A three-phase electrical frequency estimation method, device and computer-readable storage medium

Abstract

The present invention belongs to the technical field of power system frequency estimation, and relates to a three-phase electric frequency estimation method, device and computer-readable storage medium; based on the three-phase voltage signals at time k and time k+1 of the three-phase power system, a target complex voltage signal at time k, a target complex voltage signal at time k+1 and its phase value are obtained; the target complex voltage signal at time k is input into an adaptive filter based on a wide linear model, and an estimated value of the complex voltage signal at time k+1 and its phase value are output; the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal is calculated; an augmented complex valued overall minimum average phase adaptive cost function is constructed, and the standard weight coefficient and conjugate weight coefficient at time k+1 are calculated, so as to calculate the frequency estimation value of the three-phase power system at time k+1. By minimizing the phase error between the actual complex voltage signal and the estimated complex voltage signal, the accuracy of the frequency estimation result is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system frequency estimation, and in particular to a three-phase power frequency estimation method, device and computer-readable storage medium. Background Art

[0002] The rapid integration of distributed generation resources is changing the pattern of the power grid, which is characterized by a shift from centralized power plants to a network of small grid-connected renewable energy devices. This shift has led to increasingly common island and microgrid phenomena in the generation-load chain, increasing the possibility of imbalanced power transmission. Frequency estimation is an important tool for monitoring and regulating the balance of the power system. Therefore, it is necessary to improve the accuracy of the prediction results of the three-phase power frequency of the power system, so as to accurately reflect the operating status of the power system, so as to take corrective measures in time when the power system is unbalanced, and ensure the reliability and stability of the power system operation.

[0003] The existing three-phase electrical frequency estimation method collects the three-phase voltage signals at each moment of the power system, uses an adaptive filter to predict the three-phase voltage signal at the next moment based on the three-phase voltage signal at the current moment, and constructs a cost function based on the difference between the actual value and the predicted value of the three-phase voltage signal at the next moment, thereby adjusting the coefficient of the adaptive filter. Since the coefficient adjustment process of the adaptive filter reflects the law of signal changes in the power system, the frequency component in the signal can be calculated by adjusting the coefficient of the adaptive filter, thereby predicting the three-phase electrical frequency of the power system. However, when updating the coefficient of the adaptive filter based on the difference between the actual value and the predicted value of the voltage signal, the amplitude information of the signal is concerned, and the amplitude of the signal is easily affected by noise, resulting in a large deviation between the predicted value and the actual value of the voltage signal output by the adaptive filter in a noisy environment. Therefore, the coefficient of the adaptive filter obtained based on the difference is not accurate, and the frequency change in the power system cannot be accurately captured, which reduces the accuracy of the three-phase electrical frequency estimation result.

[0004] In summary, the existing three-phase electrical frequency estimation method is easily affected by noise, resulting in inaccurate coefficients of the adaptive filter updated based on the cost function, which cannot accurately reflect the true frequency components of the signal, resulting in low accuracy of the frequency estimation result. Summary of the invention

[0005] To this end, the technical problem to be solved by the present invention is to overcome the problem that the three-phase electrical frequency estimation method in the prior art is easily affected by noise, resulting in the coefficients of the adaptive filter obtained based on the cost function update being inaccurate and unable to accurately reflect the true frequency components of the signal, thereby resulting in low accuracy of the frequency estimation result.

[0006] In order to solve the above technical problems, the present invention provides a three-phase electrical frequency estimation method, comprising:

[0007] Based on the three-phase voltage signal of the three-phase power system at time k, a target complex voltage signal at time k is obtained; based on the three-phase voltage signal of the three-phase power system at time k+1, a target complex voltage signal at time k+1 and its phase value are obtained;

[0008] Inputting the target complex voltage signal at time k into an adaptive filter based on a wide linear model, and outputting an estimated value of the complex voltage signal at time k+1 and its phase value according to the standard weight coefficient and conjugate weight coefficient of the adaptive filter based on the wide linear model at time k;

[0009] Calculate the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal;

[0010] Based on the difference at time k+1, the standard weight coefficient and the conjugate weight coefficient at time k, an augmented complex valued overall minimum average phase adaptive cost function at time k is constructed; wherein the augmented complex valued overall minimum average phase adaptive cost function at time k is expressed as:

[0011] ,

[0012] in, represents the augmented complex-valued overall minimum average phase adaptive cost function at time k; represents the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; represents the standard weight coefficient at time k; represents the conjugate weight coefficient at time k;

[0013] Based on the augmented complex valued overall minimum average phase adaptive cost function at the time k, the standard weight coefficient and the conjugate weight coefficient of the adaptive filter based on the wide linear model at the time k+1 are calculated, and the frequency estimation value of the three-phase power system at the time k+1 is calculated based on the standard weight coefficient and the conjugate weight coefficient at the time k+1.

[0014] Preferably, the calculation formula of the standard weight coefficient at the k+1 time is:

[0015] ,

[0016] in, represents the standard weight coefficient at time k+1; represents the standard weight coefficient at time k; Indicates the update step size of the weight coefficient; represents the augmented complex-valued overall minimum average phase adaptive cost function at time k; express The conjugate value of It means to find partial derivative; The unit representing the imaginary part of a complex number; represents the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; represents the conjugate value of the target complex voltage signal at time k; Represents the conjugate weight coefficient at time k.

[0017] Preferably, the calculation formula of the conjugate weight coefficient at the k+1 moment is:

[0018] ,

[0019] in, represents the conjugate weight coefficient at time k+1; represents the conjugate weight coefficient at time k; Indicates the update step size of the weight coefficient; represents the augmented complex-valued overall minimum average phase adaptive cost function at time k; express The conjugate value of It means to find partial derivative; The unit representing the imaginary part of a complex number; represents the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; represents the conjugate value of the target complex voltage signal at time k; Represents the standard weight coefficient at time k.

[0020] Preferably, the calculation formula of the frequency estimation value of the three-phase power system at time k+1 is:

[0021] ,

[0022] in, represents the frequency estimate of the three-phase power system at time k+1; represents the sampling interval; It means taking the imaginary part of a complex number; represents the standard weight coefficient at time k+1; Represents the conjugate weight coefficient at time k+1.

[0023] Preferably, the estimated value of the complex voltage signal at time k+1 is expressed as:

[0024] ,

[0025] in, represents the estimated value of the complex voltage signal at time k+1; represents the target complex voltage signal at time k; represents the standard weight coefficient at time k; Represents the target complex voltage signal at time k The conjugate value of represents the conjugate weight coefficient at time k;

[0026] The calculation formula for the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal is:

[0027] ,

[0028] in, represents the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; represents the phase value of the target complex voltage signal at time k+1; Represents the phase value of the complex voltage signal estimate at time k+1.

[0029] Preferably, obtaining a target complex voltage signal at time k based on a three-phase voltage signal of a three-phase power system at time k; obtaining a target complex voltage signal at time k+1 and its phase value based on a three-phase voltage signal of a three-phase power system at time k+1 includes:

[0030] Collect the three-phase voltage signal of the three-phase power system at time k, perform Clarke transformation on the three-phase voltage signal at time k, and obtain the three-phase complex voltage signal at time k; add measurement noise to the three-phase complex voltage signal at time k, and obtain the target complex voltage signal at time k;

[0031] A three-phase voltage signal of a three-phase power system at time k+1 is collected, and a Clarke transform is performed on the three-phase voltage signal at time k+1 to obtain a three-phase complex voltage signal at time k+1; measurement noise is added to the three-phase complex voltage signal at time k+1 to obtain a target complex voltage signal at time k+1, and based on the target complex voltage signal at time k+1, a phase value of the target complex voltage signal at time k+1 is obtained.

[0032] Preferably, the target complex voltage signal at time k is expressed as:

[0033] ,

[0034] in, represents the target complex voltage signal at time k; Represents the three-phase complex voltage signal at time k; represents the measurement noise;

[0035] The target complex voltage signal at time k+1 is expressed as:

[0036] ,

[0037] in, represents the target complex voltage signal at time k+1; Represents the three-phase complex voltage signal at time k+1.

[0038] The present invention also provides a three-phase electrical frequency estimation device, comprising:

[0039] A signal processing module is used to obtain a target complex voltage signal at time k based on the three-phase voltage signal of the three-phase power system at time k; and obtain a target complex voltage signal and its phase value at time k+1 based on the three-phase voltage signal of the three-phase power system at time k+1;

[0040] A signal prediction module, used for inputting the target complex voltage signal at time k into an adaptive filter based on a wide linear model, and outputting an estimated value of the complex voltage signal at time k+1 and its phase value according to the standard weight coefficient and conjugate weight coefficient of the adaptive filter based on the wide linear model at time k;

[0041] A difference calculation module, used to calculate the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal;

[0042] The cost function construction module is used to construct an augmented complex valued overall minimum average phase adaptive cost function at time k based on the difference at time k+1, the standard weight coefficient and the conjugate weight coefficient at time k; wherein the augmented complex valued overall minimum average phase adaptive cost function at time k is expressed as:

[0043] ,

[0044] in, represents the augmented complex-valued overall minimum average phase adaptive cost function at time k; represents the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; represents the standard weight coefficient at time k; represents the conjugate weight coefficient at time k;

[0045] The frequency estimation module is used to calculate the standard weight coefficient and conjugate weight coefficient of the adaptive filter based on the wide linear model at the k+1 moment based on the augmented complex valued overall minimum average phase adaptive cost function at the k moment, and calculate the frequency estimation value of the three-phase power system at the k+1 moment based on the standard weight coefficient and conjugate weight coefficient at the k+1 moment.

[0046] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned three-phase electrical frequency estimation method are implemented.

[0047] The three-phase electrical frequency estimation method provided in the present application utilizes an adaptive filter based on a wide linear model to perform voltage prediction, and adds the calculation of the conjugate part of the voltage complex signal. When the three phases are unbalanced, the adaptive filter based on the wide linear model can capture the influence of these unbalanced components on the prediction results by adjusting its own coefficients, thereby realizing unbiased estimation of the unbalanced three-phase power system; in addition, when constructing the cost function, an augmented complex valued overall minimum average phase adaptive cost function is constructed based on the difference between the phase value of the target complex voltage signal at the current moment and the phase value of the estimated value of the complex voltage signal at the current moment, the standard weight coefficient and the conjugate weight coefficient of the adaptive filter at the previous moment. Since the frequency estimation is closely related to the phase change rate of the signal, directly using the phase difference to construct the cost function can more accurately capture the frequency changes and obtain more precise results. frequency estimation value. In addition, the amplitude of the voltage signal is easily affected by noise, while the phase is not sensitive to these noises. Even in a noisy environment, the phase value of the signal will not fluctuate too much. Therefore, using the phase error instead of the amplitude error can have a higher sensitivity to the angle deviation in a noisy environment, thereby improving the accuracy of the frequency estimation. The present application constructs the relationship between the coefficients of the adaptive filter and the phase difference of the voltage signal, with the goal of minimizing the phase error between the actual complex voltage signal and the estimated complex voltage signal, and updates and adjusts the standard weight coefficients and conjugate weight coefficients of the adaptive filter. This can not only effectively reduce the phase deviation introduced by noise, but also more smoothly track the changes in the signal in the power system, reduce the impact of rapid frequency changes caused by rapid oscillations on the frequency estimation results, and improve the accuracy of the frequency estimation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below according to specific embodiments of the present invention in conjunction with the accompanying drawings, wherein:

[0049] Figure 1 A flow chart of a three-phase electrical frequency estimation method provided for this application;

[0050] Figure 2 A schematic diagram of the principle of the three-phase electrical frequency estimation method provided in this application;

[0051] Figure 3 A schematic diagram of the estimated deviation and estimated variance when the method provided by the present application and the existing method are applied to frequency estimation under unbalanced C-shaped notch and different noise levels; wherein, Figure 3(a) is a schematic diagram of the estimated deviation when applied to frequency estimation under unbalanced C-shaped notch and different noise levels. Figure 3 (b) is a schematic diagram of the estimated variance when applied to frequency estimation under unbalanced C-shaped depression and different noise levels;

[0052] Figure 4 A schematic diagram comparing the frequency estimation results obtained when the method provided by the present application and the existing method are applied to a balanced three-phase power system with high-order harmonic pollution;

[0053] Figure 5 A schematic diagram of voltage amplitude variation of a power system provided in this application;

[0054] Figure 6 The method provided in this application is applied to the existing method Figure 5 A schematic diagram showing the comparison of frequency estimation results obtained when the power system is shown;

[0055] Figure 7 This is a schematic diagram of the structure of the three-phase electrical frequency estimation device provided in this application. DETAILED DESCRIPTION

[0056] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0057] When estimating the three-phase electrical frequency, an adaptive filter is used to predict the three-phase voltage signal at the next moment based on the three-phase voltage signal at the current moment, and a cost function is constructed based on the difference between the actual value and the predicted value of the three-phase voltage signal at the next moment, so as to adjust the coefficient of the adaptive filter, and calculate the frequency component in the signal based on the coefficient of the adjusted adaptive filter, so as to predict the three-phase electrical frequency of the power system. However, the prior art often ignores the updating of the coefficient of the adaptive filter based on the difference between the actual value and the predicted value of the voltage signal, and focuses on the amplitude information of the signal. The amplitude of the signal is easily affected by noise, resulting in a large deviation between the predicted value and the actual value of the voltage signal output by the adaptive filter in a noisy environment. Therefore, the coefficient of the adaptive filter obtained based on the difference is not accurate, and the frequency change in the power system cannot be accurately captured, making the accuracy of the three-phase electrical frequency estimation result low. The present application discovers this problem and provides a three-phase electrical frequency estimation method to solve the problem of low accuracy of the three-phase electrical frequency estimation result obtained by the existing method.

[0058] See also Figure 1 , Figure 1 The figure shows a flow chart of a three-phase electrical frequency estimation method provided by the present application, which specifically includes:

[0059] S10: based on the three-phase voltage signal of the three-phase power system at time k, obtain the target complex voltage signal at time k; based on the three-phase voltage signal of the three-phase power system at time k+1, obtain the target complex voltage signal and its phase value at time k+1;

[0060] S20: inputting the target complex voltage signal at time k into an adaptive filter based on a wide linear model, and outputting an estimated value of the complex voltage signal at time k+1 and its phase value according to the standard weight coefficient and conjugate weight coefficient of the adaptive filter based on the wide linear model at time k;

[0061] S30: Calculate the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal;

[0062] S40: constructing an augmented complex-valued overall minimum average phase adaptive cost function at time k based on the difference at time k+1, the standard weight coefficient and the conjugate weight coefficient at time k;

[0063] S50: Based on the augmented complex valued overall minimum average phase adaptive cost function at the time k, calculate the standard weight coefficient and conjugate weight coefficient of the adaptive filter based on the wide linear model at the time k+1, and calculate the frequency estimation value of the three-phase power system at the time k+1 based on the standard weight coefficient and conjugate weight coefficient at the time k+1.

[0064] The three-phase electrical frequency estimation method provided in the present application utilizes an adaptive filter based on a wide linear model to perform voltage prediction, and adds the calculation of the conjugate part of the voltage complex signal. When the three phases are unbalanced, the adaptive filter based on the wide linear model can capture the influence of these unbalanced components on the prediction results by adjusting its own coefficients, thereby realizing unbiased estimation of the unbalanced three-phase power system; in addition, when constructing the cost function, an augmented complex valued overall minimum average phase adaptive cost function is constructed based on the difference between the phase value of the target complex voltage signal at the current moment and the phase value of the estimated value of the complex voltage signal at the current moment, the standard weight coefficient and the conjugate weight coefficient of the adaptive filter at the previous moment. Since the frequency estimation is closely related to the phase change rate of the signal, directly using the phase difference to construct the cost function can be more accurate The frequency change can be captured accurately to obtain a more accurate frequency estimate. In addition, the amplitude of the voltage signal is easily affected by noise, while the phase is not sensitive to these noises. Using the phase error instead of the amplitude error can have a higher sensitivity to the angle deviation in a noisy environment, thereby improving the accuracy of the frequency estimation. The present application constructs the relationship between the coefficients of the adaptive filter and the phase difference of the voltage signal, with the goal of minimizing the phase error between the actual complex voltage signal and the estimated complex voltage signal, and updates and adjusts the standard weight coefficients and conjugate weight coefficients of the adaptive filter. This can not only effectively reduce the phase deviation introduced by noise, but also more smoothly track the changes in the signal in the power system, reduce the impact of rapid frequency changes caused by rapid oscillations on the frequency estimation results, and improve the accuracy of the frequency estimation results.

[0065] Specifically, in some embodiments of the present application, the implementation steps of step S10 include:

[0066] S100: collecting a three-phase voltage signal of a three-phase power system at time k, performing Clarke transformation on the three-phase voltage signal at time k, and obtaining a three-phase complex voltage signal at time k; adding measurement noise to the three-phase complex voltage signal at time k, and obtaining a target complex voltage signal at time k;

[0067] S101: Collect the three-phase voltage signal of the three-phase power system at time k+1, perform Clarke transform on the three-phase voltage signal at time k+1, and obtain the three-phase complex voltage signal at time k+1; add measurement noise to the three-phase complex voltage signal at time k+1 to obtain the target complex voltage signal at time k+1, and obtain the phase value of the target complex voltage signal at time k+1 based on the target complex voltage signal at time k+1.

[0068] Taking time k as an example, the three-phase voltage of the power system in a noise-free environment can be expressed as:

[0069] ,

[0070] ,

[0071] ,

[0072] in, , , They represent the peak values ​​of the fundamental voltage components of the three-phase voltages a, b, and c of the power system at time k respectively; Indicates the phase of the fundamental component; represents the angular frequency of the discrete-time system.

[0073] For the above three-phase voltage , and They are transformed into zero sequences through Clarke's orthogonal αβ transformation matrix , direct axis component and orthogonal axis components :

[0074] ,

[0075] Among them, the factor It is used to ensure that the power of the system remains unchanged under Clark transformation. In a balanced power system, that is, when = = When , , ,in, and Orthogonal, express and The amplitude value of .

[0076] From the above formula, the amplitude value can be derived is a constant, so we can use and Represents the three-phase complex voltage of the three-phase power system at time k: .

[0077] In an unbalanced power system, when the three-phase voltage deviates from the rated value, for example, in the case of voltage sags or transients of varying degrees, it will cause The rotation distribution of : ,in, , is the complex-valued coefficient of a complex sequence component.

[0078] Since there are often uncertainties and interferences in the actual operation of the power system, in order to make the estimated value of the complex voltage signal at the next moment output by the adaptive filter closer to the voltage value under the actual operating environment, the embodiment of the present application adds measurement noise to the three-phase complex voltage signal at time k and the three-phase complex voltage signal at time k+1, uses the noisy three-phase complex voltage signal at time k to predict the complex voltage signal at time k+1, and compares the predicted result with the noisy three-phase complex voltage signal at time k+1 to obtain the prediction error, so that the final frequency estimate is closer to the actual value.

[0079] Specifically, the target complex voltage signal at time k is expressed as:

[0080] ,

[0081] in, represents the target complex voltage signal at time k; Represents the three-phase complex voltage signal at time k; represents the measurement noise;

[0082] The target complex voltage signal at time k+1 is expressed as:

[0083] ,

[0084] in, represents the target complex voltage signal at time k+1; Represents the three-phase complex voltage signal at time k+1.

[0085] In some embodiments of the present application, if the measurement noise varies with time, for example, the measurement noise at time k is , the measurement noise at time k+1 is , then the target complex voltage signal at time k is expressed as , the target complex voltage signal at time k+1 is expressed as .

[0086] Furthermore, the estimated value of the complex voltage signal at time k+1 in step S20 is expressed as:

[0087] ,

[0088] in, represents the estimated value of the complex voltage signal at time k+1; represents the target complex voltage signal at time k; represents the standard weight coefficient at time k; Represents the target complex voltage signal at time k The conjugate value of represents the conjugate weight coefficient at time k;

[0089] Specifically, when k is the initial moment, and are all preset values. In a specific example of this application, when k is the initial moment, is 0.95+0.3j, is 0.

[0090] The calculation formula for the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal is:

[0091] ,

[0092] in, represents the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; represents the phase value of the target complex voltage signal at time k+1; Represents the phase value of the complex voltage signal estimate at time k+1.

[0093] Further, in some embodiments of the present application, the augmented complex-valued overall minimum average phase adaptive cost function at time k in step S40 is expressed as:

[0094] ,

[0095] in, represents the augmented complex-valued overall minimum average phase adaptive cost function at time k; represents the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; represents the standard weight coefficient at time k; Represents the conjugate weight coefficient at time k.

[0096] In the prior art, the difference between the target complex voltage signal at time k+1 and the estimated value of the complex voltage signal is usually calculated, and a cost function is constructed based on the difference. However, the difference between the voltage signals often only considers the difference in voltage amplitude, and cannot fully capture the subtle changes in phase or the impact of frequency errors. Moreover, in actual signals, noise and interference will have a greater impact on the amplitude, resulting in a large error in the cost function constructed based on the voltage amplitude difference. The coefficients calculated based on the cost function are also not accurate enough, which in turn affects the accuracy of the frequency estimation result.

[0097] The present application can more accurately reflect the error between the predicted value and the actual value of the adaptive filter output by calculating the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal, thereby avoiding noise interference. When constructing the cost function, the phase angle error is used instead of the amplitude error in the framework of total least squares, and the relationship between the phase angle error and the standard weight coefficient and conjugate weight coefficient of the adaptive filter is constructed at the same time, with the goal of minimizing the phase error between the actual complex voltage signal and the estimated complex voltage signal. It can not only have a high sensitivity to angle deviation in a noisy environment, but also can more accurately adjust the coefficients of the adaptive filter based on the error, and find the standard weight coefficient and conjugate weight coefficient corresponding to the minimum phase error, thereby achieving fast and accurate frequency estimation.

[0098] Specifically, in the embodiment of the present application, the gradient descent method is used to solve the augmented complex valued overall minimum average phase adaptive cost function at time k, and the standard weight coefficient and conjugate weight coefficient at time k+1 are calculated. In step S50, the calculation formula of the standard weight coefficient at time k+1 is:

[0099] ,

[0100] in, represents the standard weight coefficient at time k+1; represents the standard weight coefficient at time k; Indicates the update step size of the weight coefficient; represents the augmented complex-valued overall minimum average phase adaptive cost function at time k; express The conjugate value of It means to find partial derivative; The unit representing the imaginary part of a complex number; represents the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; represents the conjugate value of the target complex voltage signal at time k; Represents the conjugate weight coefficient at time k.

[0101] In step S50, the calculation formula of the conjugate weight coefficient at time k+1 is:

[0102] ,

[0103] in, represents the conjugate weight coefficient at time k+1; represents the conjugate weight coefficient at time k; Indicates the update step size of the weight coefficient; represents the augmented complex-valued overall minimum average phase adaptive cost function at time k; express The conjugate value of It means to find partial derivative; The unit representing the imaginary part of a complex number; represents the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; represents the conjugate value of the target complex voltage signal at time k; Represents the standard weight coefficient at time k.

[0104] Specifically, in a specific example of the present application, the update step length of the weight coefficient is The value range is 0.02~0.04.

[0105] In step S50, the frequency estimation value of the three-phase power system at time k+1 is calculated as follows:

[0106] ,

[0107] in, represents the frequency estimate of the three-phase power system at time k+1; represents the sampling interval; It means taking the imaginary part of a complex number; represents the standard weight coefficient at time k+1; Represents the conjugate weight coefficient at time k+1.

[0108] Specifically, the sampling interval represents the time interval between time k and time k+1. In a specific example of the present application, The value is 0.001s.

[0109] like Figure 2 The figure shows a schematic diagram of the principle of the three-phase electrical frequency estimation method provided by the present application. After performing Clarke transformation on the three-phase voltage signal at time k and adding measurement noise, the signal is input into an adaptive filter based on a wide linear model, and an estimated value of the complex voltage signal at time k+1 is output; at the same time, the three-phase voltage signal of the three-phase power system at time k+1 is Clarke transformed and measurement noise is added to obtain the target complex voltage signal at time k+1, and the coefficient of the adaptive filter is adjusted based on the phase difference between the target complex voltage signal at time k+1 and the estimated value of the complex voltage signal, and the standard weight coefficient and conjugate weight coefficient of the adaptive filter at time k+1 are obtained, thereby calculating the frequency estimate of the three-phase power system at time k+1.

[0110] The three-phase electrical frequency estimation method provided in the above embodiment is simulated and verified through three groups of experiments. Specifically, in the Matlab programming environment, the method (ACTLMP) provided in this application, the augmented complex valued minimum mean phase adaptive algorithm (ACLMP), and the augmented complex valued total least mean square adaptive algorithm (ACTLMS) are used to perform frequency estimation for several typical power system conditions. The sampling frequency during the experiment is 1kHz.

[0111] Experiment 1

[0112] The unbalanced C-type voltage sag is used to simulate the voltage imbalance in the three-phase power system. The peak values ​​of the fundamental voltage components of the a, b, and c three-phase voltages are:

[0113] ,

[0114] ,

[0115] ,

[0116] Among them, the update step length of the weight coefficient is , frequency initialization .

[0117] like Figure 3 The figure shows the estimated deviation and estimated variance of the three methods when applied to the above-mentioned unbalanced C-shaped notch and frequency estimation under different noise levels, where: Figure 3 (a) is a schematic diagram of the estimated deviation when the three methods are applied to the above-mentioned unbalanced C-shaped concave and frequency estimation under different noise levels. Figure 3 (b) is a schematic diagram of the estimated variance of the three methods when applied to the above-mentioned unbalanced C-type depression and frequency estimation under different noise levels. It can be seen from the figure that with the increase of the signal-to-noise ratio, the three frequency estimation methods are asymptotically unbiased and the variances are close to 0. However, the estimated deviation and estimated variance of the method ACTLMP provided in the present application are significantly smaller than those of ACLMP and ACTLMS. It can be seen that when the method provided in the present application is applied to a three-phase unbalanced power system, it has a stronger ability to resist noise interference and obtains a smaller oscillation error.

[0118] Experiment 2

[0119] A balanced three-phase power system polluted by high-order harmonics is used to simulate the situation where harmonics appear in a balanced three-phase power system with a frequency of 50Hz. The peak value of the fundamental voltage component of the a, b, and c three-phase voltages is , the 5th, 11th, and 13th sequence harmonics are introduced at the ratios of 5%, 5.5%, and 5.5%, respectively.

[0120] like Figure 4 Shown is a schematic diagram of the frequency estimation results of the above-mentioned power system using three methods. It can be seen from the figure that under the condition of harmonic pollution, the ACTLMS method cannot converge within the observation range, and the frequency estimation results obtained by the ACLMP and the ACTLMP method provided in the present application both show oscillation in the steady state, but the oscillation error of the ACTLMP method provided in the present application is significantly smaller than that of the ACLMP method. It can be seen that when the frequency estimation method provided in the present application is applied to a three-phase unbalanced power system with high-order harmonic pollution, the oscillation is small and the estimation result does not deviate from the true frequency, indicating that the method provided in the present application is less affected by harmonics.

[0121] Experiment 3

[0122] Simulate the voltage imbalance in the three-phase power system in real scenarios. The voltage amplitude of the power system changes as follows Figure 5 As shown in the figure, at t=0.03s, voltage amplitude imbalance occurs, where the voltage of phase A drops by 66.9%, and the voltages of phases B and C expand by 71.5% and 54.2% respectively.

[0123] like Figure 6 The figure shows a schematic diagram of the frequency estimation results of the above-mentioned power system using three methods. It can be seen from the figure that at t=0.03s, the frequency estimation values ​​of the three methods all showed serious and irrecoverable deviations from 50Hz. Starting from t=0.1s, the frequency estimation values ​​recovered to around 50Hz, but compared with the ACLMP and ACTLMS methods, the frequency estimation variance of the ACTLMP method provided by the present application is smaller, indicating that the method provided by the present application can avoid the frequency estimation deviation in the unbalanced state of the power system even when a serious fault (imbalance) occurs in the power system, and can quickly and accurately estimate the frequency of the system to achieve unbiased estimation of the unbalanced power system.

[0124] Based on the three-phase power frequency estimation method provided in the above embodiment, the embodiment of the present application also provides a three-phase power frequency estimation device, such as Figure 7 As shown, the device comprises:

[0125] The signal processing module 10 is used to obtain a target complex voltage signal at time k based on the three-phase voltage signal of the three-phase power system at time k; and obtain a target complex voltage signal and its phase value at time k+1 based on the three-phase voltage signal of the three-phase power system at time k+1;

[0126] A signal prediction module 20, configured to input the target complex voltage signal at time k into an adaptive filter based on a wide linear model, and output an estimated value of the complex voltage signal at time k+1 and its phase value according to a standard weight coefficient and a conjugate weight coefficient of the adaptive filter based on the wide linear model at time k;

[0127] A difference calculation module 30, used to calculate the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal;

[0128] The cost function construction module 40 is used to construct an augmented complex valued overall minimum average phase adaptive cost function at time k based on the difference at time k+1, the standard weight coefficient and the conjugate weight coefficient at time k;

[0129] The frequency estimation module 50 is used to calculate the standard weight coefficient and conjugate weight coefficient of the adaptive filter based on the wide linear model at time k+1 based on the augmented complex valued overall minimum average phase adaptive cost function at the time k, and calculate the frequency estimation value of the three-phase power system at time k+1 based on the standard weight coefficient and conjugate weight coefficient at time k+1.

[0130] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned three-phase electrical frequency estimation method are implemented.

[0131] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt 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 codes.

[0132] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0133] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0134] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0135] Obviously, the above embodiments are merely examples for the purpose of clear explanation and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the present invention.

Claims

1. A three-phase electrical frequency estimation method, characterized in that: include: Based on the three-phase voltage signal of the three-phase power system at time k, a target complex voltage signal at time k is obtained; Based on the three-phase voltage signal of the three-phase power system at time k+1, a target complex voltage signal and its phase value at time k+1 are obtained; Inputting the target complex voltage signal at time k into an adaptive filter based on a wide linear model, and outputting an estimated value of the complex voltage signal at time k+1 and its phase value according to the standard weight coefficient and conjugate weight coefficient of the adaptive filter based on the wide linear model at time k; Calculate the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; Based on the difference at time k+1, the standard weight coefficient and the conjugate weight coefficient at time k, an augmented complex valued overall minimum average phase adaptive cost function at time k is constructed; wherein the augmented complex valued overall minimum average phase adaptive cost function at time k is expressed as: ， in, represents the augmented complex-valued overall minimum average phase adaptive cost function at time k; represents the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; represents the standard weight coefficient at time k; represents the conjugate weight coefficient at time k; Based on the augmented complex valued overall minimum average phase adaptive cost function at the time k, the standard weight coefficient and the conjugate weight coefficient of the adaptive filter based on the wide linear model at the time k+1 are calculated, and the frequency estimation value of the three-phase power system at the time k+1 is calculated based on the standard weight coefficient and the conjugate weight coefficient at the time k+1.

2. The three-phase electrical frequency estimation method according to claim 1, characterized in that: The calculation formula of the standard weight coefficient at the k+1 moment is: ， in, represents the standard weight coefficient at time k+1; represents the standard weight coefficient at time k; Indicates the update step size of the weight coefficient; represents the augmented complex-valued overall minimum average phase adaptive cost function at time k; express The conjugate value of It means to find partial derivative; The unit representing the imaginary part of a complex number; represents the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; represents the conjugate value of the target complex voltage signal at time k; Represents the conjugate weight coefficient at time k.

3. The three-phase electrical frequency estimation method according to claim 1, characterized in that: The calculation formula of the conjugate weight coefficient at the k+1 moment is: ， in, represents the conjugate weight coefficient at time k+1; represents the conjugate weight coefficient at time k; Indicates the update step size of the weight coefficient; represents the augmented complex-valued overall minimum average phase adaptive cost function at time k; express The conjugate value of It means to find partial derivative; The unit representing the imaginary part of a complex number; represents the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; represents the conjugate value of the target complex voltage signal at time k; Represents the standard weight coefficient at time k.

4. The three-phase electrical frequency estimation method according to claim 1, characterized in that: The calculation formula of the frequency estimation value of the three-phase power system at time k+1 is: ， in, represents the frequency estimate of the three-phase power system at time k+1; represents the sampling interval; It means taking the imaginary part of a complex number; represents the standard weight coefficient at time k+1; Represents the conjugate weight coefficient at time k+1.

5. The three-phase electrical frequency estimation method according to claim 1, characterized in that: The estimated value of the complex voltage signal at time k+1 is expressed as: ， in, represents the estimated value of the complex voltage signal at time k+1; represents the target complex voltage signal at time k; represents the standard weight coefficient at time k; Represents the target complex voltage signal at time k The conjugate value of represents the conjugate weight coefficient at time k; The calculation formula for the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal is: ， in, represents the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; represents the phase value of the target complex voltage signal at time k+1; Represents the phase value of the complex voltage signal estimate at time k+1.

6. The three-phase electrical frequency estimation method according to claim 1, characterized in that: Based on the three-phase voltage signal of the three-phase power system at time k, the target complex voltage signal at time k is obtained; based on the three-phase voltage signal of the three-phase power system at time k+1, the target complex voltage signal at time k+1 and its phase value are obtained, including: Collect the three-phase voltage signal of the three-phase power system at time k, perform Clarke transformation on the three-phase voltage signal at time k, and obtain the three-phase complex voltage signal at time k; add measurement noise to the three-phase complex voltage signal at time k, and obtain the target complex voltage signal at time k; A three-phase voltage signal of a three-phase power system at time k+1 is collected, and a Clarke transform is performed on the three-phase voltage signal at time k+1 to obtain a three-phase complex voltage signal at time k+1; measurement noise is added to the three-phase complex voltage signal at time k+1 to obtain a target complex voltage signal at time k+1, and based on the target complex voltage signal at time k+1, a phase value of the target complex voltage signal at time k+1 is obtained.

7. The three-phase electrical frequency estimation method according to claim 6, characterized in that: The target complex voltage signal at time k is expressed as: ， in, represents the target complex voltage signal at time k; Represents the three-phase complex voltage signal at time k; represents the measurement noise; The target complex voltage signal at time k+1 is expressed as: ， in, represents the target complex voltage signal at time k+1; Represents the three-phase complex voltage signal at time k+1.

8. A three-phase electrical frequency estimation device, characterized in that: include: A signal processing module, used for obtaining a target complex voltage signal at time k based on a three-phase voltage signal of the three-phase power system at time k; Based on the three-phase voltage signal of the three-phase power system at time k+1, a target complex voltage signal and its phase value at time k+1 are obtained; A signal prediction module, used for inputting the target complex voltage signal at time k into an adaptive filter based on a wide linear model, and outputting an estimated value of the complex voltage signal at time k+1 and its phase value according to the standard weight coefficient and conjugate weight coefficient of the adaptive filter based on the wide linear model at time k; A difference calculation module, used to calculate the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; The cost function construction module is used to construct an augmented complex valued overall minimum average phase adaptive cost function at time k based on the difference at time k+1, the standard weight coefficient and the conjugate weight coefficient at time k; wherein the augmented complex valued overall minimum average phase adaptive cost function at time k is expressed as: ， in, represents the augmented complex-valued overall minimum average phase adaptive cost function at time k; represents the difference between the phase value of the target complex voltage signal at time k+1 and the phase value of the estimated value of the complex voltage signal; represents the standard weight coefficient at time k; represents the conjugate weight coefficient at time k; The frequency estimation module is used to calculate the standard weight coefficient and conjugate weight coefficient of the adaptive filter based on the wide linear model at the k+1 moment based on the augmented complex valued overall minimum average phase adaptive cost function at the k moment, and calculate the frequency estimation value of the three-phase power system at the k+1 moment based on the standard weight coefficient and conjugate weight coefficient at the k+1 moment.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the three-phase electrical frequency estimation method according to any one of claims 1 to 7 are implemented.

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