detail coefficients of each layer of electrical data of the same type for the electric shovel and the corresponding adaptive adjustment threshold, and the consistency feature value of electrical data of the same type for the electric shovel, obtain the adjustment value of the detail coefficients of each layer of electrical data of the same type for the electric shovel. Assign the detail coefficients to the values ​​of the corresponding adjustment values ​​of detail coefficients. Use inverse discrete wavelet transform to obtain the denoised electrical data sequence of each electric shovel. Subsynchronous oscillation fault data is separated from the denoised electrical data sequence, and subsynchronous oscillation suppression is achieved in the power supply system of the mining area based on the subsynchronous oscillation fault data.

2. The method for suppressing subsynchronous oscillations in a mine power supply system according to claim 1, characterized in that, The method for obtaining the electrical data sequence of the electric shovel is as follows: Reconstruct all types of electrical data collected by the same electric shovel to obtain the electrical data sequence of the same electric shovel.

3. The method for suppressing subsynchronous oscillations in a mine power supply system according to claim 1, characterized in that, The method for determining the adaptive adjustment threshold of detail coefficients for the same layer based on the differences among all detail coefficients in the same layer includes the following specific methods: The mean of all detail coefficients in the same layer is denoted as the first feature value of the same layer; Based on the differences among all detail coefficients of the same layer, the second and third eigenvalues ​​of the same layer are determined respectively; The positive correlation processing results of the first, second, and third eigenvalues ​​of the same layer are denoted as the adaptive adjustment threshold of the detail coefficients of the same layer.

4. The method for suppressing subsynchronous oscillations in a mine power supply system according to claim 3, characterized in that, The method for obtaining the second feature value is as follows: Based on all detail coefficients of the same layer, obtain the detail coefficient sequence of the same layer, and denote the mean of all values ​​contained in the first difference sequence of the detail coefficient sequence of the same layer as the second feature value of the same layer.

5. The method for suppressing subsynchronous oscillations in a mine power supply system according to claim 3, characterized in that, The method for obtaining the third feature value is as follows: The normalized value of the information entropy of all detail coefficients in the same layer is denoted as the third feature value of the same layer.

6. The method for suppressing subsynchronous oscillations in a mine power supply system according to claim 1, characterized in that, The method for determining the consistency characteristic value of each type of electrical data of the target electric shovel is as follows: Based on the differences between electrical data of the same type of target electric shovel, determine the degree of interference of electrical data of the same type of target electric shovel; The type of any electrical data is denoted as the target type. The sum of the absolute values ​​of the differences between the interference degree of the target type of electrical data and the interference degree of other types of electrical data is denoted as the interference degree difference of the target type of electrical data. The sum of the interference difference of the electrical data of the target electric shovel for the target type and the interference difference of the electrical data of all other electric shovels for the target type is denoted as the cumulative interference difference. The ratio of the difference in interference level to the cumulative difference in interference level of the electrical data of the target type of the electric shovel is denoted as the consistency characteristic value of the electrical data of the target type of the electric shovel.

7. A method for suppressing subsynchronous oscillations in a mine power supply system according to claim 6, characterized in that, The method for obtaining the interference level of the same type of electrical data of the target electric shovel is as follows: Arrange the electrical data of the same type of target electric shovel in the order of collection to obtain the electrical data sequence of the same type of electrical data. The mean of all values ​​contained in the first difference sequence of the electrical data sequence of the same type is recorded as the first mean of the electrical data of the same type. The variance of all values ​​contained in the first difference sequence of electrical data sequences of the same type is denoted as the first variance of the electrical data of the same type. The sum of the first mean and the first variance of electrical data of the same type is denoted as the interference degree of the electrical data of the same type of target electric shovel.

8. The method for suppressing subsynchronous oscillations in a mine power supply system according to claim 1, characterized in that, The formula for calculating the adjustment value of the detail factor for each layer of the same type of electrical data of the electric shovel is as follows: in, This represents the adjustment value of the t-th detail coefficient at the j-th layer of the electrical data of the c-th type of the n-th electric shovel; d n,c,j,t τ represents the j-th level t-th detail coefficient of the c-th type of electrical data for the n-th electric shovel; n,c,j The adaptive adjustment threshold for the detail coefficients of the c-th type of electrical data for the nth electric shovel at the j-th layer; sgn() represents the sign function; ω n,c This represents the consistency characteristic value of the electrical data of the c-th type of the nth electric shovel.

9. A method for suppressing subsynchronous oscillations in a mine power supply system according to claim 1. Its features are, The specific method for separating subsynchronous oscillation fault data based on the denoised electrical data sequence includes: The SPDMD algorithm was used to separate subsynchronous oscillation fault data from a denoised electrical data sequence.

10. A subsynchronous oscillation suppression system for a power supply system in a mining area, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as claimed in any one of claims 1-9.

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