Power distribution network harmonic index data evaluation, transmission method and system

Abstract

The application relates to a power distribution network harmonic index data evaluation, transmission method and system, the method comprising: after obtaining harmonic index data, directly judging whether a harmonic abnormal event occurs in real time according to the harmonic index data, so that the uploaded harmonic abnormal event has real-time performance. The harmonic index data is fitted to obtain fitting coefficients and is uploaded, so that a superior terminal such as a harmonic analysis platform can restore the harmonic index data at any time according to the fitting coefficients. Meanwhile, the application also screens the to-be-transmitted data in the harmonic index data, and only uploads the to-be-transmitted data, thereby reducing the data transmission amount and enabling the superior terminal to verify the restored harmonic index data through the to-be-transmitted data.

Description

Technical Field

[0001] This application relates to the field of power distribution network harmonic analysis technology, and in particular to a method and system for evaluating and transmitting power distribution network harmonic index data. Background Technology

[0002] To address the gradual depletion of fossil fuels and climate change, the widespread development of renewable energy sources such as photovoltaics and wind power is a consensus among major countries and regions worldwide. Distributed generation and microgrids are important technologies for the development and use of renewable energy. In recent years, energy storage, new energy vehicles, and other equipment have also been widely connected to the distribution network. The use of renewable energy involves the extensive application of power electronic devices, which may lead to excessive harmonics in the distribution network, thereby threatening the safe operation of the distribution network.

[0003] To ensure the safe operation of the distribution network, harmonic monitoring devices need to be installed to acquire harmonic data. This data is then transmitted to a harmonic analysis platform on the grid side for harmonic index data evaluation. The harmonic analysis platform requires complete harmonic data for this evaluation. For example, assuming each harmonic index data point is generated every 10 minutes, a single harmonic index data point would generate 6 * 24 = 144 data points per day. The harmonic index data includes 100 indicators such as harmonic voltage, harmonic current, harmonic power, and harmonic phase angle. Modern distribution networks require real-time monitoring of the grid status. Furthermore, distribution networks have a large coverage area; typically, a provincial distribution network needs to install hundreds of thousands of harmonic monitoring devices. Each device would need to transmit 144 * 100 = 14,400 data points per day. In practice, it is difficult to guarantee the complete transmission of data from such a large number of harmonic monitoring devices.

[0004] Furthermore, due to the large amount of data transmitted by the harmonic index, the data transmission speed is slow, and the harmonic analysis platform cannot obtain the harmonic index data in real time for harmonic analysis. As a result, the evaluation of harmonic index data through the harmonic analysis platform lacks real-time capability. Summary of the Invention

[0005] To overcome, to some extent, the problems in related technologies that make it difficult to guarantee the complete transmission of harmonic index data and that harmonic index data evaluation lacks real-time performance, this application provides a method and system for evaluating and transmitting harmonic index data in power distribution networks.

[0006] The proposed solution is as follows:

[0007] According to a first aspect of the embodiments of this application, a method for evaluating and transmitting harmonic index data of a distribution network is provided, including:

[0008] Obtain harmonic index data;

[0009] Based on the harmonic index data, determine in real time whether a harmonic anomaly event has occurred;

[0010] The harmonic index data are fitted to obtain the fitting coefficients;

[0011] Filter the data to be transmitted from the harmonic index data;

[0012] The harmonic anomaly event, the fitting coefficient, and the data to be transmitted are uploaded.

[0013] Preferably, the step of determining in real time whether a harmonic anomaly event has occurred based on the harmonic index data includes:

[0014] Obtain the harmonic voltage generated in the current time period from the harmonic index data;

[0015] When the harmonic voltage generated in the current time period exceeds the set harmonic distortion rate limit, it is judged as a harmonic abnormality event.

[0016] Preferably, the step of determining in real time whether a harmonic anomaly event has occurred based on the harmonic index data further includes:

[0017] Obtain the harmonic power time series from the harmonic index data;

[0018] The harmonic power time series is divided into segments, and the segment corresponding to the current time period is determined as the initial segment from the divided segments.

[0019] After a preset time interval, a sliding window is applied to the initial segment to obtain the adjacent segments of the initial segment;

[0020] The initial segment is compared with the adjacent segment, and if the ratio exceeds a preset threshold, it is determined that a harmonic anomaly event has occurred.

[0021] Preferably, the method further includes:

[0022] When a loop is in progress, the adjacent segment is used as the initial segment in the next loop, and the loop is executed.

[0023] Preferably, comparing the initial segment with the adjacent segment includes:

[0024] Calculate the sequence of differences between the individual harmonic power values ​​and the average harmonic power of the segment in the initial segment and the adjacent segment, respectively.

[0025] The initial segment and the corresponding difference value sequence are fitted to obtain the initial fitting coefficients;

[0026] The adjacent segments and the corresponding difference value sequences are fitted to obtain the adjacent fitting coefficients;

[0027] The initial fitting coefficients and the adjacent fitting coefficients are compared.

[0028] Preferably, the step of sliding a window through the initial segment to obtain the adjacent segments of the initial segment includes:

[0029] Using the number of harmonic powers in the initial segment as the length, and the value of the individual harmonic power unit after the second order in the initial segment as the starting value of the adjacent segment, the adjacent segment is obtained through a sliding window.

[0030] Preferably, the step of fitting the harmonic index data to obtain fitting coefficients includes:

[0031] The harmonic index data are categorized.

[0032] Construct a polynomial fitting function for various harmonic index data, wherein each term of the polynomial fitting function is the product of the harmonic index data and the polynomial coefficients.

[0033] The polynomial fitting function is fitted until the fitting function error is lower than a preset error threshold, and the coefficients of each polynomial are output as fitting coefficients.

[0034] Preferably, if the fitting function error cannot be lower than a preset error threshold, the harmonic index data is fitted in segments.

[0035] Preferably, the step of filtering the data to be transmitted from the harmonic index data includes:

[0036] The harmonic index data are categorized.

[0037] The starting value, ending value, maximum value, minimum value, and average value of various harmonic index data are selected as the data to be transmitted for various harmonic index data.

[0038] According to a second aspect of the embodiments of this application, a system for evaluating and transmitting harmonic index data of a distribution network is provided, comprising:

[0039] The module acquires harmonic index data;

[0040] The evaluation module is used to determine in real time whether a harmonic anomaly event has occurred based on the harmonic index data;

[0041] The fitting module is used to fit the harmonic index data to obtain fitting coefficients;

[0042] The filtering module is used to filter the data to be transmitted from the harmonic index data;

[0043] The upload module is used to upload the harmonic anomaly event, the fitting coefficient, and the data to be transmitted.

[0044] The technical solution provided in this application can include the following beneficial effects: The method for evaluating and transmitting harmonic index data in the distribution network in this application, after acquiring the harmonic index data, directly determines in real time whether a harmonic anomaly event has occurred based on the harmonic index data, making the uploaded harmonic anomaly event real-time. The harmonic index data is fitted to obtain fitting coefficients and then uploaded, allowing upper-level terminals such as harmonic analysis platforms to reconstruct the harmonic index data at any given time based on the fitting coefficients. Simultaneously, this application also filters the data to be transmitted from the harmonic index data, uploading only the data to be transmitted, which not only reduces the amount of data transmission but also allows the upper-level terminal to verify the reconstructed harmonic index data using the data to be transmitted.

[0045] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0046] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0047] Figure 1 This is a flowchart illustrating a method for evaluating and transmitting harmonic index data in a power distribution network, provided in one embodiment of this application.

[0048] Figure 2 This is a schematic diagram of an initial segment sliding window process provided in one embodiment of this application;

[0049] Figure 3 This is a schematic diagram of the structure of a power distribution network harmonic index data evaluation and transmission system provided in one embodiment of this application.

[0050] Attached image labels: Acquisition module-21; Evaluation module-22; Fitting module-23; Filtering module-24; Upload module-25. Detailed Implementation

[0051] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0052] Example 1

[0053] Figure 1 This is a flowchart illustrating a method for evaluating and transmitting harmonic index data in a distribution network, provided in one embodiment of this application. (Refer to...) Figure 1 A method for evaluating and transmitting harmonic index data in a power distribution network, comprising:

[0054] S11: Obtain harmonic index data;

[0055] There is a lot of harmonic index data in the distribution network. Taking the transmission of 2nd to 25th harmonics as an example, 100 harmonic index data such as harmonic voltage, harmonic current, harmonic power, and harmonic phase angle can be derived. The harmonic index data can be collected by existing distribution network harmonic monitoring devices.

[0056] S12: Determine in real time whether a harmonic anomaly event has occurred based on harmonic index data;

[0057] S13: Fit the harmonic index data to obtain the fitting coefficients;

[0058] S14: Filter the data to be transmitted from the harmonic index data;

[0059] S15: Upload the harmonic anomaly events, fitting coefficients, and data to be transmitted.

[0060] It should be noted that the technical solution in this embodiment is applied to the field of power system distribution network operation and analysis, specifically in the evaluation and data transmission of power system distribution network harmonic index data.

[0061] It should be noted that, in order to achieve rapid and real-time evaluation of distribution network harmonic index data, this embodiment evaluates based on the harmonic voltage and harmonic power terms within the harmonic index data. Specifically:

[0062] 1) Based on the harmonic voltage term in the harmonic index data, determine in real time whether any abnormal harmonic events have occurred, including:

[0063] Obtain the harmonic voltage generated in the current time period from the harmonic index data;

[0064] When the harmonic voltage generated in the current time period exceeds the set harmonic distortion rate limit, it is judged as a harmonic abnormality event.

[0065] It should be noted that, since the national standard specifies limits for each harmonic voltage and harmonic distortion rate, the assessment based on harmonic voltage is made with reference to the harmonic distortion rate limits specified in the national standard. If the limit is exceeded, it is judged as a harmonic anomaly event. For example, the national standard specifies that the harmonic distortion content limit in a 10kV even-order harmonic voltage is 1.6%. If the harmonic distortion content in the 6th harmonic voltage is 1.7%, it is judged as a harmonic anomaly event.

[0066] 2) Based on the harmonic power term in the harmonic index data, determine in real time whether any abnormal harmonic events have occurred, including:

[0067] Obtain the time series of harmonic power from the harmonic index data;

[0068] The harmonic power time series is divided into segments, and the segment corresponding to the current time period is determined as the initial segment from the divided segments.

[0069] After a preset time interval, a sliding window is applied to the initial segment to obtain the adjacent segments of the initial segment;

[0070] The initial segment is compared with the adjacent segments, and a harmonic anomaly event is judged to have occurred when the ratio exceeds a preset threshold.

[0071] It is understandable that harmonic power is calculated from harmonic voltage, harmonic current, and harmonic phase angle, thus it can comprehensively represent the characteristics of harmonics.

[0072] The harmonic power is calculated as follows:

[0073] P = U * I * cos(θ)

[0074] Where P is the harmonic power, U is the harmonic voltage amplitude, I is the harmonic current, and θ is the phase angle difference between the harmonic voltage and the harmonic current.

[0075] It should be noted that comparing the initial segment with adjacent segments includes:

[0076] Calculate the sequence of differences between the individual harmonic power values ​​and the average harmonic power of the segment in the initial segment and adjacent segments respectively;

[0077] The initial segment and the corresponding difference value sequence of the initial segment are fitted to obtain the initial fitting coefficients;

[0078] The adjacent segments and their corresponding difference value sequences are fitted to obtain the adjacent fitting coefficients.

[0079] The initial fitting coefficients and the adjacent fitting coefficients are compared.

[0080] In practice, the known harmonic power sequence is divided into i segments. Within these segments, the segment corresponding to the current time period is selected as the initial segment, denoted as Pi(t), where Pi(t) = [Pi(1), Pi(2), ..., Pi(N)], and t ranges from [1, N]. N represents the number of harmonic powers contained in a segment. For example, if a harmonic power is generated every 10 minutes, and one hour is considered a segment, then N is 6.

[0081] Find the average value P of the N harmonic powers in Pi(t). i avg :

[0082]

[0083] Calculate the N powers and P under Pi(t) respectively. i avg The difference value yields a new sequence P i * (t), P i * (t)=[P i * (1),P i * (2),…,P i * (N)]:

[0084] P i * (t)=P i (t)-P avg

[0085] Preferably, in this embodiment, an exponential function is used to fit the initial segment and the corresponding difference value sequence, and the initial fitting coefficients are obtained according to the following formula:

[0086]

[0087] The initial fitting coefficients are

[0088] It should be noted that other functions can also be used to fit the initial segment and the corresponding difference value sequence, but this embodiment does not impose any limitations.

[0089] After a preset time interval, a sliding window is applied to the initial segment to obtain adjacent segments. For example, the number of harmonic powers in the initial segment can be used as the length, and the value of at least the second-ranked harmonic power unit in the initial segment can be used as the starting value of the adjacent segments. The adjacent segments are obtained through a sliding window. If a harmonic power is generated every 10 minutes, and one hour is considered one segment, the preset time interval can be set to 20 minutes. That is, after the last harmonic power of the initial segment is generated, a sliding window is applied to the initial segment after a 20-minute interval to obtain the adjacent segments. The adjacent segments include the last four harmonic powers of the initial segment and the two harmonic powers generated within the 20-minute interval.

[0090] It is understandable that in this embodiment, the value of the harmonic power cell at least the second in the initial segment is used as the starting value of the adjacent segment. This is because if the value of the harmonic power cell at the second in the initial segment is used as the starting value of the adjacent segment, the adjacent segment is only shifted by one value based on the initial segment. Therefore, the change amplitude of the adjacent segment is relatively small compared to the initial segment, which is not conducive to determining whether a harmonic anomaly event has occurred.

[0091] After obtaining the adjacent segments, the adjacency fitting coefficients corresponding to the adjacent segments can be obtained using the same method.

[0092] Compare the initial fitting coefficients with the adjacent fitting coefficients:

[0093]

[0094] When the ratio k1 exceeds a preset threshold, it is determined that a harmonic abnormality event has occurred. For example, it can be set to determine that a harmonic abnormality event has occurred when k1≥1.01 or k1≤0.9.

[0095] When a loop is in progress, the adjacent segment is used as the initial segment for the next loop iteration, and the loop is executed. (See reference...) Figure 2 In the first iteration, the initial segment is Pi, and the adjacent segment is Pi+1. In the second iteration, Pi+1 is used as the new initial segment, and a sliding window is applied to Pi+1 to obtain Pi+2, and so on. In this embodiment, the similarity between two adjacent segments is determined by calculating the ratio of the fitting coefficients of each pair of adjacent segments. If the similarity between two adjacent segments does not meet the requirements, it is determined that a harmonic anomaly event has occurred.

[0096] It should be noted that the fitting coefficients obtained by fitting the harmonic index data include:

[0097] Classify the harmonic index data;

[0098] Construct polynomial fitting functions for various harmonic index data, where each term of the polynomial fitting function is the product of the harmonic index data and the polynomial coefficients.

[0099] The polynomial fitting function is fitted until the error of the fitting function is lower than the preset error threshold, and the coefficients of each polynomial are output as fitting coefficients.

[0100] Harmonic index data can be derived into 100 harmonic index data such as harmonic voltage, harmonic current, harmonic power, and harmonic phase angle. Therefore, in this embodiment, the harmonic index data is first classified, and a corresponding polynomial fitting function is constructed for each category of harmonic index data. For example, if a certain harmonic data is HMi, where HMi = [HMi1, HMi2...HMin], then the constructed polynomial fitting function is:

[0101] f(HMi)=b0+b1*HMi+b2*HMi 2 +...b r *HMi r

[0102] Where b is the polynomial coefficient.

[0103] The polynomial fitting function is fitted until the fitting function error is lower than a preset error threshold, and the coefficients of each polynomial are output as fitting coefficients. The fitting error can be determined according to the accuracy of the harmonic monitoring device, for example, 5%. In specific implementation, if the fitting function error cannot be lower than the preset error threshold, the harmonic index data can be fitted in segments.

[0104] It should be noted that other functions can also be used to fit the harmonic index data, but this embodiment does not impose any limitations.

[0105] The technical solution in this embodiment is illustrated by example:

[0106] The second harmonic voltage data of a certain monitoring point object during a certain time period are shown in the table below:

[0107]

[0108]

[0109] The fitted function obtained after fitting is: y = -0.37x 2 +4.72x+20.22, fitting coefficients b0, b1, b2 are 20.22, 4.72, and -0.37 respectively, fitting error is 5.11, average harmonic voltage is 32.01, minimum value is 26, maximum value is 37.2.

[0110] The upper-level terminal, such as a harmonic analysis platform, can obtain the fitting function based on the fitting coefficients, and then reconstruct the second harmonic voltage at any time. The new integer sequence obtained after reconstruction is as follows:

[0111] x: time series y: Harmonic voltage (V) 1 26 2 24.57 3 28.18 4 31.05 5 33.18 6 34.57 7 35.22 8 35.13 9 33.6

[0112] The upper-level terminal obtains the harmonic voltage by restoring the fitting coefficients: the average value is 31.27, the minimum value is 24.57, and the maximum value is 35.22. Compared with the original average value of 32.01, the original minimum value of 26, and the original maximum value of 37.2, after considering the fitting error of 5.11, it can be assessed that the received data is correct.

[0113] It should be noted that the data to be transmitted in the harmonic index data filtering includes:

[0114] Classify the harmonic index data;

[0115] The starting value, ending value, maximum value, minimum value, and average value of various harmonic index data are selected as the data to be transmitted for various harmonic index data.

[0116] Harmonic index data can be derived into 100 harmonic index data such as harmonic voltage, harmonic current, harmonic power, and harmonic phase angle. Therefore, in this embodiment, the harmonic index data is first classified. For each category of harmonic index data, the data to be transmitted is selected and only the data to be transmitted is uploaded. This not only reduces the amount of data transmission, but also allows the upper-level terminal to verify the reconstructed harmonic index data through the data to be transmitted.

[0117] In practice, the starting value, ending value, maximum value, minimum value, and average value are selected from various harmonic index data as the data to be transmitted. Thus, when uploading, only the fitting coefficients, starting value, ending value, maximum value, minimum value, and average value need to be uploaded.

[0118] Preferably, the fitting error can also be uploaded so that the upper-level terminal can evaluate whether the received data is correct based on the fitting error.

[0119] Understandably, when fitting harmonic index data, only three fitting operations are generally needed to complete the fitting process, resulting in three fitting coefficients. The data that needs to be uploaded includes these three fitting coefficients: the initial value, ending value, maximum value, minimum value, and average value of the harmonic index data, along with nine data points for the fitting error. Compared to the existing technology that generates 6*24=144 data points per day for each type of harmonic index data, the data transmission volume is reduced by more than 90%.

[0120] It is understandable that the method for evaluating and transmitting harmonic index data in the distribution network in this embodiment, after acquiring the harmonic index data, directly determines in real time whether a harmonic anomaly event has occurred based on the harmonic index data, ensuring the real-time nature of the uploaded harmonic anomaly events. The harmonic index data is fitted to obtain fitting coefficients, which are then uploaded, allowing the upper-level terminal, such as a harmonic analysis platform, to reconstruct the harmonic index data at any given time based on the fitting coefficients. Simultaneously, this embodiment also filters the data to be transmitted from the harmonic index data, uploading only the data to be transmitted. This not only reduces the amount of data transmission but also allows the upper-level terminal to verify the reconstructed harmonic index data using the data to be transmitted.

[0121] Example 2

[0122] Figure 3 This is a schematic diagram of the structure of a power distribution network harmonic index data evaluation and transmission system according to an embodiment of this application, with reference to... Figure 3 A system for evaluating and transmitting harmonic index data in a power distribution network, comprising:

[0123] Module 21 is used to acquire harmonic index data;

[0124] Evaluation module 22 is used to determine in real time whether a harmonic anomaly event has occurred based on harmonic index data;

[0125] Fitting module 23 is used to fit the harmonic index data to obtain fitting coefficients;

[0126] Filtering module 24 is used to filter the data to be transmitted from the harmonic index data;

[0127] Upload module 25 is used to upload harmonic anomaly events, fitting coefficients, and data to be transmitted.

[0128] It is understood that the distribution network harmonic index data evaluation and transmission system in this embodiment includes: an acquisition module 21, an evaluation module 22, a fitting module 23, a filtering module 24, and an upload module 25. In implementation, the acquisition module 21 acquires harmonic index data; the evaluation module 22 determines in real time whether a harmonic anomaly event has occurred based on the harmonic index data; the fitting module 23 fits the harmonic index data to obtain fitting coefficients; the filtering module 24 filters the data to be transmitted from the harmonic index data; and the upload module 25 uploads the harmonic anomaly event, the fitting coefficients, and the data to be transmitted. In this embodiment, the determination of whether a harmonic anomaly event has occurred is directly based on the harmonic index data in real time, ensuring the real-time nature of the uploaded harmonic anomaly events. Fitting the harmonic index data to obtain fitting coefficients and uploading them allows the upper-level terminal, such as a harmonic analysis platform, to reconstruct the harmonic index data at any given time based on the fitting coefficients. Simultaneously, this embodiment also filters the data to be transmitted from the harmonic index data, uploading only the data to be transmitted, which not only reduces the amount of data transmission but also allows the upper-level terminal to verify the reconstructed harmonic index data using the data to be transmitted.

[0129] It is understood that the same or similar parts in the above embodiments can be referred to each other, and the contents not described in detail in some embodiments can be referred to the same or similar contents in other embodiments.

[0130] It should be noted that in the description of this application, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this application, unless otherwise stated, "a plurality of" means at least two.

[0131] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the function involved, as will be understood by those skilled in the art to which embodiments of this application pertain.

[0132] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0133] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0134] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0135] The storage media mentioned above can be read-only memory, disk, or optical disk, etc.

[0136] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer 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.

[0137] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for evaluating and transmitting harmonic index data in a distribution network, characterized in that, include: Obtain harmonic index data; Based on the harmonic index data, determine in real time whether a harmonic anomaly event has occurred; The harmonic index data are fitted to obtain the fitting coefficients; Filter the data to be transmitted from the harmonic index data; Upload the harmonic anomaly event, the fitting coefficients, and the data to be transmitted; The step of determining in real time whether a harmonic anomaly event has occurred based on the harmonic index data includes: Obtain the harmonic power time series from the harmonic index data; divide the harmonic power time series into segments, and determine the segment corresponding to the current time period as the initial segment; after a preset time interval, apply a sliding window to the initial segment to obtain the adjacent segments of the initial segment; compare the initial segment with the adjacent segments, and determine that a harmonic anomaly event has occurred when the ratio exceeds a preset threshold; the ratio is obtained in the following way: The step of comparing the initial segment with the adjacent segment includes: calculating the difference sequence of each harmonic power unit value relative to the average harmonic power of the segment in the initial segment and the adjacent segment respectively; fitting the difference sequence of the initial segment to obtain an initial fitting coefficient; fitting the difference sequence of the adjacent segment to obtain an adjacent fitting coefficient; and comparing the initial fitting coefficient with the adjacent fitting coefficient. The step of applying a sliding window to the initial segment to obtain the adjacent segments of the initial segment includes: Using the number of harmonic powers in the initial segment as the length, and the value of the individual harmonic power unit after the second order in the initial segment as the starting value of the adjacent segment, the adjacent segment is obtained through a sliding window.

2. The method according to claim 1, characterized in that, The method further includes: When a loop is in progress, the adjacent segment is used as the initial segment in the next loop, and the loop is executed.

3. The method according to claim 1, characterized in that, The step of fitting the harmonic index data to obtain fitting coefficients includes: The harmonic index data are categorized. Construct a polynomial fitting function for various harmonic index data, wherein each term of the polynomial fitting function is the product of the harmonic index data and the polynomial coefficients. The polynomial fitting function is fitted until the fitting function error is lower than a preset error threshold, and the coefficients of each polynomial are output as fitting coefficients.

4. The method according to claim 3, characterized in that, If the error of the fitting function cannot be lower than the preset error threshold, then the harmonic index data will be fitted in segments.

5. The method according to claim 1, characterized in that, The process of filtering the data to be transmitted from the harmonic index data includes: The harmonic index data are categorized. The starting value, ending value, maximum value, minimum value, and average value of various harmonic index data are selected as the data to be transmitted for various harmonic index data.

6. A system for evaluating and transmitting harmonic index data in a power distribution network, characterized in that, The system for performing the method as described in any one of claims 1-5 includes: The module acquires harmonic index data; The evaluation module is used to determine in real time whether a harmonic anomaly event has occurred based on the harmonic index data; The fitting module is used to fit the harmonic index data to obtain fitting coefficients; The filtering module is used to filter the data to be transmitted from the harmonic index data; The upload module is used to upload the harmonic anomaly event, the fitting coefficients, and the data to be transmitted; The evaluation module is specifically used for: Obtain the harmonic power time series from the harmonic index data; divide the harmonic power time series into segments, and determine the segment corresponding to the current time period as the initial segment in the divided segments; after a preset time interval, perform a sliding window on the initial segment to obtain the adjacent segments of the initial segment; compare the initial segment with the adjacent segments, and determine that a harmonic abnormality event has occurred when the ratio exceeds a preset threshold; The evaluation module is further used for: Using the number of harmonic powers in the initial segment as the length, and the value of the individual harmonic power unit after the second order in the initial segment as the starting value of the adjacent segment, the adjacent segment is obtained through a sliding window.

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