Dynamic sliding window filtering method, equipment and medium

Abstract

The invention discloses a dynamic sliding window filtering method and device, and a medium. The method comprises the following steps: calculating and updating a sliding window length given value in real time based on a currently collected power grid frequency; comparing the obtained sliding window length given value with the current sliding window length; if the sliding window length given value is equal to the current sliding window length, the current sliding window length is kept unchanged; if the sliding window length given value is larger than the current sliding window length, the sliding window length is gradually increased according to a set mode; if the sliding window length given value is smaller than the current sliding window length, the sliding window length is gradually shortened according to a set mode. The device and the medium are both used for implementing the method. The beneficial effects of the application are that compared with a traditional fixed sliding window length, the technical scheme of the application can adaptively adjust the sliding window length according to the change of the power grid frequency, so that the data acquisition accuracy of the sliding window can be improved, and effective elimination of ripples can be realized.

Description

Technical Field

[0001] This application relates to the field of new energy power generation technology, and in particular to a dynamic sliding window filtering method, device and medium. Background Technology

[0002] Single-phase inverters need to convert DC power into AC power synchronized with the power grid. Their core control lies in extracting power data such as bus voltage and battery current. In practical applications, power data contains ripple, meaning the actual signal equals the true DC component plus a 100Hz ripple plus high-frequency noise. Ripple causes errors in the power data. Dynamically acquiring power grid data using a sliding window can suppress power frequency ripple interference. The sliding window eliminates ripple through integer-cycle averaging, calculating the average value of the data within the window to obtain the power data; that is, when the window length is an integer multiple of the power grid cycle, the integral value of the ripple within the window is 0, thus eliminating ripple. However, in practical applications, the power grid frequency is dynamically changing, while existing sliding windows use a fixed window for power data acquisition, which leads to a deterioration in the power frequency ripple suppression effect. Summary of the Invention

[0003] One objective of this application is to provide a dynamic sliding window filtering method that can solve at least one of the defects in the aforementioned background art.

[0004] Another objective of this application is to provide an electronic device capable of implementing a dynamic sliding window filtering method that addresses at least one of the deficiencies in the aforementioned background art.

[0005] Another object of this application is to provide a computer-readable storage medium capable of implementing a dynamic sliding window filtering method that addresses at least one of the deficiencies in the aforementioned background art.

[0006] To achieve at least one of the above objectives, the technical solution adopted in this application is as follows: a dynamic sliding window filtering method, comprising the following steps: calculating and updating the given value of the sliding window length in real time based on the currently collected power grid frequency; comparing the obtained given value of the sliding window length with the current sliding window length; if the given value of the sliding window length is equal to the current sliding window length, keeping the current sliding window length unchanged; if the given value of the sliding window length is greater than the current sliding window length, gradually increasing the sliding window length according to a set method; if the given value of the sliding window length is less than the current sliding window length, gradually shortening the sliding window length according to a set method.

[0007] Preferably, the given value of the sliding window length is equal to the ratio of the switching frequency to the currently collected power grid frequency.

[0008] Preferably, when the given value of the sliding window length is not equal to the current sliding window length, the sliding window length is increased or decreased according to the set value as the number of times the sliding window moves increases.

[0009] Preferably, the setting value for increasing or decreasing the length of the sliding window is an integer multiple of the single movement step of the sliding window.

[0010] Preferably, the setting value for increasing or decreasing the length of the sliding window is the single movement step of the sliding window.

[0011] Preferably, the sliding window length is increased by extending backward from the end of the buffer area corresponding to the sliding window; the sliding window length is shortened by decreasing forward from the end of the buffer area corresponding to the sliding window.

[0012] Preferably, an upper and lower limit for the sliding window length are set; if the given value of the sliding window length is greater than the current sliding window length and the current sliding window length reaches the upper limit, the current sliding window length remains unchanged; if the given value of the sliding window length is less than the current sliding window length and the current sliding window length reaches the lower limit, the current sliding window length remains unchanged.

[0013] Preferably, a safe range for the power grid frequency is set, and the ratio of the switching frequency to the lower limit of the safe range for the power grid frequency is used as the upper limit of the sliding window length, while the ratio of the switching frequency to the upper limit of the safe range for the power grid frequency is used as the lower limit of the sliding window length.

[0014] An electronic device includes a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program to implement the above-described dynamic sliding window filtering method.

[0015] A computer-readable storage medium storing a computer program; when the computer program is executed by a processor, it implements the above-described dynamic sliding window filtering method.

[0016] Compared with the prior art, the beneficial effects of this application are as follows: Compared to the traditional fixed length of the sliding window, the technical solution of this application can adaptively adjust the length of the sliding window according to the change of the power grid frequency, thereby improving the data acquisition accuracy of the sliding window and achieving effective elimination of ripple. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the working steps of this application.

[0018] Figure 2 This is a schematic diagram illustrating the specific workflow of this application.

[0019] Figure 3 This is a schematic diagram of the sliding window movement when the given value of the sliding window length is equal to the current sliding window length.

[0020] Figure 4 This is a schematic diagram illustrating the movement of the sliding window when the given value of the sliding window length is greater than the current sliding window length.

[0021] Figure 5 This is a schematic diagram illustrating the movement of the sliding window when the given value of the sliding window length is less than the current sliding window length. Detailed Implementation

[0022] The present application will now be further described in conjunction with specific embodiments. It should be noted that, in the description of this specification, the use of terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicates that the specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms should not be construed as necessarily referring to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0023] In the description of this application, it should be noted that the terms "center", "lateral", "longitudinal", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc., which indicate the orientation and positional relationship based on the orientation or positional relationship shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and should not be construed as limiting the specific protection scope of this application.

[0024] It should be noted that the terms "first," "second," etc., in the specification and claims of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0025] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "joining," and "fixing," etc., should be interpreted broadly. For example, they can refer to a connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0026] In this application, unless otherwise expressly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature being directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature being directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0027] The terms “comprising” and “having”, and any variations thereof, in the specification and claims of this application are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0028] One aspect of this application provides a dynamic sliding window filtering method, such as Figure 1 and Figure 2 As shown, one preferred embodiment includes the following steps: calculating and updating the given value of the sliding window length in real time based on the currently collected power grid frequency; and comparing the obtained given value of the sliding window length with the current sliding window length. If the given value of the sliding window length is equal to the current sliding window length, the current sliding window length remains unchanged. If the given value of the sliding window length is greater than the current sliding window length, the sliding window length is gradually increased according to a set method. If the given value of the sliding window length is less than the current sliding window length, the sliding window length is gradually shortened according to a set method.

[0029] Understandably, traditional methods for acquiring power data using a sliding window typically assume the grid frequency remains constant, for example, always at 50Hz; therefore, the sliding window length is set to a fixed value. However, in actual inverter operation, the grid frequency may fluctuate due to factors such as load changes or line impedance. For fluctuating grid frequencies, acquiring data using a fixed-length sliding window may result in inaccurate data values, leading to a decrease in the effectiveness of power frequency ripple suppression.

[0030] Therefore, in the technical solution of this application, the power grid frequency can be acquired in real time, and then a corresponding real-time sliding window length setpoint can be calculated based on the acquired power grid frequency. This sliding window length setpoint is compared with the current sliding window length. If the two are equal, it indicates that the power grid frequency is stabilizing; if they are not equal, it indicates that the power grid frequency is fluctuating. To ensure the accuracy of the sliding window data acquisition, the technical solution of this application can adjust the sliding window length according to the relationship between the given sliding window length and the current sliding window length. That is, the technical solution of this application can adaptively adjust the sliding window length according to changes in the power grid frequency, thereby improving the accuracy of the sliding window data acquisition and effectively eliminating ripple.

[0031] In this embodiment, there are several ways to calculate the given value of the sliding window length. For example, the ratio or difference between the current power grid frequency and the reference value of the power grid frequency can be used as a coefficient, and then the obtained coefficient can be multiplied by the initially given sliding window length to calculate the given value of the sliding window length. Taking a 220V, 50Hz power grid as an example, the reference value of the power grid frequency is 50Hz, so the initial value of the corresponding sliding window length is the sliding window length calculated when the power grid frequency is 50Hz. Considering that the sliding window length is calculated as the ratio of the switching frequency to the power grid frequency, taking a switching frequency of 20kHz as an example, the sliding window length is 20000 / 50=400. Therefore, in this embodiment, the given value of the sliding window length is actually the theoretical value of the sliding window length based on the current power grid frequency. That is, the calculation of the given value of the sliding window length can preferably be equal to the ratio of the switching frequency to the currently collected power grid frequency. For example, if a power grid fluctuation causes the grid frequency to drop to 48Hz, the given window length is approximately 20000 / 48 ≈ 416.7. Since the window length can only be an integer, the given window length is either 416 or 417. It's important to note that the phase error introduced by rounding down the given window length is extremely small and has almost no impact on ripple suppression at twice the power frequency, i.e., 100Hz.

[0032] Understandably, taking a scenario where the grid frequency was 50Hz at the previous moment and has fluctuated to 48Hz at the current moment, the corresponding sliding window length is 417. If the current sliding window length is directly increased from 400 to 417, then at the next moment, if the grid frequency returns to 50Hz, the sliding window length needs to be directly decreased from 417 to 400. This would result in excessively large instantaneous changes in the sliding window length, easily causing data oscillations, potentially leading to inaccurate data acquisition and processor overload. Therefore, in the technical solution of this application, when the grid frequency fluctuates, the sliding window length can be gradually increased or decreased according to a set method. By gradually changing the sliding window length, the degree of instantaneous change in the sliding window length can be effectively suppressed.

[0033] In layman's terms, when the power grid frequency fluctuates momentarily, its impact on ripple is minimal; however, if the power grid frequency fluctuates for an extended period, its impact on ripple is significant. Therefore, the technical solution of this application allows for a slight adjustment of the sliding window length during momentary power grid frequency fluctuations, avoiding data oscillations caused by excessively large instantaneous changes in the sliding window length. Conversely, when the power grid frequency remains in a fluctuating state, the sliding window length can be gradually increased to the corresponding theoretical length, effectively suppressing ripple.

[0034] In this embodiment, there are several ways to increase or decrease the length of the sliding window. The length can be adjusted sequentially as the number of sliding window movements increases; alternatively, it can be adjusted intermittently as the number of sliding window movements increases. Preferably, in this embodiment, when the given value of the sliding window length is not equal to the current sliding window length, the sliding window length is increased or decreased sequentially according to the set value as the number of sliding window movements increases.

[0035] It is understandable that the setting for adjusting the sliding window length can be a fixed value or a variable value. For ease of understanding, the adjustment process for both fixed and variable values ​​of the sliding window length will be described in detail below.

[0036] Specifically, when adjusting the fixed value for increasing or decreasing the length of the sliding window, the set value can be an integer multiple of the single movement step of the sliding window; the specific multiple can be set according to the actual needs of those skilled in the art, for example, it can be 1, 2, or 3 times. In this embodiment, the set value used for adjusting the fixed value for increasing or decreasing the length of the sliding window is preferably the single movement step of the sliding window.

[0037] It's important to note that the single movement step of the sliding window is typically 1. For easier understanding, a detailed description using specific parameters can be provided. Taking a power grid frequency fluctuating from 50Hz to 48Hz as an example, if the power grid frequency remains at 48Hz, then as the number of sliding window movements increases, the sliding window length will increase sequentially from 400 to 401, 402, ..., 417.

[0038] Specifically, when adjusting the variable value of increasing or decreasing the sliding window length, the set value can be a set ratio of the difference between the given sliding window length and the current sliding window length. The given sliding window length can be set to W. ref If the current sliding window length is W, then the setting value used to adjust the sliding window length is k(W). ref -W); where k is a set proportional coefficient, and the specific value can be set according to the actual needs of those skilled in the art, such as k=0.05, k=0.1, k=0.2, etc.

[0039] To facilitate understanding, a detailed description can be provided using specific parameters. Taking a grid frequency fluctuation from 50Hz to 48Hz, with k=0.1 as an example; if the grid frequency remains at 48Hz, then when the sliding window moves for the first time, the setting value for adjusting the sliding window length is 0.1×(417-400)=1.7; considering that the sliding window length is an integer, the setting value can be 2; when the sliding window moves for the second time, the setting value for adjusting the sliding window length is 0.1×(417-402)=1.5, so the setting value is 2; when the sliding window moves for the third time, the setting value for adjusting the sliding window length is 0.1×(417-404)=1.3, so the setting value is 1; as the sliding window moves, the above process of selecting different setting values ​​is repeated until the sliding window length equals the given sliding window length value.

[0040] In this embodiment, the direction of increasing and decreasing the length of the sliding window can be arbitrary. Increasing the length of the sliding window can be achieved by extending it at both ends of the buffer corresponding to the sliding window; specifically, increasing the length at the beginning of the buffer is equivalent to the beginning of the sliding window moving two steps at a time, while the end shortens by one step; increasing the length at the end of the buffer is equivalent to the end of the sliding window remaining unchanged, while the beginning of the sliding window moves by a single step. Decreasing the length of the sliding window can be achieved by decreasing the length at the end of the buffer corresponding to the sliding window, or by randomly decreasing the length of the buffer corresponding to the sliding window by one step. In this embodiment, it is preferable to increase the length by extending it backward from the end of the buffer corresponding to the sliding window, and to decrease it by decreasing it forward from the end of the buffer corresponding to the sliding window.

[0041] To facilitate further understanding, the dynamic sliding window filtering process of this application will be described in detail below, taking the adjustment of a set value as an example.

[0042] 1. For scenarios where the given value of the sliding window length calculated based on the current power grid frequency is equal to the current sliding window length.

[0043] like Figure 2 As shown, the difference between the given sliding window length and the current sliding window length is 0, allowing the current sliding window length to remain unchanged while performing sliding summation. Finally, the mean of the summation result is calculated to achieve power data output with ripple suppression. As the sliding window moves, the result of the sliding summation, DataSum, increases. _N It can be represented by the following expression: DataSum _N = DataSum _N-1 +DataReal-DataBuff.

[0044] Among them, DataSum _N-1 This represents the summation result of the previous sliding window. DataReal represents the data value added to the beginning of the buffer when the sliding window moves one step, and DataBuff represents the data value subtracted from the end of the buffer when the sliding window moves one step. After completing the sliding summation, the desired mean can be obtained by dividing the result of the sliding summation by the current sliding window length.

[0045] like Figure 3 As shown, taking a sliding window with a length of 3 and moving 3 times as an example: After the first move, the sliding window corresponds to buffer regions 1, 2, and 3, with data values ​​of 6, 7, and 8 respectively. The yellow window's data values ​​6 and 7 represent the values ​​previously stored in the buffer, while the green window's data value 8 represents the value newly entered during the move. In the second move, the sliding window moves one step, corresponding to buffer regions 2, 3, and 4, with data values ​​of 7, 8, and 9 respectively. Again, the yellow window's data values ​​7 and 8 represent the values ​​previously stored in the buffer, while the green window's data value 9 represents the value newly entered during the move. In the third move, the sliding window moves one step, corresponding to buffer regions 3, 4, and 5, with data values ​​of 8, 9, and 10 respectively. Again, the yellow window's data values ​​8 and 9 represent the values ​​previously stored in the buffer, while the green window's data value 10 represents the value newly entered during the move.

[0046] 2. For scenarios where the given value of the sliding window length calculated based on the current power grid frequency is greater than the current sliding window length.

[0047] like Figure 2 As described above, when the difference between the given sliding window length and the current sliding window length is greater than 0, the sliding window length can be increased successively as the sliding window moves, and a sliding summation can be performed. Finally, the mean value is calculated based on the summation result to achieve power data output with ripple suppression. At this time, as the sliding window moves, the result of the sliding summation, DataSum, increases. _N It can be represented by the following expression: DataSum _N = DataSum _N-1 +DataReal-DataBuff+ DataBuffOnedelay.

[0048] Here, DataBuffOnedelay represents the data value corresponding to the extension of the buffer by one step after the sliding window moves. Theoretically, DataBuffOnedelay = DataBuff.

[0049] like Figure 4 As shown, taking a sliding window with a length of 3 and moving 3 times as an example: After the first move, the sliding window corresponds to buffer regions 1, 2, and 3, with data values ​​6, 7, and 8 respectively. The yellow window's data values ​​6 and 7 represent the values ​​previously stored in the buffer, while the green window's data value 8 represents the value newly entered during the sliding window's move. During the second move, the sliding window moves by one step, and its length increases by one step. At this point, the sliding window corresponds to buffer regions 1, 2, 3, and 4, with data values ​​6, 7, 8, and 9 respectively. The blue window's data value 6 represents the value after the sliding window moves one step backward from the end of the buffer, the yellow window's data values ​​7 and 8 represent the values ​​previously stored in the buffer, and the green window's data value 9 represents the value newly entered during the sliding window's move. During the third move, the sliding window moves by one step, and the length of the sliding window increases by one step. At this time, the sliding window corresponds to regions 1, 2, 3, 4, and 5 of the buffer, and the data values ​​corresponding to each region are 6, 7, 8, 9, and 10, respectively. Among them, the data value 6 corresponding to the blue window represents the data value of the buffer extending backward by one step after the sliding window completes the move; the data values ​​7, 8, and 9 corresponding to the yellow window represent the values ​​previously stored in the buffer; and the data value 10 corresponding to the green window represents the value newly entered into the sliding window during the move.

[0050] 3. For scenarios where the given value of the sliding window length calculated based on the current power grid frequency is less than the current sliding window length.

[0051] like Figure 2 As shown, the difference between the given sliding window length and the current sliding window length is less than 0. The sliding window length can be shortened successively as it moves, and a sliding summation can be performed. Finally, the mean of the summation result is calculated to achieve power data output with ripple suppression. The result of the sliding summation, DataSum, increases as the sliding window moves. _N It can be represented by the following expression: DataSum _N = DataSum _N-1 +DataReal-DataBuff- DataBuffend.

[0052] Here, DataBuffOnedelay represents the data value corresponding to the length that the end of the buffer is extended forward after the sliding window moves.

[0053] like Figure 5As shown, taking a sliding window with a length of 3 and moving 3 times as an example: After the first move, the sliding window corresponds to buffer regions 1, 2, and 3, with data values ​​6, 7, and 8 respectively. The yellow window's data values ​​6 and 7 represent the values ​​previously stored in the buffer, while the green window's data value 8 represents the value newly entered when the sliding window moves. In the second move, the sliding window moves one step, and its length decreases by one step. At this point, the sliding window corresponds to buffer regions 3 and 4, with data values ​​8 and 9 respectively. The red window's data value 7 represents the value after the sliding window moves forward one step from the end of the buffer, the yellow window's data value 8 represents the value previously stored in the buffer, and the green window's data value 9 represents the value newly entered when the sliding window moves. During the third move, the sliding window moves by one step, and at the same time, the length of the sliding window shortens by one step. That is, at this time, the sliding window corresponds to region 5 of the buffer, and the data value corresponding to this region is 10. Among them, the data value 9 corresponding to the red window represents the data value of the end of the buffer extending forward by one step after the sliding window completes the move, and the data value 10 corresponding to the green window represents the value newly entered into the sliding window when the sliding window moves.

[0054] In this embodiment, due to the limited memory in the cache, an excessively large sliding window length may lead to data loss or processor malfunction. Furthermore, both excessively large and excessively small sliding window lengths will increase the time required for the sliding window length to recover to the baseline value. Therefore, when adjusting the sliding window length, it is necessary to set an upper and lower limit. When the given sliding window length is greater than the current sliding window length and the current sliding window length has reached the upper limit, the current sliding window length can be kept unchanged. Conversely, when the given sliding window length is less than the current sliding window length and the current sliding window length has reached the lower limit, the current sliding window length can also be kept unchanged.

[0055] Understandably, there are multiple ways to set the upper and lower limits of the sliding window length. For example, the upper and lower limits can be set directly as a fixed proportion of the baseline sliding window length value, such as setting 80% of the baseline sliding window length value as the lower limit and 120% as the upper limit. Alternatively, the upper and lower limits can be set based on the memory of the cache; or they can be set based on the safe range of the power grid frequency. In this embodiment, it is preferable to set the upper and lower limits of the sliding window length based on the safe range of the power grid frequency.

[0056] Specifically, a safe range for the power grid frequency is set, and the ratio of the switching frequency to the lower limit of the safe range of the power grid frequency is used as the upper limit of the sliding window length, while the ratio of the switching frequency to the upper limit of the safe range of the power grid frequency is used as the lower limit of the sliding window length.

[0057] To facilitate understanding, a detailed explanation using specific parameters will be provided below. Taking a 220V, 50Hz power grid as an example, the safe frequency range of the power grid is generally 45Hz~55Hz. Therefore, the upper limit of the sliding window length is 20000 / 45≈444.4, which is taken as 444; the lower limit of the sliding window length is 20000 / 55≈363.6, which is taken as 367. That is, the adjustment range of the sliding window length is [367, 444].

[0058] Another aspect of this application provides an electronic device, in one preferred embodiment of which includes a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program to implement the above-described dynamic sliding window filtering method.

[0059] Another aspect of this application provides a computer-readable storage medium, in a preferred embodiment of which a computer program is stored on the storage medium; when the computer program is executed by a processor, it implements the above-described dynamic sliding window filtering method.

[0060] The basic principles, main features, and advantages of this application have been described above. Those skilled in the art should understand that this application is not limited to the above embodiments. The embodiments and descriptions in the specification are merely the principles of this application. Various changes and modifications can be made to this application without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claims. The scope of protection claimed by this application is defined by the appended claims and their equivalents.

Claims

1. A dynamic sliding window filtering method, characterized in that, Includes the following steps: The given value of the sliding window length is calculated and updated in real time based on the currently collected power grid frequency. Compare the obtained given sliding window length with the current sliding window length; If the given value of the sliding window length is equal to the current sliding window length, keep the current sliding window length unchanged; If the given value for the sliding window length is greater than the current sliding window length, the sliding window length will be gradually increased according to the set method. If the given value for the sliding window length is less than the current sliding window length, the sliding window length will be gradually shortened according to the set method.

2. The dynamic sliding window filtering method as described in claim 1, characterized in that, The given value for the sliding window length is equal to the ratio of the switching frequency to the currently collected power grid frequency.

3. The dynamic sliding window filtering method as described in claim 1, characterized in that, When the given value of the sliding window length is not equal to the current sliding window length, the sliding window length will be increased or decreased according to the set value as the number of times the sliding window moves increases.

4. The dynamic sliding window filtering method as described in claim 3, characterized in that, The setting for increasing or decreasing the length of the sliding window is an integer multiple of the single movement step of the sliding window.

5. The dynamic sliding window filtering method as described in claim 4, characterized in that, The setting for increasing or decreasing the length of the sliding window is the single movement step of the sliding window.

6. The dynamic sliding window filtering method as described in claim 1, characterized in that, The length of the sliding window is increased by extending backward from the end of the buffer corresponding to the sliding window; the length of the sliding window is shortened by decreasing forward from the end of the buffer corresponding to the sliding window.

7. The dynamic sliding window filtering method according to any one of claims 1-6, characterized in that, Set the upper and lower limits of the sliding window length; if the given value of the sliding window length is greater than the current sliding window length and the current sliding window length has reached the upper limit, keep the current sliding window length unchanged; if the given value of the sliding window length is less than the current sliding window length and the current sliding window length has reached the lower limit, keep the current sliding window length unchanged.

8. The dynamic sliding window filtering method as described in claim 7, characterized in that, Set a safe range for the power grid frequency. Use the ratio of the switching frequency to the lower limit of the safe range of the power grid frequency as the upper limit of the sliding window length, and use the ratio of the switching frequency to the upper limit of the safe range of the power grid frequency as the lower limit of the sliding window length.

9. An electronic device, characterized in that, It includes a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program to implement the dynamic sliding window filtering method as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program; when the computer program is executed by a processor, it implements the dynamic sliding window filtering method as described in any one of claims 1-8.

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