Power distribution network harmonic traceability method and system

Abstract

The invention belongs to the technical field of power distribution networks, and provides a power distribution network harmonic traceability method and system, and the method comprises the steps: obtaining a distributed photovoltaic distribution detection path in a to-be-detected power distribution network; according to the acquired distributed detection path, acquiring asynchronous data of a plurality of distributed photovoltaics; key features of the collected asynchronous data are extracted, and a time sequence of the power distribution network is constructed; preliminarily screening potential harmonic sources of the power distribution network based on the constructed time sequence; and according to the encoder-decoder, the attention mechanism model and the potential harmonic source of the power distribution network, performing harmonic traceability of the power distribution network.

Description

Technical Field

[0001] This invention belongs to the field of power distribution network technology, and specifically relates to a method and system for tracing the source of harmonics in power distribution networks. Background Technology

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

[0003] With the decline in the cost of photovoltaic power generation devices and the implementation of relevant support policies, the penetration rate of small-capacity distributed photovoltaic inverters in low-voltage distribution networks is rapidly increasing. Power quality issues such as high-frequency harmonics caused by their start-up / shutdown, shading, and sudden power fluctuations are amplified and superimposed at the end of the distribution network, forming a "gray pollution" zone that traditional monitoring methods cannot detect. Multiple incidents of precision manufacturing production line tripping caused by unknown harmonic sources have occurred in various locations, resulting in serious economic losses.

[0004] The existing power quality monitoring of distributed photovoltaic grid-connected points mainly relies on indirect estimation at the distribution network master station level, which has the problem of "not being able to detect or accurately judge" harmonic pollution; there is "no clear understanding" of the actual power quality of distributed photovoltaic grid-connected points, so conservative strategies such as "one-size-fits-all" power limiting and grid connection limitation are necessary, which restricts the space for new energy consumption.

[0005] To ensure accurate measurement of distributed photovoltaic (PV) power quality, direct measurement terminals need to be installed at each grid-connected point, but this is difficult to achieve due to cost constraints. Having maintenance personnel use mobile power quality testing devices to test all distributed PV systems individually could reduce equipment investment, but existing testing equipment is bulky and has complex wiring, resulting in low work efficiency. Furthermore, when a single mobile testing device tests multiple distributed PV grid-connected points, synchronous data acquisition is not possible, making direct harmonic source tracing difficult.

[0006] Therefore, in response to the distributed photovoltaic harmonic problem faced under the current investment level of the distribution network, it is urgent to study a portable distributed photovoltaic power quality detection device and a method for tracing the source of asynchronous data harmonics using this device, so as to achieve accurate source tracing of harmonic pollution at the distributed photovoltaic grid connection point while minimizing the workload of distribution network operation and maintenance personnel. Summary of the Invention

[0007] To address the aforementioned issues, this invention proposes a method and system for tracing the source of harmonics in a power distribution network. This method enables power quality testing of multiple distributed photovoltaic grid-connected points within the same area during a single operation and maintenance task. It fundamentally solves the technical challenges of high cost, strict synchronization requirements, and complex deployment in existing harmonic monitoring technologies, thereby achieving accurate harmonic source tracing under asynchronous detection conditions.

[0008] According to some embodiments, the first solution of the present invention provides a method for tracing the source of harmonics in a power distribution network, which adopts the following technical solution: A method for tracing the source of harmonics in a power distribution network includes: Obtain the distributed detection path of distributed photovoltaic power in the distribution network to be detected; Based on the obtained distributed detection path, collect asynchronous data from several distributed photovoltaic systems; Extract key features from the collected asynchronous data to construct a time series of the power distribution network; Based on the constructed time series, potential harmonic sources in the distribution network were initially screened out; Harmonic source tracing of the distribution network is performed based on the encoder-decoder and attention mechanism model and the potential harmonic sources of the distribution network.

[0009] As a further technical limitation, after obtaining the distributed detection path of distributed photovoltaics in the distribution network to be tested, a measurement point is selected as a reference point at the low-voltage outlet of the distribution transformer or at the common connection point of the regional power grid, and the common influence of all harmonic sources in the region is sensed based on the selected reference point.

[0010] As a further technical limitation, during the process of collecting asynchronous data from several distributed photovoltaic systems, a time measurement is performed sequentially at each grid connection point according to the obtained distributed detection path. The collected asynchronous data includes at least high-density sampling data, power quality index data, and absolute timestamps.

[0011] As a further technical limitation, the process of initially screening potential harmonic sources in the distribution network involves selecting a certain characteristic time series of a reference point as a reference signal, taking the same characteristic sequence for each photovoltaic grid-connected point Pi, calculating the normalized cross-correlation between the reference signal and the characteristic sequence, using the obtained correlation coefficient as a preliminary screening index, and screening out the candidate points with the highest correlation to the harmonic activity of the reference point, thus completing the preliminary screening of potential harmonic sources in the distribution network.

[0012] As a further technical limitation, in the process of harmonic source tracing in the distribution network, the feature sequence of each distributed photovoltaic grid-connected point is sequentially input into the encoder-decoder and attention mechanism model to obtain a virtual reference point sequence synchronized with the feature sequence. The dynamic time adjustment method (DTW) is used to calculate the similarity distance between each virtual reference point sequence and the real feature sequence of the reference point. When the obtained similarity distance exceeds the distance threshold, the distributed photovoltaic grid-connected point is the harmonic source of the distribution network, thus completing the harmonic source tracing of the distribution network.

[0013] As a further technical limitation, the obtained distribution network harmonic sources are verified according to auxiliary criteria, namely, the highest similarity to the harmonic mode of the reference point or the smallest similarity distance and the largest local harmonic current amplitude.

[0014] According to some embodiments, the second aspect of the present invention provides a power distribution network harmonic source tracing system, which adopts the following technical solution: A power distribution network harmonic source tracing system, comprising: The acquisition module is configured to acquire the distributed detection path of distributed photovoltaics in the distribution network to be detected; The acquisition module is configured to collect asynchronous data from several distributed photovoltaic systems based on the acquired distribution detection paths. A construction module is configured to extract key features from the collected asynchronous data and construct the time series of the distribution network. The screening module is configured to initially screen potential harmonic sources in the distribution network based on the constructed time series. The source tracing module is configured to perform harmonic source tracing of the distribution network based on the encoder-decoder and attention mechanism model and the potential harmonic sources of the distribution network.

[0015] According to some embodiments, a third aspect of the present invention provides a computer-readable storage medium, employing the following technical solution: A computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the power distribution network harmonic source tracing method as described in the first aspect of the present invention.

[0016] According to some embodiments, the fourth aspect of the present invention provides an electronic device, which adopts the following technical solution: An electronic device includes a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps in the power distribution network harmonic source tracing method as described in the first aspect of the present invention.

[0017] According to some embodiments, the fifth aspect of the present invention provides a computer program product, which adopts the following technical solution: A computer program product includes software code, wherein the program in the software code performs the steps in the power distribution network harmonic source tracing method as described in the first aspect of the present invention.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention enables power quality detection for multiple distributed photovoltaic grid-connected points within the same area, fundamentally solving the technical challenges of high cost, strict synchronization requirements, and complex deployment in existing technologies for harmonic monitoring, and achieving accurate harmonic source tracing under asynchronous detection conditions. Attached Figure Description

[0019] The accompanying drawings, which form part of this embodiment, are used to provide a further understanding of this embodiment. The illustrative embodiments and their descriptions are used to explain this embodiment and do not constitute an improper limitation of this embodiment.

[0020] Figure 1 This is a flowchart of the power distribution network harmonic source tracing method in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the results from the distributed photovoltaic power quality detection device in Embodiment 1 of the present invention; Figure 3 This is a structural block diagram of the power distribution network harmonic source tracing system in Embodiment 2 of the present invention. Detailed Implementation

[0021] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0022] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0023] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0024] In this invention, terms such as "upper," "lower," "left," "right," "front," "back," "vertical," "horizontal," "side," and "bottom" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used only to facilitate the description of the structural relationships of the various components or elements of this invention and do not specifically refer to any component or element in this invention. They should not be construed as limiting the invention.

[0025] In this invention, terms such as "fixed connection," "connected," and "linked" should be interpreted broadly, indicating a fixed connection, an integral connection, or a detachable connection; a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can determine the specific meaning of these terms in this invention based on the specific circumstances, and they should not be construed as limitations on the invention.

[0026] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0027] Example 1 Embodiment 1 of this invention introduces a method for tracing the source of harmonics in a power distribution network.

[0028] like Figure 1 The method for tracing the source of harmonics in a power distribution network, as shown, includes: Obtain the distributed detection path of distributed photovoltaic power in the distribution network to be detected; Based on the obtained distributed detection path, collect asynchronous data from several distributed photovoltaic systems; Extract key features from the collected asynchronous data to construct a time series of the power distribution network; Based on the constructed time series, potential harmonic sources in the distribution network were initially screened out; Harmonic source tracing of the distribution network is performed based on the encoder-decoder and attention mechanism model and the potential harmonic sources of the distribution network.

[0029] This embodiment uses, as follows: Figure 2 The distributed photovoltaic power quality testing device shown has power quality testing capabilities, supporting the detection of voltage deviation, voltage fluctuation and flicker, harmonics, and interharmonics, meeting power quality standard requirements. It can draw power without interrupting power or disconnecting wires, facilitating rapid testing by personnel upon arrival at the distributed photovoltaic grid-connected point. It also features device configuration, test result query, and rapid test data upload functions. After testing, the results can be viewed directly or quickly transmitted to maintenance personnel's laptops, tablets, or mobile phones via Bluetooth for subsequent data analysis and harmonic source tracing.

[0030] Compared with existing mobile power quality testing devices, the portable distributed photovoltaic power quality testing device in this embodiment is highly portable and easy to operate, making it more suitable for staff to conduct power quality testing on a large number of distributed photovoltaic grid-connected points in power distribution network scenarios, as detailed below: (1) Lightweight hardware and software design reduces the overall weight of the device and enhances portability. To increase the portability of the device, the complex data analysis and harmonic source tracing functions with large computational loads are placed in the workstation of the distribution network control center. The power quality detection device only retains data acquisition and simple data calculation functions. At the same time, the device does not need to establish a communication network with the distribution network control center. Instead, it transmits measurement data to the laptops, tablets or mobile phones of the operation and maintenance personnel via Bluetooth communication. The operation and maintenance personnel collect all the data from the distributed photovoltaic grid-connected points and then upload it to the distribution control workstation. Therefore, the device only needs to use smaller hardware boards and control chips, and does not require large-capacity batteries and cooling fans, thereby reducing the overall weight of the portable distributed photovoltaic power quality detection device and enhancing portability.

[0031] (2) Power can be extracted without interrupting power supply or disconnecting wiring by using magnetic steel wire and current clamps, simplifying the equipment wiring process. When sampling the voltage at the grid-connected point of distributed photovoltaic power, sampling is performed using magnetic steel wire. One end of the magnetic steel wire is connected to the detection equipment, and the other end is a magnetic head fixed to the power extraction device. The power extraction device is placed above the photovoltaic circuit breaker, and the magnetic head is connected to the wiring screw. The magnetic force enables easy and safe power extraction without interrupting power supply or disconnecting wiring. When sampling the current at the grid-connected point, the photovoltaic field current is sampled using a three-phase current clamp mode, converting the large current signal into a small current signal with a current range of 100mA-100A, which also enables easy and safe power extraction without interrupting power supply or disconnecting wiring.

[0032] For distribution networks containing a large number of distributed photovoltaic (PV) systems, a method is proposed that utilizes a single portable power quality monitoring device for asynchronous detection and employs artificial intelligence algorithms to trace harmonic sources. The method first uses the portable device to sequentially inspect multiple PV grid-connected points, recording power quality data (especially harmonic spectrum data) and absolute timestamps at each point. Then, the voltage harmonics at the transformer outlet or a relatively stable point of common coupling (PCC) in the grid are selected as a reference benchmark. Deep learning algorithms are used to analyze the correlation and time delay characteristics between the harmonic data at each monitoring point and the reference benchmark, thereby inferring the propagation path and direction of the harmonics and ultimately identifying the dominant harmonic source.

[0033] Compared to existing methods for tracing harmonic sources in distributed photovoltaic power distribution networks, the method in this embodiment does not require modification of existing distribution network lines or the installation of numerous fixed monitoring devices. It utilizes data obtained from inspections conducted by a single portable power quality monitoring device at different times, combined with artificial intelligence algorithms, to accurately locate the main harmonic sources in the distribution network. This reduces the deployment cost of harmonic monitoring and tracing systems and significantly improves operation and maintenance efficiency.

[0034] The method for tracing the source of harmonics in the power distribution network in this embodiment includes the following steps: Step 1: Determine the detection path and select appropriate reference points based on the distribution of distributed photovoltaics in the distribution network to be tested.

[0035] Specifically, maintenance personnel plan an inspection route for all grid-connected distributed photovoltaic points (denoted as points P1, P2, ..., Pn) to be tested within the target area. Simultaneously, a measurement point is selected as a reference point at the low-voltage outlet of the distribution transformer or at the point of common coupling (PCC) of the regional power grid. This point theoretically experiences the combined effects of all harmonic sources within the area, and its voltage is relatively stable.

[0036] Step 2: Use a portable distributed photovoltaic power quality testing device to achieve asynchronous acquisition of measurement data for each distributed photovoltaic grid-connected point.

[0037] Specifically, using the portable distributed photovoltaic power quality monitoring device provided in the first aspect of this invention, measurements are performed sequentially at each grid connection point Pi (i=1~n) for a period of time (e.g., each measurement lasts 5-15 minutes) according to a planned path. The device records the following data: (1) High-density sampling data: voltage and current waveform data of at least 2560 points per second; (2) Power quality index data: including voltage content, effective current value, and harmonic phase angle of each harmonic (e.g., 2nd-50th harmonics); (3) Absolute timestamp: Each data record has a precise absolute time. Although the times at different points are not synchronized, the absolute time is accurate.

[0038] Step 3: Extract key features from waveform data to form time series, generating feature time series such as harmonic amplitude sequences and total harmonic distortion (THD) sequences for each monitoring point with respect to absolute time.

[0039] Step 4: Calculate the cross-correlation between the measurement signals of each distributed photovoltaic grid-connected point and the measurement signals of the reference point, and preliminarily screen out potential harmonic sources.

[0040] Specifically, a characteristic time series of a reference point (such as the amplitude sequence of the h-th harmonic voltage) is selected as the reference signal Sref(t). For each photovoltaic grid-connected point Pi, the same time series is selected. Feature sequence Since Si(t) and Sref(t) are measured at different time points, directly calculating the cross-correlation function is meaningless. Therefore, instead of directly comparing the absolute values ​​of the data, we compare their fluctuation patterns (trends, shapes). We calculate the normalized cross-correlation of Si(t) and Sref(t), or use the DTW algorithm to calculate the similarity distance between sequences. Although the absolute timestamps of different measurement points are different, if the change patterns of two signals are highly similar, it indicates that they have a high degree of homology and correlation. We use this correlation coefficient as a preliminary screening criterion to select several candidate points with the highest correlation to the harmonic activity of the reference point for further detailed analysis. This reduces the computational burden.

[0041] Step 5: Construct a model based on encoder-decoder (Seq2Seq) and attention mechanism to achieve virtual synchronization of measurement signals from different distributed photovoltaic grid-connected points.

[0042] Specifically, the data collected synchronously is first used as a training set to obtain the data required for training the model. The specific acquisition methods include: temporarily deploying multiple synchronous detection devices to collect data in the short term, and using software such as PSCAD, MATLAB / Simulink to build a power distribution network simulation model containing multiple distributed photovoltaics to generate a large amount of high-quality synchronous data.

[0043] Secondly, in the model structure design phase, the input Pi point has a time window feature sequence Si(t) = [X{tk}, ..., Xt], where the feature X can be a vector containing the amplitude, phase, and total power of each harmonic. The output model predicts the reference point's corresponding feature sequence Sref(t) = [Y{t+1}, ..., Y{t+m}] over a future time period. The encoder is typically composed of LSTM (Long Short-Term Memory) or GRU (Gated Recurrent Unit) layers. It reads the input S(t) sequence and compresses it into a context vector containing all the important information of the sequence. The attention mechanism is a key improvement. Traditional Seq2Seq models rely on the last hidden state as the context vector, which loses information from the beginning of the sequence. The attention mechanism allows the decoder to "look back" at the hidden states of all encoder steps at each step of generating the output and assign different weights to different steps. This means that the model can learn to focus on the part of the Pi sequence that is most relevant to the current prediction of the reference point (e.g., the starting point of a harmonic abrupt change). The decoder is also composed of LSTM / GRU layers. It generates the predicted output sequence Sref(t) step by step based on the context vector and attention weights provided by the encoder.

[0044] Finally, the prepared synchronized data pairs are used for training, with mean squared error (MSE) or mean absolute error (MAE) as the loss function, to train the encoder-decoder model with the attention mechanism. The goal is to make the predicted results as close as possible to the true values. Once the model has learned, it has mastered the ability to infer the global reference point pattern from the local patterns of Pi.

[0045] Step 6: Perform harmonic source tracing based on the prediction results of the encoder-decoder (Seq2Seq) and attention mechanism model.

[0046] Specifically, the feature sequence Si(t) of each distributed photovoltaic grid-connected point Pi (i=1~n) is sequentially input into the trained model. The model outputs a predicted reference point sequence Sref-Pi(t) synchronized with Si(t). The point whose virtual sequence Sref-Pi(t) is most similar to the real reference point's real feature sequence Sref (the similarity distance between each virtual sequence and the real reference point's feature sequence is calculated using the DTW algorithm) indicates that the dynamic characteristics of that point have the greatest impact on the reference point, and thus it is the most important harmonic source.

[0047] Step 7: Verify the identified harmonic sources based on auxiliary criteria.

[0048] Specifically, the harmonic current emission level is usually highest at the harmonic source. The magnitude of the absolute value of the harmonic current measured at each point is used as an auxiliary factor in the judgment. If a point simultaneously meets both the conditions of "highest similarity to the harmonic mode of the reference point (smallest DTW distance)" and "largest local harmonic current amplitude," then it can be confidently identified as the dominant harmonic source.

[0049] This embodiment performs power quality testing on multiple distributed photovoltaic grid-connected points in the same area, fundamentally solving the technical problems of high cost, strict synchronization requirements and complex deployment of harmonic monitoring in the existing technology, and realizing accurate harmonic source tracing under asynchronous detection conditions.

[0050] Example 2 Embodiment 2 of the present invention introduces a harmonic source tracing system for power distribution networks.

[0051] like Figure 3 The distribution network harmonic source tracing system shown includes: The acquisition module is configured to acquire the distributed detection path of distributed photovoltaics in the distribution network to be detected; The acquisition module is configured to collect asynchronous data from several distributed photovoltaic systems based on the acquired distribution detection paths. A construction module is configured to extract key features from the collected asynchronous data and construct the time series of the distribution network. The screening module is configured to initially screen potential harmonic sources in the distribution network based on the constructed time series. The source tracing module is configured to perform harmonic source tracing of the distribution network based on the encoder-decoder and attention mechanism model and the potential harmonic sources of the distribution network.

[0052] The detailed steps are the same as those of the distribution network harmonic source tracing method provided in Example 1, and will not be repeated here.

[0053] Example 3 Embodiment 3 of the present invention provides a computer-readable storage medium.

[0054] A computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the power distribution network harmonic source tracing method as described in Embodiment 1 of the present invention.

[0055] The detailed steps are the same as those of the distribution network harmonic source tracing method provided in Example 1, and will not be repeated here.

[0056] Example 4 Embodiment 4 of the present invention provides an electronic device.

[0057] An electronic device includes a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, it implements the steps in the power distribution network harmonic source tracing method as described in Embodiment 1 of the present invention.

[0058] The detailed steps are the same as those of the distribution network harmonic source tracing method provided in Example 1, and will not be repeated here.

[0059] Example 5 Embodiment 5 of the present invention provides a computer program product.

[0060] A computer program product includes software code, wherein the program in the software code performs the steps in the power distribution network harmonic source tracing method as described in Embodiment 1 of the present invention.

[0061] The detailed steps are the same as those of the distribution network harmonic source tracing method provided in Example 1, and will not be repeated here.

[0062] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0063] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0064] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0065] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0066] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0067] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

[0068] The above description is merely a preferred embodiment of this practice and is not intended to limit the scope of this practice. Various modifications and variations can be made to this practice by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this practice should be included within the protection scope of this practice.

Claims

1. A power distribution network harmonic tracing method, characterized in that, The method comprises the following steps: acquiring a distributed detection path of a distributed photovoltaic in a power distribution network to be detected; collecting non-synchronous data of a plurality of distributed photovoltaics according to the acquired distributed detection path; extracting key features of the collected non-synchronous data to construct a time sequence of the power distribution network; preliminarily screening out potential harmonic sources of the power distribution network based on the constructed time sequence; performing harmonic tracing of the power distribution network according to an encoder-decoder and attention mechanism model and the potential harmonic sources of the power distribution network.

2. A power distribution network harmonic tracing method as claimed in claim 1, characterized in that, After acquiring the distributed detection path of the distributed photovoltaic in the power distribution network to be detected, a measurement point at a low-voltage outlet of a power distribution transformer or a point of common coupling of a regional power grid is selected as a reference point, and the common influence of all harmonic sources in the region is sensed based on the selected reference point.

3. A power distribution network harmonic tracing method as claimed in claim 1, wherein, In the process of collecting non-synchronous data of a plurality of distributed photovoltaics, a time measurement is sequentially performed at each grid-connected point according to the acquired distributed detection path, and the collected non-synchronous data at least includes high-density sampling data, power quality index data and absolute time stamp.

4. A power distribution network harmonic tracing method as claimed in claim 1, wherein, The process of preliminarily screening out the potential harmonic sources of the power distribution network is that a certain feature time sequence of the reference point is taken as a reference signal, the same feature sequence of each photovoltaic grid-connected point Pi is taken, the normalized cross-correlation of the reference signal and the feature sequence is calculated, the obtained correlation coefficient is taken as a preliminary screening index, the candidate point with the highest correlation with the harmonic activity of the reference point is screened out, and the preliminary screening of the potential harmonic sources of the power distribution network is completed.

5. A power distribution network harmonic tracing method as claimed in claim 1, wherein, In the process of harmonic tracing of the power distribution network, the feature sequence of each distributed photovoltaic grid-connected point is sequentially input into the encoder-decoder and attention mechanism model to obtain a virtual reference point sequence synchronized with the feature sequence, the similarity distance between each virtual reference point sequence and the real feature sequence of the reference point is calculated by using a dynamic time adjustment method DTW, and when the obtained similarity distance exceeds a distance threshold, the distributed photovoltaic grid-connected point is a harmonic source of the power distribution network, and the harmonic tracing of the power distribution network is completed.

6. A power distribution network harmonic tracing method as claimed in claim 1, wherein, The obtained harmonic sources of the power distribution network are verified according to an auxiliary criterion, and the auxiliary criterion is that the harmonic mode similarity with the reference point is the highest or the similarity distance is small and the local harmonic current amplitude is the largest.

7. A power distribution network harmonic tracing system, characterized by, The method comprises the following steps: an acquiring module configured to acquire a distributed detection path of a distributed photovoltaic in a power distribution network to be detected; a collecting module configured to collect non-synchronous data of a plurality of distributed photovoltaics according to the acquired distributed detection path; a constructing module configured to extract key features of the collected non-synchronous data to construct a time sequence of the power distribution network; a screening module configured to preliminarily screen out potential harmonic sources of the power distribution network based on the constructed time sequence; a tracing module configured to perform harmonic tracing of the power distribution network according to an encoder-decoder and attention mechanism model and the potential harmonic sources of the power distribution network.

8. A computer readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to realize the steps of the power distribution network harmonic tracing method in any one of claims 1-6.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, The processor executes the program to realize the steps of the power distribution network harmonic tracing method in any one of claims 1-6.

10. A computer program product comprising software code, characterized in that, The programs in the software code perform the steps of the power distribution network harmonic tracing method as claimed in any one of claims 1-6.

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