A method for determining the impact of harmonic source type on monitoring point attribution in a power grid

Abstract

This invention proposes a method for determining the impact of harmonic source types on monitoring points in power grids, belonging to the field of harmonic source tracing technology in power systems. The method involves acquiring various harmonic source currents and constructing harmonic source feature vectors; acquiring harmonic data for a specified time period T at monitoring point M, setting n sampling points, and constructing a normalized vector for each sampling point; multiplying the normalized vector of each sampling point with the feature vector of each harmonic source to determine the dominant harmonic source type for each sampling point; statistically analyzing the number of sources to determine the main harmonic sources at each monitoring point; if the number of sources is equal, it is determined that multiple sources are jointly affecting the source. This solution aims to solve the problems of difficult unified processing of harmonic sources and difficulty in extracting effective information from massive amounts of data, achieving accurate attribution determination.

Description

Technical Field

[0001] This invention belongs to the field of power system harmonic source tracing technology, specifically relating to a method for determining the impact of harmonic source type on monitoring point attribution in a power grid. Background Technology

[0002] In power systems, with the rapid growth in the scale and number of nonlinear devices connected to the grid, harmonic pollution has become increasingly serious, posing a significant threat to the safe, stable, and economical operation of the power grid.

[0003] Existing technologies face two major challenges in analyzing the harmonic source impact of a single monitoring point:

[0004] First, there are many types of harmonic sources with significant differences in characteristics. There are more than fourteen major categories of harmonic sources alone, and with the differences in technical approaches among different manufacturers, a large number of subcategories have been derived. The spectral characteristics of various harmonic sources are different, which makes it difficult to determine which harmonic source dominates the monitoring point.

[0005] Secondly, harmonic monitoring data exhibits characteristics of multiple parameters and large volume, making it difficult to process efficiently using traditional analysis methods. Taking a three-phase power supply monitoring point as an example, the total harmonic monitoring data at a single moment includes hundreds of indicators, covering fundamental voltage, current, active power, reactive power, voltage and current amplitudes and phases of each harmonic and interharmonic, active and reactive power of each harmonic, and key parameters such as total harmonic voltage distortion rate (THDU) and total harmonic current distortion rate (THDI). Traditional analysis methods based on harmonic statistical reports are insufficient for efficiently processing massive amounts of multi-dimensional measurement data, and even more so for accurately extracting effective features for harmonic source identification, thus making it difficult to quickly determine which harmonic source dominates the monitoring point. Summary of the Invention

[0006] This invention proposes a method for determining the impact of power grid harmonic source types on monitoring points. It aims to solve the problem that existing technologies struggle to uniformly process harmonic sources due to their diverse types and significant differences in characteristics. At the same time, it abandons the traditional analysis method that relies on harmonic statistical reports and cannot effectively extract features from massive, multi-dimensional monitoring data. This method achieves unified feature processing for different types of harmonic sources and accurately determines whether each type of harmonic source is the dominant harmonic source of the monitoring point.

[0007] To achieve the above objectives, the present invention proposes the following technical content:

[0008] A method for determining the impact of harmonic source type on monitoring points in a power grid includes the following steps:

[0009] S1: Apply sinusoidal voltages to various harmonic sources in the power grid and collect the current signals of each harmonic source; perform a fast Fourier transform on the current of each type of harmonic source to obtain its harmonic current; then construct the harmonic source feature vector of the corresponding harmonic source based on the fundamental current of each type of harmonic source.

[0010] S2: For power grid monitoring points M Get its time period T The harmonic monitoring data sequence within the system; identifies and outputs the last window of data in a stable operating state; the harmonic monitoring data sequence includes harmonic current. I h Total Harmonic Current Distortion (THDI);

[0011] S3: For the window data output in step S2, record its start time and end time, and manually set the time between the start time and end time. n One sampling point; combined with the time period obtained in step S2. T Internal harmonic current I h The harmonic current corresponding to each sampling point is obtained by interpolation, and the normalized vector of each sampling point is constructed.

[0012] S4: Take the normalized vector of a certain sampling point and dot product it with the harmonic source feature vectors of each type of harmonic source in step S1, and obtain the result. i Each inner product value; i Compare the inner product values ​​and determine the type of harmonic source corresponding to the largest inner product value as the dominant harmonic source of that sampling point;

[0013] S5: Repeat step S4 to obtain the normalized vectors of the remaining sampling points in sequence. Calculate the inner product of each vector with the harmonic source feature vectors of each type of harmonic source in step S1, and determine the dominant harmonic source type for each sampling point. Count the occurrence frequency of each type of harmonic source in all sampling points, and determine the harmonic source type with the highest occurrence frequency as the monitoring point. M The dominant harmonic source type.

[0014] Further, step S2 includes the following steps:

[0015] S2.1: The j The window data for acquiring the harmonic monitoring data sequence is obtained next. j ≥1, and is an integer; two windows are taken each time, a base window and a sliding window; the first... j The length of the reference window taken next is:

[0016] In the formula, w 0 indicates the initial window length. w0 is a positive integer, and the initial window starts at time 0. t 0; a Indicates the set coefficient; the first j The start time of the reference window is set to t 0, consistent with the start time of the initial window; the first j The length of the sliding window selected this time is a constant value: oh 0;th j The starting time of the next sliding window selection is: j The last moment of the reference window;

[0017] S2.2: Calculate and obtain the first... j The mean total harmonic current distortion (THDI) within the reference window is taken next. m j and standard deviation s j ; calculate and obtain the first j The mean total harmonic distortion (THDI) within the sliding window is taken next. m js and standard deviation s js ;

[0018] S2.3: If Then the first j The sliding window selected this time is a window in an unstable operating state. The data for the last window in a stable operating state is: j The reference window data is taken next; if Then the first j The sliding window selected this time is the one in a stable operating state;

[0019] S2.4: If the first j If the sliding window selected in the next step is a window in an unstable operating state, then the output of the first step will be... j The reference window data taken next is the data of the last window that is in a stable operating state; if the first... j If the selected sliding window is in a stable operating state, then S2.1-S2.3 are executed repeatedly. Each iteration adds the number of times the reference window has been acquired, and the length of the reference window changes accordingly, resulting in a corresponding sliding window. The start time of this sliding window is the end time of the acquired reference window; this process continues until the... j+ The window selected for the Rth time in an unstable sliding window state is output as the th window. j+ The reference window data is taken R times, where R is a positive integer greater than 2.

[0020] Furthermore, in step S1, the 1st to 50th harmonic currents of various harmonic sources in the power grid are obtained; in step S3, the 1st to 50th harmonic currents corresponding to each sampling point are obtained.

[0021] Furthermore, in step S1, it is set that there are a total of i Harmonic source; for the first k Harmonic source, k ∈[1 ,i ], and is an integer, its harmonic source eigenvector is:

[0022]

[0023] In the formula, b hk Indicates the first k Harmonic source h +1 harmonic current content h ∈[1 , 49], and is an integer, its formula is: In the formula, I h+1,k Indicates the first k Harmonic source h +1st harmonic current; I 1,k Indicates the first k First harmonic current of a harmonic source.

[0024] Furthermore, in step S3, the first x The normalized vector of each sampling point is:

[0025]

[0026] In the formula, b hx Indicates the first x Each sampling point h Normalized value of +1st harmonic current; x ∈[1 ,n ], and is an integer. n Indicates the total number of sampling points; , I h+1,x Indicates the first x sampling points h +1st harmonic current; I 1,x Indicates the first x The fundamental current at each sampling point.

[0027] Furthermore, in step S4, the first x The normalized vector of the nth sampling point and the nth sampling point k The formula for the inner product of the eigenvectors of a harmonic source is:

[0028]

[0029] In the formula, b hk Indicates the first k Harmonic source h +1 harmonic current content; b hx Indicates the first x Each sampling point h +1 harmonic current normalized value.

[0030] Furthermore, in step S2.1, a Set to 0.5.

[0031] The beneficial effects that can be achieved by adopting the above technologies are:

[0032] 1. By using a sliding window adaptive filter, the window of harmonic source under stable operating conditions is extracted, eliminating interference caused by load fluctuations and equipment switching, so as to accurately determine the dominant harmonic source type;

[0033] 2. By normalizing and vectorizing harmonics and performing inner product operations, the similarity between measured values ​​and type spectra can be quantified, making it suitable for complex power grid environments with multiple harmonic sources superimposed. Attached Figure Description

[0034] Figure 1 This is the flowchart of this solution. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] like Figure 1 As shown, a method for determining the impact of harmonic source type on monitoring points in a power grid includes the following steps:

[0037] S1: Apply sinusoidal voltages to various harmonic sources in the power grid and collect the current signals of each harmonic source; perform Fast Fourier Transform (FFT) on the current of each type of harmonic source to obtain its 1st to 50th harmonic currents, with the 1st harmonic current being the fundamental current; then construct the harmonic source feature vectors of the corresponding harmonic sources based on the fundamental currents of each type of harmonic source. Specifically, this includes the following steps:

[0038] S1.1: Collect the current signals of various harmonic sources, perform Fast Fourier Transform (FFT) on them, and obtain the 1st to 50th harmonic currents of each type of harmonic source;

[0039] S1.2: Construct the harmonic source feature vectors for various harmonic sources;

[0040] Setting up a power grid with a total of i Harmonic source; for the first k Harmonic source ( k ∈[1 ,i The eigenvectors of the harmonic sources are: (where is an integer).

[0041]

[0042] In the formula, b hk Indicates the first k Harmonic source h +1 harmonic current content h ∈[1 , 49], and is an integer, its formula is: In the formula, I h+1,k Indicates the first k Harmonic source h +1st harmonic current; I 1,k Indicates the first k First harmonic current (fundamental current) of a harmonic source.

[0043] S2: For power grid monitoring points M Get its time period T The harmonic monitoring data sequence within; identify and output the last window data that is in a stable operating state.

[0044] Specifically, for monitoring points M collection T =24-hour harmonic monitoring data, which includes: harmonic current I h Total Harmonic Current Distortion (THDI).

[0045] After data collection, identify and output the data of the last window that is in a stable operating state:

[0046] S2.1: The j The window data for acquiring the harmonic monitoring data sequence is obtained next. j ≥1, and an integer; two windows are used each time: a base window and a sliding window. j The length of the reference window taken next is:

[0047] In the formula, w 0 indicates the initial window length. w 0 represents a positive integer, and the start time of the initial window is set to 0.t 0; a This indicates the set coefficient, set to 1 / 2; the first... j The start time of the reference window is set to t 0, consistent with the start time of the initial window; the first j The length of the sliding window selected this time is a constant value: oh 0;th j The starting time of the next sliding window selection is: j The last moment of the reference window;

[0048] S2.2: Calculate and obtain the first... j The mean total harmonic current distortion (THDI) within the reference window is taken next. m j and standard deviation s j ; calculate and obtain the first j The mean total harmonic distortion (THDI) within the sliding window is taken next. m js and standard deviation s js ;

[0049] S2.3: If Then the first j The sliding window selected this time is a window in an unstable operating state. The data for the last window in a stable operating state is: j The reference window data is taken next; if Then the first j The sliding window selected this time is the one in a stable operating state;

[0050] S2.4: If the first j If the sliding window selected in the next step is a window in an unstable operating state, then the output of the first step will be... j The reference window data taken next is the data of the last window that is in a stable operating state; if the first... j If the selected sliding window is in a stable operating state, then S2.1-S2.3 are executed repeatedly. Each iteration adds the number of times the reference window has been acquired, and the length of the reference window changes accordingly, resulting in a corresponding sliding window. The start time of this sliding window is the end time of the acquired reference window; this process continues until the... j+ The window selected for the Rth time in an unstable sliding window state is output as the th window. j+ The reference window data is taken R times, where R is a positive integer greater than 2.

[0051] S3: For the window data output in step S2, record its start and end times, and obtain the data between the start and end times according to the sampling frequency of the harmonic monitoring device. nEach sampling point (e.g., if the harmonic monitoring device samples once per minute, then a 100-minute time window will have 100 sampling points); combined with the time period obtained in step S2 T Internal harmonic current I h The 1st to 50th harmonic currents at each sampling point are obtained by interpolation, and a normalized vector for each sampling point is constructed.

[0052] Then the first x sampling points ( x ∈[1 ,n The normalized vector of (where ] is an integer) is:

[0053]

[0054] In the formula, b hx Indicates the first x Each sampling point h The normalized value of the +1st harmonic current is given by the following formula: , I h+1,x Indicates the first x sampling points h +1st harmonic current; I 1,x Indicates the first x The fundamental current at each sampling point.

[0055] S4: The first x The normalized vector of each sampling point is then multiplied by the dot product of the harmonic source feature vectors of each type of harmonic source in step S1, resulting in a total of [missing information]. i Each inner product value; i The inner product values ​​are compared, and the harmonic source type corresponding to the largest inner product value is determined as the nth inner product value. x The dominant harmonic source at each sampling point.

[0056] No. x The normalized vector of the nth sampling point and the nth sampling point k The formula for the inner product of the eigenvectors of a harmonic source is:

[0057]

[0058] If the first x The normalized vector of the nth sampling point and the nth sampling point in step S1 k If the inner product value of the eigenvectors of a harmonic source is maximized, then the first... k The harmonic source was determined to be the first x The dominant harmonic source at each sampling point;

[0059] If the inner product of the normalized vector and the eigenvectors of the two or more harmonic sources in step S1 is the largest, then all two or more harmonic sources are considered as the first... x The dominant harmonic source at each sampling point.

[0060] S5: Repeat step S4 to obtain the normalized vectors of the remaining sampling points in sequence. Calculate the inner product of each vector with the harmonic source feature vectors of each type of harmonic source in step S1, and determine the dominant harmonic source type for each sampling point. Count the occurrence frequency of each type of harmonic source in all sampling points, and determine the harmonic source type with the highest occurrence frequency as the monitoring point. M The dominant harmonic source type.

[0061] For example: if the dominant harmonic source at the first sampling point is Class A, then the second to... n If the dominant harmonic source at each sampling point is Class B, then statistical analysis shows that the monitoring points... M The dominant harmonic source is a Class B harmonic source.

[0062] If there are two or more types of harmonic sources with the same number of sampling points, then the monitoring point M is determined to be affected by the multiple types of harmonic sources simultaneously.

[0063] For example: Suppose there are 25 sampling points in total. The dominant harmonic sources of sampling points 1-10 are of type A, those of sampling points 11-20 are of type B, and those of sampling points 21-25 are of type C. Statistical analysis shows that the dominant harmonic sources at monitoring point M are both type A and type B harmonic sources.

[0064] Calculation example:

[0065] To verify the accuracy of this scheme in identifying dominant harmonic sources, a monitoring point affected by harmonics was selected to conduct harmonic source tracing. This monitoring point is located at a company in XX City, and is situated on the low-voltage outgoing line of the main transformer.

[0066] After obtaining harmonic measurement data, this solution was applied to trace the harmonic sources, accurately identifying the dominant harmonic source as a six-pulse rectifier. On-site investigation confirmed that the company did indeed have a six-pulse rectifier-equipped medium-frequency induction furnace.

[0067] The results show that the proposed scheme has high accuracy and reliability in identifying dominant harmonic sources in practical engineering.

[0068] Some of the judgment data for this scheme are shown in Tables 1-3:

[0069] Table 1. Characteristic vectors of some harmonic sources

[0070]

[0071] Table 2 Partial Normalized Vectors

[0072]

[0073] Table 3 Inner Product Results and Type Determination

[0074]

[0075] Table 3 shows the dot product results of the normalized vector and the harmonic source eigenvector at the five selected time points. According to the method described above, the dot product of the normalized vector and the six-pulse rectification is the largest at the above five time points, and it is determined that the dominant harmonic source at the above time points is the six-pulse rectification.

[0076] Based on the above-described preferred embodiments of the present invention, and through the foregoing description, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A method for determining the attribution of the influence of a harmonic source type on a monitoring point in an electrical network, characterized in that, Includes the following steps: S1: Apply sinusoidal voltages to various harmonic sources in the power grid and collect the current signals of various harmonic sources; Perform a Fast Fourier Transform on the current of each type of harmonic source to obtain its harmonic current; then construct the harmonic source feature vector of the corresponding harmonic source based on the fundamental current of each type of harmonic source. Setting up a power grid with a total of i Harmonic source; For the k Harmonic source, k ∈[1 ,i ], and is an integer, its harmonic source eigenvector is: ； In the formula, b hk Indicates the first k Harmonic source h +1 harmonic current content h ∈[1 , 49], and is an integer, its formula is: In the formula, I h+1,k Indicates the first k Harmonic source h +1st harmonic current; I 1,k Indicates the first k First harmonic current of a harmonic source; S2: For power grid monitoring points M Get its time period T The harmonic monitoring data sequence within the system; identifies and outputs the last window of data in a stable operating state; the harmonic monitoring data sequence includes harmonic current. I h Total Harmonic Current Distortion (THDI); S3: For the window data output in step S2, record its start and end times, and obtain the data between the start and end times according to the sampling frequency of the harmonic monitoring device. n One sampling point; combined with the time period obtained in step S2. T Internal harmonic current I h The harmonic current corresponding to each sampling point is obtained by interpolation, and the normalized vector of each sampling point is constructed. In step S3, the first x The normalized vector of each sampling point is: ； In the formula, b hx Indicates the first x Each sampling point h Normalized value of +1st harmonic current; x ∈[1 ,n ], and is an integer. n Indicates the total number of sampling points; , I h+1,x Indicates the first x sampling points h +1st harmonic current; I 1,x Indicates the first x Fundamental current at each sampling point; S4: Take the normalized vector of a certain sampling point and dot product it with the harmonic source feature vectors of each type of harmonic source in step S1, and obtain the result. i Each inner product value; i Compare the inner product values ​​and determine the type of harmonic source corresponding to the largest inner product value as the dominant harmonic source of that sampling point; S5: Repeat step S4 to obtain the normalized vector of each of the remaining sampling points in turn, and calculate the inner product of the vector with the harmonic source feature vector of each type of harmonic source in step S1, and determine the dominant harmonic source type of each sampling point one by one. The frequency of each type of harmonic source at all sampling points is counted, and the type of harmonic source with the highest frequency is identified as the monitoring point. M The dominant harmonic source type.

2. The method for determining the influence of harmonic source type on monitoring point attribution in a power grid according to claim 1, characterized in that, Step S2 includes the following steps: S2.1: The j The window data for acquiring the harmonic monitoring data sequence is obtained next. j ≥1, and is an integer; two windows are taken each time, a base window and a sliding window; the first... j The length of the reference window taken next is: In the formula, w 0 represents the initial window length. w 0 is a positive integer, and the initial window starts at time 0. t 0; a Indicates the set coefficient; the first j The start time of the reference window is set to t 0, consistent with the start time of the initial window; the first j The length of the sliding window selected this time is a constant value: aw 0;th j The starting time of the next sliding window selection is: j The last moment of the reference window; S2.2: Calculate and obtain the first... j The mean total harmonic current distortion (THDI) within the reference window is taken next. μ j and standard deviation σ j ; calculate and obtain the first j The mean total harmonic distortion (THDI) within the sliding window is taken next. μ js and standard deviation σ js ; S2.3: If Then the first j The sliding window selected this time is a window in an unstable operating state. The data for the last window in a stable operating state is: j The reference window data is taken next; if Then the first j The sliding window selected this time is the one in a stable operating state; S2.4: If the first j If the sliding window selected in the next step is a window in an unstable operating state, then the output of the first step will be... j The reference window data taken next is the data of the last window that is in a stable operating state; if the first... j If the selected sliding window is in a stable operating state, then S2.1-S2.3 are executed repeatedly. Each iteration adds the number of times the reference window has been acquired, and the length of the reference window changes accordingly, resulting in a corresponding sliding window. The start time of this sliding window is the end time of the acquired reference window; this process continues until the... j+ The window selected for the Rth time in an unstable sliding window state is output as the th window. j+ The reference window data is taken R times, where R is a positive integer greater than 2.

3. The method for determining the influence of harmonic source type on monitoring point attribution in a power grid according to claim 1, characterized in that, In step S1, the 1st to 50th harmonic currents of various harmonic sources in the power grid are obtained; in step S3, the 1st to 50th harmonic currents corresponding to each sampling point are obtained.

4. The method for determining the influence of harmonic source type on monitoring point attribution in a power grid according to claim 1, characterized in that, In step S4, the first x The normalized vector of the nth sampling point and the nth sampling point k The formula for the inner product of the eigenvectors of a harmonic source is: ； In the formula, b hk Indicates the first k Harmonic source h +1 harmonic current content; b hx Indicates the first x Each sampling point h +1 harmonic current normalized value.

5. The method for determining the influence of harmonic source type on monitoring point attribution in a power grid according to claim 2, characterized in that, In step S2.1, a Set to 0.5.

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