A dynamic phasor measurement method for distribution network with large-scale distributed generation access

Abstract

The application discloses a kind of distribution network dynamic phasor measurement methods suitable for large-scale distributed power access, comprising: S1, according to the design of measurement demand low-pass filter I, the real part and imaginary part of initial synchronous phasor are obtained by using sine filter set to the fundamental signal of distribution network measurement;S2, construct the measurement error model of initial synchronous phasor under the static and dynamic conditions of distribution network, while using low-pass filter II to low-pass filter processing to initial synchronous phasor, eliminate negative frequency interference component;S3, construct the second-order differentiator of synchronous phasor, and according to the amplitude-frequency characteristic of second-order differentiator, the linear relationship between the second derivative of synchronous phasor and its measurement error is constructed, compensates the error of synchronous phasor, obtains the final synchronous phasor value of distribution network.The application can accurately measure the synchronous phasor of voltage and current signal when the frequency of distribution network signal occurs frequency deviation, dynamic change, harmonic distortion, improve the observable and measurable level of distribution network, provide data support for various applications.

Description

Technical Field

[0001] This invention belongs to the field of power system synchronous phasor measurement technology, and specifically relates to a dynamic phasor measurement method for distribution networks with large-scale distributed power source access. Background Technology

[0002] With the construction and development of new power systems, more and more distributed power sources are being integrated into distribution networks, and electric vehicles are becoming increasingly widespread. This leads to more frequent interactions between distribution networks and users, posing greater challenges to the measurement of power system phasors. Currently, the measurement of power system phasors mainly faces the following problems:

[0003] (1) With the access of large-scale distributed power sources and frequent interactions, the electrical quantities of the distribution network exhibit high noise and strong transient characteristics, and the three-phase asymmetry problem is serious, resulting in a decrease in the measurability of the distribution network.

[0004] (2) Problems such as the intertwining of power sources and loads, complex characteristics, insufficient measurement, inaccurate parameters, and difficulty in fault location in the distribution network have become prominent, leading to a decline in the observability of the distribution network.

[0005] (3) The randomness and volatility of new energy sources make it more difficult to ensure the safe and reliable operation of the distribution network through multi-dimensional control, resulting in a decrease in the controllability of the distribution network.

[0006] A crucial approach to solving these problems is to develop dynamic phasor measurement methods for distribution networks suitable for large-scale distributed power generation integration. Traditional distribution automation equipment, such as FTUs and DTUs, do not involve phase angles when measuring electrical quantities and have upload speeds on the order of minutes, making it difficult to monitor dynamic changes in the distribution network and limiting their applicability. While the synchronization and speed of phasor measurement devices can compensate for the shortcomings of existing distribution network monitoring equipment and improve the observability, measurability, and controllability of the distribution network, existing dynamic phasor measurement methods are mostly applicable to transmission networks. Compared to transmission networks, distribution network signals after large-scale distributed renewable energy integration are more complex, exhibiting severe harmonic distortion, frequent voltage fluctuations, and larger frequency offsets. Traditional methods are often unsuitable for these conditions, thus necessitating the development of new synchronous phasor measurement methods to ensure measurement accuracy. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of the above-mentioned technologies and provide a dynamic phasor measurement method for distribution networks with large-scale distributed power source access. This method can accurately measure the synchronous phasors of voltage and current signals when the distribution network signals experience frequency shifts, dynamic changes, and harmonic distortions, thereby improving the observability and measurability of the distribution network and providing data support for various applications.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] A dynamic phasor measurement method for distribution networks suitable for large-scale distributed power generation integration, comprising the following steps:

[0010] S1. Design a low-pass filter I according to the measurement requirements, and construct a sine and cosine filter group by frequency shifting the low-pass filter I. Use the sine and cosine filter group to measure the fundamental signal of the distribution network to obtain the real and imaginary parts of the initial synchronization phasor.

[0011] S2. Based on the amplitude-frequency characteristics of the sine and cosine filter banks, construct measurement error models of the initial synchronization phasor under static and dynamic conditions of the distribution network. At the same time, use low-pass filter II to perform low-pass filtering on the initial synchronization phasor measured in step S1 to eliminate negative frequency interference components.

[0012] S3. Construct a second-order differentiator for the synchronization phasor, and establish a linear relationship between the second derivative of the synchronization phasor and its measurement error based on the amplitude-frequency characteristics of the second-order differentiator. Based on the synchronization phasor after low-pass filtering in step S2, compensate for the synchronization phasor error to obtain the final synchronization phasor value of the distribution network.

[0013] Preferably, the specific steps of S1 are as follows:

[0014] S1-1: Determine the measurement window length and the passband and stopband of low-pass filter I according to the measurement requirements, and then design low-pass filter I;

[0015] S1-2: Based on the Fourier transform, the low-pass filter I designed in step S1-1 is frequency-shifted to obtain a sine and cosine filter bank, as shown in equation (1):

[0016]

[0017] In equation (1), h low (k) represents the k-th coefficient of low-pass filter I; h c (k) represents the k-th coefficient of the cosine filter; h s (k) represents the k-th coefficient of the sinusoidal filter; T(k) represents the k-th element in the time series, and f s The sampling rate of the distribution network signal is represented by N, where N is a positive integer, 2N is the order of the sine and cosine filter banks, k is an integer representing the sequence index, and f is the sampling rate of the distribution network signal. n The rated frequency is 50Hz;

[0018] S1-3: The fundamental signal of the distribution network is measured using a sine and cosine filter bank to obtain the real and imaginary parts of the initial synchronization phasor, as shown in equations (2) and (3) respectively:

[0019]

[0020]

[0021] In the formula, For t k The real part of the phasor value at time. For t k The imaginary part of the phasor value at time. Indicates t k The phasor value at time t k The moment of synchronous phasor measurement. Indicates distribution network signal The sampled value at time h c (i+N) represents the (i+N)th coefficient of the cosine filter, h s (i+N) represents the (i+N)th coefficient of the sine filter, where i = [-N, -(N-1), ..., 0, ..., N-1, N].

[0022] Preferably, in S2,

[0023] The measurement error model of the synchronous phasor under static conditions of the distribution network is shown in equation (7):

[0024]

[0025] Wherein, E(t) k ) represents t k Phasor measurement error at time x + (t k ) represents the fundamental frequency signal of the distribution network at time t k The positive frequency component value at time x - (t k ) represents the fundamental frequency signal of the distribution network at time t k The negative frequency component value at time t, |H(f0)| represents the gain of the sine and cosine filter bank at f0, |H(-f0)| represents the gain of the sine and cosine filter bank at -f0, and f0 represents the frequency of the fundamental signal of the distribution network;

[0026] The measurement error model of the synchronous phasor under the dynamic conditions of the distribution network is shown in Equation (10):

[0027]

[0028] Where M represents the number of frequency components in the dynamic signal of the distribution network, f i This represents the frequency value of the i-th frequency component. Represents the frequency component f i In t k The positive frequency component value at time t. Represents the frequency component f i In t k The negative frequency component value at time , |H(fi | indicates that the sine and cosine filter banks are at f i Gain at |H(-f) i )| indicates that the sine and cosine filter banks are at -f i Gain at that point.

[0029] Preferably, in S2, the synchronization phasor obtained after eliminating the negative frequency interference component using low-pass filter II is shown in equation (11):

[0030]

[0031] Among them, h l (i) represents the coefficients of the i-th order of low-pass filter II, and S is the order of low-pass filter II. This indicates that after low-pass filtering, at t k The synchronization phasor value at time.

[0032] Preferably, in S3, the second-order differentiator of the synchronizing phasor is as shown in equation (15):

[0033]

[0034] in,

[0035] Among them, t0 to t K Let K+1 be equally spaced time intervals, where K is a positive integer, A be a matrix composed of discrete time intervals, B be a matrix composed of differentiator coefficients, b0 be the zeroth-order differentiator coefficients, b1 be the first-order differentiator coefficients, and b2 be the second-order differentiator coefficients.

[0036] Preferably, in S3, t k Second derivative of the synchronization phasor at time t Its measurement error E(t) k The linear relationship between them is shown in equation (22):

[0037]

[0038] in,

[0039] In the above formula, Indicates t k The second derivative of the synchronization phasor at time t, C p0 The proportionality coefficient between the second derivative of the phasor and its measurement error, |H l (f)| represents the amplitude-frequency response of low-pass filter I, |H2(f)| represents the amplitude-frequency response of the second-order differentiator, |H l (Δf i | indicates that the low-pass filter I is in Δf i The gain at that point, |H2(Δf)i | indicates that the second-order differentiator is in Δf i Gain at Δf i =f i -f n , representing the i-th frequency component f i With frequency rating f n The difference between them;

[0040] Therefore, the final synchronous phasor values ​​of the distribution network are shown in equation (23):

[0041]

[0042] in, Indicates t k The phasor value of the distribution network synchronization at a given time. E(t) represents the synchronization phasor value after low-pass filtering in step S2. k ) represents t k Phasor measurement error at time t.

[0043] Beneficial effects: This invention discloses a dynamic phasor measurement method for distribution networks with large-scale distributed power supply access. It adopts dynamic compensation technology based on the frequency domain characteristics of the least squares method to eliminate the measurement error of dynamic phasors. It can achieve accurate measurement of synchronous phasors of voltage and current signals when the distribution network signals experience frequency shifts, dynamic changes, and harmonic distortion. Attached Figure Description

[0044] Figure 1 This is a schematic diagram of the measurement method flow in Example 1;

[0045] Figure 2 This is a schematic diagram of the filtering characteristics of the low-pass filter in Example 1;

[0046] Figure 3 This is a schematic diagram illustrating the relationship between the phasor measurement error and the ratio of its second derivative as a function of frequency in Example 1. Detailed Implementation

[0047] The present invention will now be described with reference to the accompanying drawings, and these improvements and modifications should also be considered within the scope of protection of the present invention.

[0048] Example 1

[0049] Example 1 provides a dynamic phasor measurement method for distribution networks with large-scale distributed power source integration, such as... Figure 1 As shown, the specific methods include:

[0050] S1. Design a low-pass filter I according to the measurement requirements, and construct a sine and cosine filter bank by frequency shifting the low-pass filter I. Use the sine and cosine filter bank to measure the fundamental signal of the distribution network to obtain the real and imaginary parts of the initial synchronization phasor. The specific steps are as follows:

[0051] S1-1: Determine the measurement window length and the passband and stopband of low-pass filter I based on the measurement requirements, and then design low-pass filter I. To eliminate the negative frequency components of the fundamental signal, the gain of low-pass filter I near 50Hz should be lower than that of other stopbands. For example... Figure 2 The diagram shows a design schematic of low-pass filter I. The passband is used to extract the synchronization phasor, and the stopband is used to filter out interference components, including harmonics, interharmonics, and fundamental negative frequency components.

[0052] S1-2: Shift the frequency of the low-pass filter I obtained in step S1-1 to obtain a sine and cosine filter bank; In this embodiment 1, the sine and cosine filter bank is constructed based on the frequency shifting characteristics of Fourier transform, as shown in equation (1):

[0053]

[0054] In equation (1), h low (k) represents the k-th coefficient of low-pass filter I; h c (k) represents the k-th coefficient of the cosine filter; h s (k) represents the coefficients of the sinusoidal filter; T(k) represents the k-th element in the time series, and f s The sampling rate of the distribution network signal is represented by N, where N is a positive integer, 2N is the order of the sine and cosine filter banks, k is an integer representing the sequence index, and f is the sampling rate of the distribution network signal. n The rated frequency is 50Hz;

[0055] S1-3: Since the synchronization phasor is composed of a real part and an imaginary part, the real part and imaginary part of the initial synchronization phasor can be obtained by measuring the distribution network signal using a sine and cosine filter bank, as shown in equations (2) and (3) respectively:

[0056]

[0057]

[0058] In the formula, For t k The real part of the phasor value at time. For t k The imaginary part of the phasor value at time. Indicates t k The phasor value at time t k The moment of synchronous phasor measurement. Indicates distribution network signal The sampled value at time h c (i+N) represents the (i+N)th coefficient of the cosine filter, h s (i+N) represents the (i+N)th coefficient of the sine filter, where i = [-N, -(N-1), ..., 0, ..., N-1, N].

[0059] S2: Based on the amplitude-frequency characteristics of the sine and cosine filter banks, construct measurement error models of the initial synchronization phasor under static and dynamic conditions of the distribution network. At the same time, use low-pass filter II to perform low-pass filtering on the initial synchronization phasor measured in step S1 to eliminate negative frequency interference components.

[0060] Since a sine and cosine filter bank is used to extract the initial synchronization phasor in this embodiment 1, its filtering characteristics directly affect the measurement error of the initial synchronization phasor. Therefore, it is necessary to analyze its measurement error model based on the frequency domain characteristics of the sine and cosine filter bank to provide a theoretical basis for subsequent accuracy optimization. The specific steps are as follows:

[0061] S2-1: Distribution network signals exist in static and dynamic states. In the static state, the parameters of the fundamental signal of the distribution network change slowly and can be regarded as constant within a short time window. Therefore, the fundamental signal model of the distribution network under static conditions is represented as shown in equation (4):

[0062]

[0063] Among them, X m f0 represents the amplitude of the fundamental signal, and f0 represents the frequency of the fundamental signal in the distribution network. The initial phase angle of the fundamental signal;

[0064] S2-2: According to Euler's formula, the expansion of equation (4) is shown in equation (5):

[0065]

[0066] Where, x + (t) represents the positive frequency component of the fundamental signal at time t, x - (t) represents the negative frequency component of the fundamental signal at time t, where j is the imaginary unit; the positive frequency component is the synchronization phasor to be solved, and the negative frequency component is the interference signal with a content of 100%. Therefore, the sine and cosine filter bank should filter out the negative frequency component and retain the positive frequency component.

[0067] S2-3: In t k The fundamental signal of the distribution network is measured using a sine and cosine filter bank at all times, and the initial synchronization phasor is measured. As shown in equation (6):

[0068]

[0069] In the formula, x + (t k ) represents the fundamental frequency signal of the distribution network at time t k The positive frequency component value at time x - (t k ) represents the fundamental frequency signal of the distribution network at time t k The negative frequency component value at time t, |H(f0)| represents the gain of the sine and cosine filter bank at f0, |H(-f0)| represents the gain of the sine and cosine filter bank at -f0, and f0 represents the frequency of the fundamental signal of the distribution network;

[0070] S2-4: Under static conditions of the distribution network, the synchronous phasor at time t k The measurement error model for time is as follows:

[0071]

[0072] Wherein, E(t) k ) represents t k Phasor measurement error at time x + (t k ) represents the fundamental frequency signal of the distribution network at time t k The positive frequency component value at time x - (t k ) represents the fundamental frequency signal of the distribution network at time t k The negative frequency component value at time;

[0073] S2-5: When a disturbance or fault occurs, the fundamental signal of the distribution network will change dynamically. At this time, the fundamental signal model is represented as shown in equation (8):

[0074]

[0075] Where x(t) represents the sampled value of the distribution network signal at time t, and X(t) represents the dynamically changing amplitude at time t. This represents the phase angle that changes dynamically at time t;

[0076] S2-6: The dynamically changing fundamental signal is a superposition of multiple frequency components within the measurement frequency band, as shown in formula (9):

[0077]

[0078] Where M represents the number of frequency components in the dynamic signal of the distribution network. This represents the positive frequency component value of the i-th frequency component of the fundamental signal at time t. This represents the negative frequency component value of the i-th frequency component of the fundamental signal at time t;

[0079] S2-7: Under dynamic conditions of the distribution network, the synchronous phasor at time tk The measurement error model for time is shown in equation (10):

[0080]

[0081] Where M represents the number of frequency components in the dynamic signal of the distribution network, f i This represents the frequency value of the i-th frequency component. Represents the frequency component f i In t k The positive frequency component value at time t. Represents the frequency component f i In t k The negative frequency component value at time , |H(f i | indicates that the sine and cosine filter banks are at f i Gain at |H(-f) i )| indicates that the sine and cosine filter banks are at -f i Gain at that point.

[0082] S2-8: Since the window length of the sine and cosine filter banks is relatively short, it cannot effectively suppress the negative frequency component. The obtained initial synchronization phasor still contains the negative frequency interference component. Therefore, it is necessary to use a low-pass filter II to filter out the interference, as shown in equation (11):

[0083]

[0084] Among them, h l (i) represents the coefficients of the i-th order of low-pass filter II, and S is the order of low-pass filter II. This indicates that after low-pass filtering, at t k The synchronization phasor value at time.

[0085] S3. Construct a second-order differentiator for the synchronization phasor, and establish a linear relationship between the second derivative of the phasor and its measurement error based on the frequency domain characteristics of the second-order differentiator. When the distribution network signal experiences frequency shifts and dynamic changes, the synchronization phasor extracted by the sine and cosine filter banks will have measurement errors. Therefore, error compensation is required to improve measurement accuracy. The specific steps are as follows:

[0086] S3-1: Perform a quadratic polynomial fitting on the synchronization phasor after low-pass filtering in step S2, as shown in formula (12):

[0087]

[0088] in, This represents the synchronization phasor value at time t after low-pass filtering, where a0, a1, and a2 are polynomial fitting coefficients.

[0089] S3-2: Construct the system of equations to solve for the fitting coefficients of equation (12), as shown in equation (13):

[0090]

[0091] Among them, t0 to t K There are K+1 equally spaced time intervals, where K is a positive integer;

[0092] S3-3: The fitting coefficients are obtained using the least squares method as shown in formula (14):

[0093]

[0094] make

[0095] in, t0 to t K Let K+1 be equally spaced time intervals, where K is a positive integer, A be a matrix composed of discrete time intervals, B be a matrix composed of differentiator coefficients, b0 be the zeroth-order differentiator coefficients, b1 be the first-order differentiator coefficients, and b2 be the second-order differentiator coefficients.

[0096] S3-4: Solve for the second derivative of the synchronous phasor using a second-order differentiator, as shown in equation (16):

[0097]

[0098] The frequency domain expression of formula (16) is shown in formula (17):

[0099]

[0100] Among them, |H l (Δf i | indicates that the low-pass filter I is in Δf i The gain at that point, |H2(Δf) i | indicates that the second-order differentiator is in Δf i Gain at Δf i =f i -f n , representing the i-th frequency component f i With frequency rating f n The difference between them;

[0101] S3-5: After the negative frequency component is filtered out, t k The measurement error at time is expressed as:

[0102]

[0103] By combining equations (17) and (18), we can obtain:

[0104]

[0105] S3-6: Order

[0106] Equation (20) represents |H2(f)| and |H l The proportional relationship between (f) and |H2(f)|, where |H2(f)| represents the amplitude-frequency characteristic of the second-order differentiator, and |H l (f)| represents the low-pass filter I at Δf i Gain at the location;

[0107] Figure 3 The image shows C. p The behavior of C with frequency shows that as frequency changes, p The value of C changes very little, so C can be... p Treating it as a constant independent of frequency, let f = Δf i ,Right now:

[0108]

[0109] Among them, C p0 This represents the proportionality coefficient between the second derivative of the phasor and its measurement error; its value is a constant.

[0110] Therefore, the linear relationship between the phasor's second derivative and its measurement error can be expressed as:

[0111]

[0112] S3-7: The phasor values ​​of the final distribution network are as shown in formula (23):

[0113]

[0114] in, Indicates t k The phasor value of the distribution network synchronization at a given time. This refers to the synchronization phasor after low-pass filtering in step S2.

[0115] Simulation test

[0116] To demonstrate the effectiveness of the phasor measurement method described in Example 1, the following simulation tests were conducted, specifically divided into static and dynamic tests.

[0117] Static testing is as follows:

[0118] (1) Frequency offset test: The fundamental frequency offset is between 48Hz and 52Hz;

[0119] (2) Harmonic test: The 2nd to 13th harmonics are superimposed on the fundamental signal, and the harmonic content is 10%;

[0120] Dynamic testing is as follows:

[0121] (1) Modulation test: The amplitude and phase angle are sinusoidally modulated, the modulation frequency is 0.1 to 5 Hz, the amplitude modulation depth is 10% of the rated amplitude, and the phase angle modulation depth is 0.1 rad;

[0122] (2) Frequency ramp test: The frequency changes linearly from 48Hz to 52Hz.

[0123] During the test, the signal sampling rate was 10000Hz, the measurement window length of low-pass filter I was 2 cycles, the calculation frequency was 400Hz, the measurement window length of low-pass filter II was 5 cycles, and the order of the second-order differentiator in step S3 was 5. The test results are shown in Table 1.

[0124] Table 1 Maximum measurement error in Example 1

[0125]

[0126] As can be seen from Table 1, the maximum measurement error of the dynamic phasor measurement method for distribution networks proposed in Example 1 meets the standard requirements and is at least 80 times less than the standard requirements. This indicates that the method proposed in Example 1 can accurately measure synchronous phasors under the conditions of harmonic distortion, frequency shift, and dynamic changes in distribution network signals, providing effective dynamic monitoring for complex distribution networks after large-scale distributed power source access, and providing data support for various applications.

[0127] The above description is merely an illustration of the present invention and represents a preferred embodiment. It should be noted that those skilled in the art can make various improvements and modifications without departing from the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A dynamic phasor measurement method for distribution networks suitable for large-scale distributed power source integration, characterized in that, The specific steps include: S1. Design a low-pass filter I according to the measurement requirements, and construct a sine and cosine filter group by frequency shifting the low-pass filter I. Use the sine and cosine filter group to measure the fundamental signal of the distribution network to obtain the real and imaginary parts of the initial synchronization phasor. S2. Based on the amplitude-frequency characteristics of the sine and cosine filter banks, construct measurement error models of the initial synchronization phasor under static and dynamic conditions of the distribution network. At the same time, use low-pass filter II to perform low-pass filtering on the initial synchronization phasor measured in step S1 to eliminate negative frequency interference components. S3. Construct a second-order differentiator for the synchronization phasor, and construct a linear relationship between the second derivative of the synchronization phasor and its measurement error based on the amplitude-frequency characteristics of the second-order differentiator. Based on the synchronization phasor after low-pass filtering in step S2, compensate for the synchronization phasor error and obtain the final synchronization phasor value of the distribution network. In S3, Second derivative of the synchronization phasor at time t Its measurement error The linear relationship between them is shown in equation (22): （22）； in, (twenty one); In the above formula, express t k The second derivative value of the synchronization phasor at time t. C p0 The proportionality coefficient between the second derivative of the phasor and its measurement error, | H l ( f | represents the amplitude-frequency response of low-pass filter I, | H 2( f | represents the amplitude-frequency response of a second-order differentiator. H l (Δ f i )| indicates that the low-pass filter I is in Δ f i Gain at | H 2(Δ f i )| indicates that the second-order differentiator is in Δ f i Gain at Δ f i = f i - f n , indicating the first i Frequency components f i With frequency rating f n The difference between them; Therefore, the final synchronous phasor values ​​of the distribution network are shown in equation (23): （23）； in, express t k The phasor value of the distribution network synchronization at a given time. The value of the synchronization phasor after low-pass filtering in step S2. express t k Phasor measurement error at time t.

2. The dynamic phasor measurement method for distribution networks applicable to large-scale distributed power source access according to claim 1, characterized in that, The specific steps of S1 are as follows: S1-1: Determine the measurement window length and the passband and stopband of low-pass filter I according to the measurement requirements, and then design low-pass filter I; S1-2: Based on the Fourier transform, the low-pass filter I designed in step S1-1 is frequency-shifted to obtain a sine and cosine filter bank, as shown in equation (1): （1）； In equation (1), h low ( k ) represents the first pass of low-pass filter I. k One coefficient; h c ( k ) represents the first cosine filter. k One coefficient; h s ( k ) represents the first digit of the sinusoidal filter. k One coefficient; Represents the first in a time series k 1 element, and , f s Indicates the sampling rate of the distribution network signal. N It is a positive integer, 2 N is the order of the sine and cosine filter bank; k The integer represents the sequence index; f n The rated frequency is 50Hz; S1-3: The fundamental signal of the distribution network is measured using a sine and cosine filter bank to obtain the real and imaginary parts of the initial synchronization phasor, as shown in equations (2) and (3) respectively: （2）； （3）； In the formula, for t k The real part of the phasor value at time. for t k The imaginary part of the phasor value at time. express t k The phasor value at time t. t k The moment of synchronous phasor measurement. Indicates distribution network signal The sampled value at time 10:

00. The first cosine filter represents the... One coefficient, The first sine filter represents the... One coefficient, .

3. The dynamic phasor measurement method for distribution networks applicable to large-scale distributed power source access according to claim 2, characterized in that, In S2, The measurement error model of the synchronous phasor under static conditions of the distribution network is shown in equation (7): （7）； in, E ( t k )express t k Phasor measurement error at time t, x + ( t k ) indicates the fundamental frequency signal of the distribution network. t k The positive frequency component value at time t. x - ( t k ) indicates the fundamental frequency signal of the distribution network. t k The negative frequency component value at time , | H ( f 0)| indicates that the sine and cosine filter banks are in f Gain at 0, | H (- f 0)| indicates that the sine and cosine filter banks are in - f Gain at 0, f 0 represents the frequency of the fundamental signal in the distribution network; The measurement error model of the synchronous phasor under the dynamic conditions of the distribution network is shown in equation (10): （10）； in, M This indicates the number of frequency components in the dynamic signal of the distribution network. f i Indicates the first i The frequency value of each frequency component Represents frequency components f i exist t k The positive frequency component value at time t. Represents frequency components f i exist t k The negative frequency component value at time t. Indicates the sine and cosine filter banks in Gain at that point, Indicates that the sine and cosine filter banks are in - Gain at that point.

4. The dynamic phasor measurement method for distribution networks applicable to large-scale distributed power source access according to claim 3, characterized in that, In S2, the synchronization phasor obtained after eliminating the negative frequency interference component using low-pass filter II is shown in equation (11): （11）； in, h l ( i ) indicates the second low-pass filter. i The coefficient of order, S The order of low-pass filter II. Indicates after low-pass filtering t k The synchronization phasor value at time.

5. The dynamic phasor measurement method for distribution networks applicable to large-scale distributed power source access according to claim 4, characterized in that, In S3, the second-order differentiator of the synchronizing phasor is shown in equation (15): （15）； in, ; in, t 0 to t K for K +1 equally spaced time intervals K It is a positive integer. A A matrix composed of discrete time intervals. B It is a matrix consisting of the differentiator coefficients. b 0 represents the coefficient of the zeroth-order differentiator. b 1 represents the coefficient of the first-order differentiator. b 2 represents the coefficients of the second-order differentiator.

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