A method, device, equipment, medium and product for estimating time-varying harmonic impedance

Abstract

The present invention discloses a method, device, equipment, medium and product for estimating time-varying harmonic impedance, which obtains harmonic measurement data at a common connection point in a power grid system; constructs a regression equation and a weight matrix of local weighted regression according to the harmonic measurement data; calculates a harmonic impedance reference value and a background harmonic reference value using a weighted least square method according to the regression equation and the weight matrix; sorts and segments the background harmonic reference value to obtain a plurality of sub-data segments, and calculates a cross-correlation function of each sub-data segment according to the harmonic impedance reference value; calculates the system-side harmonic impedance according to the cross-correlation function. The present invention can realize harmonic impedance estimation for the problem of impedance variation and correlation between harmonic sources on both sides, and effectively improves the efficiency and accuracy of time-varying harmonic impedance estimation.

Description

Technical Field

[0001] The present invention relates to the technical field of power harmonic impedance, and in particular to a time-varying harmonic impedance estimation method, device, equipment, medium and product. Background Art

[0002] With the large-scale access of new energy sources such as wind power and photovoltaic power, as well as nonlinear users such as high-speed rail and urban rail transit, the number of harmonic sources in the power grid has increased and their distribution has become widespread. The harmonic distortion rate of the power grid has increased significantly, and the problem of excessive harmonics has become more serious, resulting in an increase in the risk of malfunction and failure of relay protection devices and automatic devices, and interference with the normal operation of the communication system; harmonics lead to increased losses for users and power grids and deterioration of power quality; at the same time, harmonics may also cause equipment damage, line shutdown, etc., endangering the safety of the power grid, and are becoming a major technical challenge that restricts the high-quality power supply and safe and stable operation of new power systems. Therefore, accurate harmonic tracing is conducive to harmonic source control or centralized control, and is the primary condition for achieving harmonic control. Accurate estimation of harmonic impedance helps to determine the harmonic emission and harmonic responsibility of the system side and the user side, which is of great significance for achieving harmonic control.

[0003] In applications, since the user side cannot be switched on and off at will and the background harmonics cannot be directly measured, the key to harmonic tracing is to accurately estimate the harmonic impedance on the system side using only the measurement data of the point of common coupling (PCC). However, due to the volatility of new energy and changes in system operation (large users or power supply start-up and shutdown, filter switching, etc.), the harmonic impedance on the system side may change over a large range or even suddenly. At the same time, the control system of new energy causes the harmonic sources on both sides to be correlated. Under these conditions, the existing harmonic impedance estimation method is no longer applicable, and it is necessary to study a harmonic impedance estimation method for impedance changes and the correlation between the harmonic sources on both sides. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a time-varying harmonic impedance estimation method, device, equipment, medium and product, which can realize harmonic impedance estimation for the problem of impedance change and correlation between harmonic sources on both sides, and effectively improve the efficiency and accuracy of time-varying harmonic impedance estimation.

[0005] To achieve the above object, an embodiment of the present invention provides a time-varying harmonic impedance estimation method, comprising:

[0006] Obtaining harmonic measurement data at a common connection point in a power grid system;

[0007] Constructing a regression equation and a weight matrix of local weighted regression according to the harmonic measurement data;

[0008] According to the regression equation and the weight matrix, a harmonic impedance reference value and a background harmonic reference value are calculated using a weighted least square method;

[0009] Sorting and segmenting the background harmonic reference values ​​to obtain a plurality of sub-data segments, and calculating a cross-correlation function of each of the sub-data segments according to the harmonic impedance reference values;

[0010] The system-side harmonic impedance is calculated according to the cross-correlation function.

[0011] As an improvement of the above solution, the harmonic measurement data includes harmonic voltage and harmonic current measured at the common connection point;

[0012] The step of constructing a regression equation based on the harmonic measurement data comprises:

[0013] The harmonic voltage measured at the common connection point is expressed as a function of the harmonic current measured at the common connection point, the system-side harmonic impedance, and the system-side harmonic voltage source, and a regression equation is obtained:

[0014]

[0015] Convert the regression equation into matrix form:

[0016]

[0017]

[0018] in, is the harmonic voltage source on the system side, is the system side harmonic impedance, is the harmonic voltage measured at the common connection point, is the harmonic current measured at the common connection point; is the explanatory variable matrix, is the explained variable matrix, is the regression coefficient matrix, (i=1, 2,…, N) represents the sample point number, and N is the total number of sample points.

[0019] As an improvement of the above solution, the weight matrix of local weighted regression is constructed according to the harmonic measurement data, including:

[0020] Judging whether there is a mutation according to the magnitude of the change in the harmonic voltage and harmonic current measured at the common connection point, so as to calculate the mutation index between the sample points; wherein the weight assigned to the mutation point is smaller than that of the non-mutation point;

[0021] Calculating a weighted index of the time interval between the sample points according to the time interval between the sample points; wherein the sample points with a larger time interval have a smaller weight value assigned thereto;

[0022] Constructing a weight matrix of local weighted regression according to the mutation index and the time interval weighted index;

[0023] Among them, the weight matrix of the local weighted regression is:

[0024]

[0025]

[0026] in, is the weight matrix of local weighted regression, is a time interval weighted indicator, is the mutation indicator, is the distance between sample points; i and j are the serial numbers of sample points, and N is the total number of sample points.

[0027] As an improvement of the above scheme, the harmonic impedance reference value and the background harmonic reference value are calculated using a weighted least square method according to the regression equation and the weight matrix, including:

[0028] Using the weight matrix of the local weighted regression to perform weighted least squares fitting on the regression equation, to obtain an estimated value of the regression coefficient matrix;

[0029] A reference value of the harmonic impedance on the system side and a reference value of the harmonic voltage source on the system side are calculated from the estimated value of the regression coefficient matrix, which are recorded as a harmonic impedance reference value and a background harmonic reference value respectively;

[0030] Among them, the objective function of the weighted least squares method to fit the regression equation is:

[0031]

[0032] The estimated value of the regression coefficient matrix is:

[0033]

[0034] in, is the background harmonic reference value, is the harmonic impedance reference value, is the weight matrix of local weighted regression.

[0035] As an improvement of the above scheme, the background harmonic reference value is sorted and segmented to obtain a plurality of sub-data segments, and the cross-correlation function of each sub-data segment is calculated according to the harmonic impedance reference value, including:

[0036] Sorting the background harmonic reference values ​​in ascending order and dividing them into a plurality of sub-data segments;

[0037] For each of the sub-data segments, a cross-correlation function between the background harmonic reference value and the harmonic current measured at the common connection point is calculated according to the following calculation formula:

[0038]

[0039] in, is the cross-correlation function, n is the total number of samples in each sub-segment, i is a sample point, k is the time interval between two sub-segments, is the background harmonic reference value, The magnitude of the harmonic currents measured at the point of common connection.

[0040] As an improvement of the above solution, the calculating harmonic impedance according to the cross-correlation function includes:

[0041] Determine a maximum time interval value; wherein the maximum time interval value is the maximum k value in the k value condition range that satisfies the weak correlation between the two random variables;

[0042] According to the maximum time interval value, constructing a time interval interval that satisfies a weak correlation between the background harmonic reference value and the harmonic current measured at the common connection point;

[0043] Calculating the harmonic impedance residual of each time interval according to the cross-correlation function satisfying that the time interval is within the time interval interval;

[0044] According to the harmonic impedance residual, the real part and the imaginary part of the harmonic impedance are calculated to obtain the system-side harmonic impedance;

[0045] The harmonic impedance residual includes a real harmonic impedance residual and an imaginary harmonic impedance residual, and the real harmonic impedance residual is:

[0046]

[0047] The real part of the harmonic impedance is:

[0048]

[0049] The imaginary harmonic impedance residual is:

[0050]

[0051] The imaginary part of the harmonic impedance is:

[0052]

[0053] in, and are the real and imaginary parts of the harmonic voltage measured at the common connection point, respectively.

[0054] An embodiment of the present invention provides a time-varying harmonic impedance estimation device, comprising:

[0055] A measurement data acquisition module, used to acquire harmonic measurement data at a common connection point in a power grid system;

[0056] A regression parameter construction module, used to construct a regression equation and a weight matrix of local weighted regression according to the harmonic measurement data;

[0057] A harmonic reference value calculation module, used to calculate the harmonic impedance reference value and the background harmonic reference value by using a weighted least square method according to the regression equation and the weight matrix;

[0058] A cross-correlation function calculation module, used for sorting and segmenting the background harmonic reference value to obtain a plurality of sub-data segments, and calculating the cross-correlation function of each sub-data segment according to the harmonic impedance reference value;

[0059] The harmonic impedance calculation module is used to calculate the system-side harmonic impedance according to the cross-correlation function.

[0060] An embodiment of the present invention provides a time-varying harmonic impedance estimation device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the time-varying harmonic impedance estimation method as described in any one of the above items is implemented.

[0061] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the time-varying harmonic impedance estimation methods described above.

[0062] An embodiment of the present invention provides a computer program product, which includes a computer program or a computer instruction. When the computer program or the computer instruction is executed by a processor, the method for estimating time-varying harmonic impedance as described in any one of the above is implemented.

[0063] Compared with the prior art, the time-varying harmonic impedance estimation method, device, equipment, medium and product disclosed in the present invention realize time-varying harmonic impedance estimation by considering the correlation of harmonic sources, adopt local weighted regression, realize variable impedance problem estimation by constructing a weight matrix, and reduce the influence of the correlation between harmonic sources on harmonic impedance estimation through data screening method. The present invention can realize harmonic impedance estimation for the problems of impedance change and correlation between harmonic sources on both sides, and effectively improve the efficiency and accuracy of time-varying harmonic impedance estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is a flow chart of a method for estimating time-varying harmonic impedance provided by an embodiment of the present invention;

[0065] Figure 2 is a simulation waveform diagram of harmonic impedance in an embodiment of the present invention;

[0066] Figure 3 It is a schematic diagram of the estimation error of different estimation methods;

[0067] Figure 4 It is a structural schematic diagram of a time-varying harmonic impedance estimation device provided by an embodiment of the present invention;

[0068] Figure 5 It is a structural schematic diagram of a time-varying harmonic impedance estimation device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0071] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0072] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0073] See also Figure 1 , is a flow chart of a time-varying harmonic impedance estimation method provided by an embodiment of the present invention. The embodiment of the present invention provides a time-varying harmonic impedance estimation method, including steps S11 to S15:

[0074] S11, obtaining harmonic measurement data at a common connection point in a power grid system;

[0075] S12. Constructing a regression equation and a weight matrix of local weighted regression according to the harmonic measurement data;

[0076] S13, according to the regression equation and the weight matrix, using weighted least squares method to calculate the harmonic impedance reference value and the background harmonic reference value;

[0077] S14, sorting and segmenting the background harmonic reference values ​​to obtain a plurality of sub-data segments, and calculating the cross-correlation function of each of the sub-data segments according to the harmonic impedance reference values;

[0078] S15. Calculate the system-side harmonic impedance according to the cross-correlation function.

[0079] In the embodiment of the present invention, data collection is first performed to obtain harmonic measurement data at the common connection point PCC in the power grid system, including the harmonic voltage measured at the PPC. Harmonic current Then, based on the harmonic measurement data, a regression equation is constructed, which is used to calculate the harmonic voltage measured at the PPC. Harmonic current To estimate the system side harmonic impedance and system side harmonic voltage source , using the local weighted regression algorithm, considering the correlation and distinction between sample points, and assigning certain weights to construct a weight matrix , and then use the weight matrix of the local weighted regression to fit the regression equation with the weighted least square method to calculate the harmonic impedance reference value and the reference value of the harmonic voltage source on the system side, that is, the background harmonic reference value ), finally, the original data is sorted and segmented by the background harmonic reference value, and the cross-correlation function of each sub-data segment is calculated in combination with the harmonic impedance reference value to calculate the harmonic impedance on the system side.

[0080] By adopting the technical means of the embodiments of the present invention, a time-varying harmonic impedance estimation method considering the correlation of harmonic sources is provided. Local weighted regression is adopted to realize the estimation of the variable impedance problem by constructing a weight matrix. The influence of the correlation between harmonic sources on the harmonic impedance estimation is reduced by the data screening method. The present invention can realize harmonic impedance estimation for the problem of impedance change and the correlation between harmonic sources on both sides, and effectively improve the efficiency and accuracy of time-varying harmonic impedance estimation.

[0081] As a preferred implementation, the embodiment of the present invention is further implemented on the basis of the above embodiment, and the harmonic measurement data includes the harmonic voltage measured at the common connection point. Harmonic current .

[0082] Then, in step S12, that is, constructing a regression equation based on the harmonic measurement data, includes steps S121 and S122:

[0083] S121. Express the harmonic voltage measured at the common connection point as a function of the harmonic current measured at the common connection point, the system-side harmonic impedance, and the system-side harmonic voltage source, to obtain a regression equation:

[0084]

[0085] S122, converting the regression equation into a matrix form:

[0086]

[0087] The matrix expressions are as follows:

[0088]

[0089] in, is the harmonic voltage source on the system side, is the system side harmonic impedance, is the harmonic voltage measured at the common connection point, is the harmonic current measured at the common connection point; is the explanatory variable matrix, is the explained variable matrix, is the regression coefficient matrix, (i=1, 2,…, N) represents the sample point number, and N is the total number of sample points.

[0090] Then, in step S12, that is, constructing a weight matrix of local weighted regression according to the harmonic measurement data, further includes steps S123 to S125:

[0091] S123, judging whether there is a mutation according to the magnitude of the change in the harmonic voltage and harmonic current measured at the common connection point, so as to calculate the mutation index between the sample points; wherein the weight value assigned to the mutation point is smaller than that of the non-mutation point;

[0092] S124, calculating a weighted index of the time interval between the sample points according to the time interval between the sample points; wherein the sample points with a larger time interval have a smaller weighted value;

[0093] S125, constructing a weight matrix of local weighted regression according to the mutation index and the time interval weighted index;

[0094] Among them, the weight matrix of the local weighted regression is:

[0095]

[0096]

[0097] in, is the weight matrix of local weighted regression, is a time interval weighted indicator, is the mutation indicator, is the distance between sample points; i and j are the serial numbers of sample points, and N is the total number of sample points.

[0098] In the embodiment of the present invention, since the system-side harmonic impedance and background harmonics in the actual system usually change continuously, there is a certain correlation between the previous and next sample points, and the longer the time distance between the two sample points, the weaker the correlation. Therefore, a smaller weight can be assigned to the sample points with a larger time interval to reduce their impact on the estimation results of the system-side harmonic impedance and background harmonics of the sample point of interest. In addition, the sudden changes in system impedance and background harmonics will lead to Therefore, for the possible background harmonics or impedance mutation, The magnitude of the change is used to judge, and then a smaller weight is assigned to the mutation point to reduce the impact of the mutation sample point on the result.

[0099] Based on the above weighting principles, the time interval weighted index is calculated , weighted according to the time distance between sample points, and calculate the mutation index ,according to The magnitude of the change in the amount of is used to determine whether there is a mutation, and a smaller weight is assigned to the mutation point to construct a weight matrix .

[0100] By adopting the technical means of the embodiments of the present invention, a regression equation is constructed to express the harmonic voltage measured at the PPC point as a function of the harmonic current measured at the PPC point, the system-side harmonic impedance and the system-side harmonic voltage source, so that the system-side harmonic impedance and the system-side harmonic voltage source can be estimated. Local weighted regression is used to consider the time correlation and possible mutations between sample points. A weight matrix is ​​constructed to reduce the impact of irrelevant or mutation sample points on the estimation results, thereby improving the accuracy and efficiency of subsequent estimation of the system-side harmonic impedance.

[0101] As a preferred implementation, the embodiment of the present invention is further implemented on the basis of the above embodiment, step S13, that is, according to the regression equation and the weight matrix, the harmonic impedance reference value and the background harmonic reference value are calculated by using the weighted least squares method, including steps S131 to S132:

[0102] S131, using the weight matrix of the local weighted regression to perform weighted least squares fitting on the regression equation to obtain an estimated value of the regression coefficient matrix;

[0103] S132, calculating a reference value of the system-side harmonic impedance and a reference value of the system-side harmonic voltage source from the estimated value of the regression coefficient matrix, and recording them as a harmonic impedance reference value and a background harmonic reference value, respectively;

[0104] In the embodiment of the invention, the objective function of the weighted least square method is to minimize the weighted residual square sum, and the harmonic impedance and the background harmonic reference value can be solved by minimizing the objective function.

[0105] Among them, the objective function of the weighted least squares method to fit the regression equation is:

[0106]

[0107] The estimated value of the regression coefficient matrix is:

[0108]

[0109] in, is the background harmonic reference value, is the harmonic impedance reference value, is the weight matrix of local weighted regression.

[0110] The weighted least square method is an optimization method that estimates the regression coefficient by minimizing the weighted error square sum. The embodiment of the present invention uses a weight matrix to weight the regression equation to improve the accuracy of harmonic impedance estimation.

[0111] As a preferred implementation, the embodiment of the present invention is further implemented on the basis of the above embodiment, step S14, that is, the background harmonic reference value is sorted and segmented to obtain a plurality of sub-data segments, and the cross-correlation function of each sub-data segment is calculated according to the harmonic impedance reference value, including steps S141 to S142:

[0112] S141, sorting the background harmonic reference values ​​in ascending order, and dividing them into a plurality of sub-data segments;

[0113] S142. For each of the sub-data segments, a cross-correlation function between the background harmonic reference value and the harmonic current measured at the common connection point is calculated according to the following calculation formula:

[0114]

[0115] in, is the cross-correlation function, n is the total number of samples in each sub-segment, i is a sample point, k is the time interval between two sub-segments, is the background harmonic reference value, The magnitude of the harmonic currents measured at the point of common connection.

[0116] Preferably, step S15, i.e., calculating harmonic impedance according to the cross-correlation function, comprises steps S151 to S154:

[0117] S151, determine the maximum time interval value ; Wherein, the maximum time interval value is the maximum k value in the k value condition range that satisfies the weak correlation between the two random variables;

[0118] S152. Constructing, according to the maximum time interval value, a time interval interval that satisfies a weak correlation between the background harmonic reference value and the harmonic current measured at the common connection point;

[0119] S153, calculating the harmonic impedance residual of each time interval according to the cross-correlation function satisfying that the time interval is within the time interval interval;

[0120] S154. Calculate the real part and the imaginary part of the harmonic impedance according to the harmonic impedance residual to obtain the system-side harmonic impedance.

[0121] Preferably, the k value condition range is , the time interval is .

[0122] In the embodiment of the present invention, the correlation function describes the correlation between two random variables at different periods, which is a decreasing function of the time interval k. In the time interval corresponding to , the two random variables have weak correlation, let To satisfy Maximum value, so when Located in the interval When the background harmonic reference value is determined and the modulus of the harmonic current measured at the PCC point Satisfy the weak correlation condition.

[0123] The following relations are satisfied:

[0124]

[0125] Multiply both ends of the above formula by available:

[0126]

[0127] In length In the sub-data segment, find the correlation function for both ends of the above formula:

[0128]

[0129] when Located in the interval hour, and are weakly correlated, and their cross-correlation function is approximately 0, which satisfies:

[0130]

[0131] The harmonic impedance residual of each time interval can be calculated, and then the harmonic impedance value of the system side can be calculated. .

[0132] in, is the modulus of the harmonic current at the common connection point, , is the real part of the harmonic impedance reference value, It is the difference between the true value and the reference value of the harmonic impedance.

[0133] The harmonic impedance residual includes a real harmonic impedance residual and an imaginary harmonic impedance residual, and the real harmonic impedance residual is:

[0134]

[0135] The real part of the harmonic impedance is:

[0136]

[0137] The imaginary harmonic impedance residual is:

[0138]

[0139] The imaginary part of the harmonic impedance is:

[0140]

[0141] in, and They are the real and imaginary parts of the harmonic voltage measured at the common connection point. real() means taking the real part of the parameter in the brackets, and imag() means taking the imaginary part of the parameter in the brackets.

[0142] By using the technical means of the embodiment of the present invention, the cross-correlation function is used to describe the correlation between two random variables at different periods. The embodiment of the present invention determines the weak correlation interval between the background harmonic reference value and the modulus value of the harmonic current measured at the PCC point by calculating the cross-correlation function between them. Within the weak correlation interval, the harmonic impedance residual is calculated using the formula, and the harmonic impedance is estimated by averaging all the residuals. This method takes into account the correlation between the harmonic sources and improves the accuracy of the harmonic impedance estimation.

[0143] The present invention will be further described in detail below in conjunction with specific embodiments, but the embodiments of the present invention are not limited thereto.

[0144] As an example, the amplitude of the harmonic current source on the user side is set to 100A, the phase angle is set to 0.524rad, and a 10% random disturbance is added to the amplitude and phase angle respectively. The amplitude of the harmonic voltage source on the system side is set to 1000V, the phase angle is set to 1.451rad, and a 5% random disturbance is added to the amplitude and phase angle respectively. The amplitude of the harmonic impedance on the user side is set to 50Ω, and the phase angle is set to 0.927rad. The amplitude and phase angle of the harmonic impedance on the user side are added with 5% random fluctuations, as shown in Table 1:

[0145] Table 1

[0146]

[0147] See also Figure 2 and Figure 3 , Figure 2 is a simulation waveform diagram of harmonic impedance in an embodiment of the present invention, Figure 3Schematic diagram of estimation error of different estimation methods. Method 1 adopts weighted minimum variation method, and method 2 adopts the estimation method of the embodiment of the present invention. Method 1 and method 2 are used to perform simulation respectively, and the simulation waveform diagram is as follows: Figure 2 As shown, it can be seen that the time-varying harmonic impedance estimation method considering the harmonic source correlation in the embodiment of the present invention has a faster estimation speed and more accurate estimation precision.

[0148] See also Figure 4 , is a schematic diagram of the structure of a time-varying harmonic impedance estimation device provided by an embodiment of the present invention. The embodiment of the present invention provides a time-varying harmonic impedance estimation device 10, comprising:

[0149] The measurement data acquisition module 11 is used to acquire harmonic measurement data at a common connection point in the power grid system;

[0150] A regression parameter construction module 12, used to construct a regression equation and a weight matrix of local weighted regression according to the harmonic measurement data;

[0151] A harmonic reference value calculation module 13, used to calculate the harmonic impedance reference value and the background harmonic reference value by using a weighted least square method according to the regression equation and the weight matrix;

[0152] A cross-correlation function calculation module 14 is used to sort and segment the background harmonic reference value to obtain a plurality of sub-data segments, and calculate the cross-correlation function of each sub-data segment according to the harmonic impedance reference value;

[0153] The harmonic impedance calculation module 15 is used to calculate the system-side harmonic impedance according to the cross-correlation function.

[0154] As a preferred implementation, the harmonic measurement data includes harmonic voltage and harmonic current measured at a common connection point.

[0155] The regression parameter construction module 12 is specifically used for:

[0156] The harmonic voltage measured at the common connection point is expressed as a function of the harmonic current measured at the common connection point, the system-side harmonic impedance, and the system-side harmonic voltage source, and a regression equation is obtained:

[0157]

[0158] Convert the regression equation into matrix form:

[0159]

[0160]

[0161] in, is the harmonic voltage source on the system side, is the system side harmonic impedance, is the harmonic voltage measured at the common connection point, is the harmonic current measured at the common connection point; is the explanatory variable matrix, is the explained variable matrix, is the regression coefficient matrix, (i=1, 2,…, N) represents the sample point number, and N is the total number of sample points.

[0162] Judging whether there is a mutation according to the magnitude of the change in the harmonic voltage and harmonic current measured at the common connection point, so as to calculate the mutation index between the sample points; wherein the weight assigned to the mutation point is smaller than that to the non-mutation point;

[0163] Calculating a weighted index of the time interval between the sample points according to the time interval between the sample points; wherein the sample points with a larger time interval have a smaller weight value assigned thereto;

[0164] Constructing a weight matrix of local weighted regression according to the mutation index and the time interval weighted index;

[0165] Among them, the weight matrix of the local weighted regression is:

[0166]

[0167]

[0168] in, is the weight matrix of local weighted regression, is a time interval weighted indicator, is the mutation indicator, is the distance between sample points; i and j are the serial numbers of sample points, and N is the total number of sample points.

[0169] As a preferred implementation, the harmonic reference value calculation module 13 is specifically used for:

[0170] Using the weight matrix of the local weighted regression to perform weighted least squares fitting on the regression equation, to obtain an estimated value of the regression coefficient matrix;

[0171] A reference value of the harmonic impedance on the system side and a reference value of the harmonic voltage source on the system side are calculated from the estimated value of the regression coefficient matrix, which are recorded as a harmonic impedance reference value and a background harmonic reference value respectively;

[0172] Among them, the objective function of the weighted least squares method to fit the regression equation is:

[0173]

[0174] The estimated value of the regression coefficient matrix is:

[0175]

[0176] in, is the background harmonic reference value, is the harmonic impedance reference value, is the weight matrix of local weighted regression.

[0177] As a preferred implementation, the cross-correlation function calculation module 14 is specifically used for:

[0178] Sorting the background harmonic reference values ​​in ascending order and dividing them into a plurality of sub-data segments;

[0179] For each of the sub-data segments, a cross-correlation function between the background harmonic reference value and the harmonic current measured at the common connection point is calculated according to the following calculation formula:

[0180]

[0181] in, is the cross-correlation function, n is the total number of samples in each sub-segment, i is a sample point, k is the time interval between two sub-segments, is the background harmonic reference value, The magnitude of the harmonic currents measured at the point of common connection.

[0182] As a preferred implementation, the harmonic impedance calculation module 15 is specifically used for:

[0183] Determine a maximum time interval value; wherein the maximum time interval value is the maximum k value in the k value condition range that satisfies the weak correlation between the two random variables;

[0184] According to the maximum time interval value, constructing a time interval interval that satisfies a weak correlation between the background harmonic reference value and the harmonic current measured at the common connection point;

[0185] Calculating the harmonic impedance residual of each time interval according to the cross-correlation function satisfying that the time interval is within the time interval interval;

[0186] According to the harmonic impedance residual, the real part and the imaginary part of the harmonic impedance are calculated to obtain the system-side harmonic impedance;

[0187] The harmonic impedance residual includes a real harmonic impedance residual and an imaginary harmonic impedance residual, and the real harmonic impedance residual is:

[0188]

[0189] The real part of the harmonic impedance is:

[0190]

[0191] The imaginary harmonic impedance residual is:

[0192]

[0193] The imaginary part of the harmonic impedance is:

[0194]

[0195] in, and are the real and imaginary parts of the harmonic voltage measured at the common connection point, respectively.

[0196] It should be noted that the time-varying harmonic impedance estimation device provided in the embodiment of the present invention is used to execute all the process steps of the time-varying harmonic impedance estimation method in the above embodiment. The working principles and beneficial effects of the two correspond one to one, and thus will not be described in detail.

[0197] By adopting the technical means of the embodiments of the present invention, a time-varying harmonic impedance estimation method considering the correlation of harmonic sources is provided. Local weighted regression is adopted to realize the estimation of the variable impedance problem by constructing a weight matrix. The influence of the correlation between harmonic sources on the harmonic impedance estimation is reduced by the data screening method. The present invention can realize harmonic impedance estimation for the problem of impedance change and the correlation between harmonic sources on both sides, and effectively improve the efficiency and accuracy of time-varying harmonic impedance estimation.

[0198] See also Figure 5 , is a structural diagram of a time-varying harmonic impedance estimation device provided by an embodiment of the present invention. The embodiment of the present invention also provides a time-varying harmonic impedance estimation device 20, including a processor 21, a memory 22, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the time-varying harmonic impedance estimation method described in any one of the above embodiments is implemented.

[0199] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the time-varying harmonic impedance estimation method as described in any one of the above embodiments.

[0200] An embodiment of the present invention further provides a computer program product, which includes a computer program or computer instructions. When the computer program or the computer instructions are executed by a processor, the time-varying harmonic impedance estimation method as described in any one of the above embodiments is implemented.

[0201] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0202] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A time-varying harmonic impedance estimation method, characterized in that: include: Obtaining harmonic measurement data at a common connection point in a power grid system; constructing a regression equation and a weight matrix of local weighted regression according to the harmonic measurement data; According to the regression equation and the weight matrix, a harmonic impedance reference value and a background harmonic reference value are calculated using a weighted least square method; Sorting and segmenting the background harmonic reference values ​​to obtain a plurality of sub-data segments, and calculating a cross-correlation function of each of the sub-data segments according to the harmonic impedance reference values; Calculating the system-side harmonic impedance according to the cross-correlation function; The harmonic measurement data includes harmonic voltage and harmonic current measured at the common connection point; The step of constructing a regression equation based on the harmonic measurement data comprises: The harmonic voltage measured at the common connection point is expressed as a function of the harmonic current measured at the common connection point, the system-side harmonic impedance, and the system-side harmonic voltage source, and a regression equation is obtained: Convert the regression equation into matrix form: in, is the harmonic voltage source on the system side, is the system side harmonic impedance, is the harmonic voltage measured at the common connection point, is the harmonic current measured at the common connection point; is the explanatory variable matrix, is the explained variable matrix, is the regression coefficient matrix, Represents the sample point number, i=1, 2,…, N; N is the total number of sample points; The step of constructing a weight matrix of local weighted regression according to the harmonic measurement data comprises: Judging whether there is a mutation according to the magnitude of the change in the harmonic voltage and harmonic current measured at the common connection point, so as to calculate the mutation index between the sample points; wherein the weight assigned to the mutation point is smaller than that of the non-mutation point; Calculating a weighted index of the time interval between the sample points according to the time interval between the sample points; wherein the sample points with a larger time interval have a smaller weight value assigned thereto; Constructing a weight matrix of local weighted regression according to the mutation index and the time interval weighted index; Among them, the weight matrix of the local weighted regression is: in, is the weight matrix of local weighted regression, is a time interval weighted indicator, is the mutation indicator, is the distance between sample points; i and j are the serial numbers of sample points, and N is the total number of sample points.

2. The time-varying harmonic impedance estimation method according to claim 1, characterized in that: The method of calculating the harmonic impedance reference value and the background harmonic reference value by using the weighted least square method according to the regression equation and the weight matrix includes: Using the weight matrix of the local weighted regression to perform weighted least squares fitting on the regression equation, to obtain an estimated value of the regression coefficient matrix; A reference value of the harmonic impedance on the system side and a reference value of the harmonic voltage source on the system side are calculated from the estimated value of the regression coefficient matrix, which are recorded as a harmonic impedance reference value and a background harmonic reference value respectively; Among them, the objective function of the weighted least squares method to fit the regression equation is: The estimated value of the regression coefficient matrix is: in, is the background harmonic reference value, is the harmonic impedance reference value, is the weight matrix of local weighted regression.

3. The time-varying harmonic impedance estimation method according to claim 2, characterized in that: The step of sorting and segmenting the background harmonic reference values ​​to obtain a plurality of sub-data segments, and calculating the cross-correlation function of each sub-data segment according to the harmonic impedance reference value comprises: Sorting the background harmonic reference values ​​in ascending order and dividing them into a plurality of sub-data segments; For each of the sub-data segments, a cross-correlation function between the background harmonic reference value and the harmonic current measured at the common connection point is calculated according to the following calculation formula: in, is the cross-correlation function, n is the total number of samples in each sub-segment, i is a sample point, k is the time interval between two sub-segments, is the background harmonic reference value, The magnitude of the harmonic currents measured at the point of common connection.

4. The time-varying harmonic impedance estimation method according to claim 3, characterized in that: The step of calculating harmonic impedance according to the cross-correlation function comprises: Determine a maximum time interval value; wherein the maximum time interval value is the maximum k value in the k value condition range that satisfies the weak correlation between the two random variables; According to the maximum time interval value, constructing a time interval interval that satisfies a weak correlation between the background harmonic reference value and the harmonic current measured at the common connection point; Calculating the harmonic impedance residual of each time interval according to the cross-correlation function satisfying that the time interval is within the time interval interval; According to the harmonic impedance residual, the real part and the imaginary part of the harmonic impedance are calculated to obtain the system-side harmonic impedance; The harmonic impedance residual includes a real harmonic impedance residual and an imaginary harmonic impedance residual, and the real harmonic impedance residual is: The real part of the harmonic impedance is: The imaginary harmonic impedance residual is: The imaginary part of the harmonic impedance is: in, and are the real and imaginary parts of the harmonic voltage measured at the common connection point, respectively.

5. A time-varying harmonic impedance estimation device, characterized in that: include: A measurement data acquisition module, used to acquire harmonic measurement data at a common connection point in a power grid system; A regression parameter construction module, used to construct a regression equation and a weight matrix of local weighted regression according to the harmonic measurement data; A harmonic reference value calculation module, used to calculate the harmonic impedance reference value and the background harmonic reference value by using a weighted least square method according to the regression equation and the weight matrix; A cross-correlation function calculation module, used for sorting and segmenting the background harmonic reference value to obtain a plurality of sub-data segments, and calculating the cross-correlation function of each sub-data segment according to the harmonic impedance reference value; A harmonic impedance calculation module, used to calculate the system-side harmonic impedance according to the cross-correlation function; The harmonic measurement data includes harmonic voltage and harmonic current measured at the common connection point; The step of constructing a regression equation based on the harmonic measurement data comprises: The harmonic voltage measured at the common connection point is expressed as a function of the harmonic current measured at the common connection point, the system-side harmonic impedance, and the system-side harmonic voltage source, and a regression equation is obtained: Convert the regression equation into matrix form: in, is the harmonic voltage source on the system side, is the system side harmonic impedance, is the harmonic voltage measured at the common connection point, is the harmonic current measured at the common connection point; is the explanatory variable matrix, is the explained variable matrix, is the regression coefficient matrix, Represents the sample point number, i=1, 2,…, N; N is the total number of sample points; The step of constructing a weight matrix of local weighted regression according to the harmonic measurement data comprises: Judging whether there is a mutation according to the magnitude of the change in the harmonic voltage and harmonic current measured at the common connection point, so as to calculate the mutation index between the sample points; wherein the weight assigned to the mutation point is smaller than that of the non-mutation point; Calculating a weighted index of the time interval between the sample points according to the time interval between the sample points; wherein the sample points with a larger time interval have a smaller weight value assigned thereto; Constructing a weight matrix of local weighted regression according to the mutation index and the time interval weighted index; Among them, the weight matrix of the local weighted regression is: in, is the weight matrix of local weighted regression, is a time interval weighted indicator, is the mutation indicator, is the distance between sample points; i and j are the serial numbers of sample points, and N is the total number of sample points.

6. A time-varying harmonic impedance estimation device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the time-varying harmonic impedance estimation method according to any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the time-varying harmonic impedance estimation method according to any one of claims 1 to 4.

8. A computer program product, characterized in that The computer program product comprises a computer program or a computer instruction, and when the computer program or the computer instruction is executed by a processor, the time-varying harmonic impedance estimation method according to any one of claims 1 to 4 is implemented.

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