Harmonic impedance determination method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to a harmonic impedance determination method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: constructing a first regression equation and a first weight matrix according to harmonic voltage and harmonic current at a common connection point in a power grid system, and determining a harmonic impedance reference value and a background harmonic reference value according to the first regression equation and the first weight matrix; determining a second regression equation according to the harmonic impedance reference value and the first regression equation, and determining a second weight matrix according to the background harmonic reference value; and determining a background harmonic estimation value according to the second regression equation and the second weight matrix, and determining a harmonic impedance estimation value according to the background harmonic estimation value, the harmonic voltage and the harmonic current. The invention provides the harmonic impedance determination method suitable for the harmonic impedance change condition of the power system side, and the accuracy of the harmonic impedance determination method is effectively improved.

Description

Technical Field

[0001] The present application relates to the technical field of power grids, and particularly to a method, device, computer device, computer-readable storage medium, and computer program product for determining harmonic impedance. Background Art

[0002] With the rapid development of power electronics technology, more and more non-linear loads are connected to the power grid system on a large scale. During operation, non-linear loads inject harmonic currents into the power system, resulting in voltage waveform distortion, thereby increasing power grid system losses and deteriorating power quality. Accurate harmonic tracing can achieve harmonic control, and the key to harmonic tracing lies in accurately estimating the harmonic impedance on the power system side.

[0003] In the prior art, it is mostly assumed that the harmonic impedance on the power system side is constant and cannot be applied to the case where the harmonic impedance on the power system side changes. Therefore, there is an urgent need for a method for determining harmonic impedance applicable to the case where the harmonic impedance on the power system side changes. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a method, device, computer device, computer-readable storage medium, and computer program product for determining harmonic impedance that can be applied to the case where the harmonic impedance on the power system side changes.

[0005] In a first aspect, the present application provides a method for determining harmonic impedance, including:

[0006] Construct a first regression equation and a first weight matrix according to the harmonic voltage and harmonic current at the common connection point in the power grid system, and determine a harmonic impedance reference value and a background harmonic reference value according to the first regression equation and the first weight matrix;

[0007] Determine a second regression equation according to the harmonic impedance reference value and the first regression equation, and determine a second weight matrix according to the background harmonic reference value;

[0008] Determine a background harmonic estimated value according to the second regression equation and the second weight matrix, and determine a harmonic impedance estimated value according to the background harmonic estimated value, the harmonic voltage, and the harmonic current.

[0009] In one embodiment, the step of constructing a first regression equation and a first weight matrix according to the harmonic voltage and harmonic current at the common connection point in the power grid system includes: constructing an explanatory variable matrix and a explained variable matrix according to the harmonic voltage and the harmonic current, and constructing the first regression equation according to the explanatory variable matrix and the explained variable matrix; determining the degree of voltage change according to the harmonic voltage, and determining the first weight matrix according to the degree of voltage change.

[0010] In one embodiment, determining the second regression equation according to the harmonic impedance reference value and the first regression equation includes: splitting the harmonic impedance reference value to obtain a basic impedance component and a time-varying impedance residual component; updating the first regression equation based on the basic impedance component and the time-varying impedance residual component to obtain the second regression equation.

[0011] In one embodiment, determining the second weight matrix according to the background harmonic reference value includes: constructing an auxiliary plane according to the background harmonic reference value; determining the second weight matrix according to the auxiliary plane and the background harmonic reference value.

[0012] In one embodiment, determining the background harmonic estimation value according to the second regression equation and the second weight matrix includes: determining the background harmonic estimation value based on the geographically weighted regression algorithm according to the second regression equation and the second weight matrix.

[0013] In one embodiment, determining the harmonic impedance reference value and the background harmonic reference value according to the first regression equation and the first weight matrix includes: constructing an optimization function with the goal of minimizing the weighted residual sum of squares based on the first regression equation and the first weight matrix; solving the optimization function by weighted least squares to obtain the harmonic impedance reference value and the background harmonic reference value.

[0014] In a second aspect, the present application also provides a harmonic impedance determination device, including:

[0015] A first determination module, configured to construct a first regression equation and a first weight matrix according to the harmonic voltage and harmonic current at the point of common coupling in the power grid system, and determine a harmonic impedance reference value and a background harmonic reference value according to the first regression equation and the first weight matrix;

[0016] A second determination module, configured to determine a second regression equation according to the harmonic impedance reference value and the first regression equation, and determine a second weight matrix according to the background harmonic reference value;

[0017] A third determination module, configured to determine a background harmonic estimation value according to the second regression equation and the second weight matrix, and determine a harmonic impedance estimation value according to the background harmonic estimation value, the harmonic voltage, and the harmonic current.

[0018] In a third aspect, the present application also provides a computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the steps of the method described in any one of the embodiments in the first aspect are implemented.

[0019] Fourthly, the present application 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 method described in any one of the embodiments of the first aspect are implemented.

[0020] Fifthly, the present application also provides a computer program product, including a computer program. When the computer program is executed by a processor, the steps of the method described in any one of the embodiments of the first aspect are implemented.

[0021] For the above harmonic impedance determination method, device, computer device, computer-readable storage medium and computer program product, first, according to the harmonic voltage and harmonic current at the point of common coupling in the power grid system, a first regression equation and a first weight matrix are constructed, and the harmonic impedance reference value and the background harmonic reference value are determined according to the first regression equation and the first weight matrix. Then, according to the harmonic impedance reference value and the first regression equation, a second regression equation is determined, and a second weight matrix is determined according to the background harmonic reference value. Then, according to the second regression equation and the second weight matrix, the background harmonic estimated value is determined, and the harmonic impedance estimated value is determined according to the background harmonic estimated value, the harmonic voltage and the harmonic current. The harmonic impedance determination method provided by the present application first determines the harmonic impedance reference value and the background harmonic reference value according to the harmonic voltage and harmonic current at the point of common coupling in the power grid system, and then determines the harmonic impedance estimated value according to the harmonic impedance reference value and the background harmonic reference value, solving the problem that the prior art assumes that the harmonic impedance on the power system side is constant and cannot be applied to the case where the harmonic impedance on the power system side changes. Description of the Drawings

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments of the present application or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0023] Figure 1 It is a schematic flowchart of the harmonic impedance determination method in an embodiment;

[0024] Figure 2 It is a schematic flowchart of the method for constructing the first regression equation and the first weight matrix in an embodiment;

[0025] Figure 3 It is a schematic flowchart of the method for determining the harmonic impedance reference value and the background harmonic reference value in an embodiment;

[0026] Figure 4Schematic flowchart of a method for determining a second regression equation based on a harmonic impedance reference value and a first regression equation in an embodiment;

[0027] Figure 5 Schematic flowchart of a method for determining a second weight matrix based on a background harmonic reference value in an embodiment;

[0028] Figure 6 Schematic flowchart of a method for determining harmonic impedance in another embodiment;

[0029] Figure 7 Schematic diagram of a power grid system in an embodiment;

[0030] Figure 8 Schematic diagram of a comparison result in an embodiment;

[0031] Figure 9 Structural block diagram of a harmonic impedance determination device in an embodiment;

[0032] Figure 10 Internal structure diagram of a computer device in an embodiment;

[0033] Figure 11 Internal structure diagram of a computer device in another embodiment. Detailed implementation manners

[0034] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0035] With the rapid development of power electronics technology, more and more non-linear loads are connected to the power grid system on a large scale. During operation, non-linear loads inject harmonic currents into the power system, resulting in voltage waveform distortion, thereby increasing the power grid system loss and deteriorating the power quality. Accurate harmonic tracing can achieve harmonic control, and the key to harmonic tracing lies in accurately estimating the harmonic impedance on the power system side.

[0036] In the prior art, it is mostly assumed that the harmonic impedance on the power system side is constant and cannot be applied to the case where the harmonic impedance on the power system side changes. Therefore, there is an urgent need for a harmonic impedance determination method applicable to the case where the harmonic impedance on the power system side changes.

[0037] In view of this, the present application provides a harmonic impedance determination method applicable to the case where the harmonic impedance on the power system side changes, which can solve the problems existing in the prior art and effectively improve the accuracy of the harmonic impedance determination method.

[0038] The harmonic impedance determination method provided by this application may be executed by a computer device, which may be a terminal or a server.

[0039] In an exemplary embodiment, as Figure 1 shown, a harmonic impedance determination method is provided, and the method includes the following steps:

[0040] Step 101: Construct a first regression equation and a first weight matrix based on the harmonic voltage and harmonic current at the point of common coupling in the power grid system, and determine the harmonic impedance reference value and the background harmonic reference value according to the first regression equation and the first weight matrix.

[0041] The point of common coupling (PCC) refers to the electrical connection point between the user and the power grid system and is also the node for the electrical energy interaction between the two. Exemplarily, in an actual power grid, the point of common coupling is usually the high-voltage side bus of the user-side transformer or a specific location where the user connects to the distribution line. This point is the key position for distinguishing between the power grid system side and the user side, and is used to define harmonic responsibilities and monitor power quality. For example, the high-voltage side bus of the distribution transformer of a certain factory is the point of common coupling between the factory and the power grid system, and the harmonic condition here directly affects the power consumption quality of the internal equipment of the factory and other users in the power grid system.

[0042] Exemplarily, in an ideal state, the voltage waveform in the power grid system is a standard sine wave with a frequency of the fundamental frequency. However, due to the existence of non-linear loads, the current waveform is distorted. When these distorted currents flow through the power grid impedance, additional voltage components that are integer multiples of the fundamental frequency will be generated, and these components are harmonic voltages.

[0043] Furthermore, harmonic voltages will cause the voltage waveform to deviate from the sine shape, resulting in voltage distortion and affecting the normal operation of equipment, such as causing problems like motor heating and communication equipment interference.

[0044] Exemplarily, in an ideal state, the current in the power grid system is also a standard sine wave. However, when non-linear loads such as rectifiers, frequency converters, and electric arc furnaces are connected to the power grid system, the current and voltage of these devices no longer maintain a linear relationship, resulting in the current waveform no longer being a sine wave. In addition to the fundamental current, current components that are integer multiples of the fundamental frequency will also be generated, and these components are harmonic currents.

[0045] Furthermore, after harmonic currents are injected into the power grid system, they will flow in the power grid, affecting the normal operation of other devices and systems, increasing line losses, and even triggering resonance.

[0046] In some exemplary embodiments, the computer device may first obtain the harmonic voltage and harmonic current at the point of common coupling in the power grid system. The harmonic voltage and harmonic current may be a harmonic voltage sequence and a harmonic current sequence.

[0047] Specifically, the computer device may obtain the harmonic voltage and harmonic current through a data acquisition device installed at the point of common coupling in the power grid system.

[0048] Further, after obtaining the harmonic voltage and harmonic current at the point of common coupling in the power grid system, the computer device may establish a first regression equation and a first weight matrix based on the harmonic voltage and harmonic current.

[0049] Specifically, the computer device may establish a first regression equation and a first weight matrix based on the harmonic voltage and harmonic current by means of a pre-trained construction model.

[0050] As described above, after constructing the first regression equation and the first weight matrix according to the harmonic voltage and harmonic current at the point of common coupling in the power grid system, the computer device may further determine a harmonic impedance reference value and a background harmonic reference value based on the first regression equation and the first weight matrix.

[0051] The harmonic impedance reference value refers to a preliminary estimated value of the equivalent harmonic impedance on the power grid system side, which is used to reflect the impedance characteristic of the power grid system to harmonics. The background harmonic reference value refers to an estimated value of the background harmonic voltage at the point of common coupling that is not affected by the device to be detected, which is used to distinguish the harmonics generated by the device itself from the inherent harmonics of the power grid system.

[0052] Step 102: Determine a second regression equation based on the harmonic impedance reference value and the first regression equation, and determine a second weight matrix based on the background harmonic reference value.

[0053] In some exemplary embodiments, after determining the harmonic impedance reference value and the background harmonic reference value, the computer device may determine a second regression equation based on the harmonic impedance reference value and the first regression equation.

[0054] Specifically, the computer device determines a second regression equation based on the harmonic impedance reference value and the first regression equation by means of a pre-trained second regression equation determination model.

[0055] Further, after determining the second regression equation based on the harmonic impedance reference value and the first regression equation, the computer device may further determine a second weight matrix based on the background harmonic reference value.

[0056] Specifically, the second weight matrix corresponds to the second regression equation.

[0057] Step 103: Determine the background harmonic estimation value according to the second regression equation and the second weight matrix, and determine the harmonic impedance estimation value according to the background harmonic estimation value, the harmonic voltage, and the harmonic current.

[0058] The background harmonic estimation value can be used to characterize the harmonic background level of the power grid system itself and is used to distinguish equipment harmonic emissions from the inherent harmonics of the power grid system.

[0059] The harmonic impedance estimation value can be used to characterize the impedance characteristic of the power grid system to current at harmonic frequencies and can be used to evaluate the harmonic suppression ability of the power grid system or detect the harmonic emission level of equipment.

[0060] In some exemplary embodiments, after determining the second regression equation and the second weight matrix, the computer device can determine the background harmonic estimation value according to the second regression equation and the second weight matrix.

[0061] Specifically, the computer device can determine the background harmonic estimation value according to the second regression equation and the second weight matrix based on a pre-trained background harmonic estimation value determination model.

[0062] Further, after determining the background harmonic estimation value according to the second regression equation and the second weight matrix, the computer device can determine the harmonic impedance estimation value according to the background harmonic estimation value, the harmonic voltage, and the harmonic current.

[0063] Specifically, the computer device can determine the harmonic impedance estimation value according to the background harmonic estimation value, the harmonic voltage, and the harmonic current based on a pre-trained harmonic impedance estimation value determination model.

[0064] For the above harmonic impedance determination method, first, based on the harmonic voltage and harmonic current at the common connection point in the power grid system, a first regression equation and a first weight matrix are constructed, and the harmonic impedance reference value and the background harmonic reference value are determined according to the first regression equation and the first weight matrix. Then, a second regression equation is determined according to the harmonic impedance reference value and the first regression equation, and a second weight matrix is determined according to the background harmonic reference value. Then, the background harmonic estimation value is determined according to the second regression equation and the second weight matrix, and the harmonic impedance estimation value is determined according to the background harmonic estimation value, the harmonic voltage, and the harmonic current. The harmonic impedance determination method provided in this application first determines the harmonic impedance reference value and the background harmonic reference value according to the harmonic voltage and harmonic current at the common connection point in the power grid system, and then determines the harmonic impedance estimation value according to the harmonic impedance reference value and the background harmonic reference value, solving the problem that the prior art assumes a constant harmonic impedance on the power system side and cannot be applied to the case where the harmonic impedance on the power system side changes.

[0065] In an exemplary embodiment, such as Figure 2As shown, constructing the first regression equation and the first weight matrix based on the harmonic voltage and harmonic current at the point of common coupling in the power grid system includes the following steps:

[0066] Step 201: Construct an explanatory variable matrix and a explained variable matrix based on the harmonic voltage and the harmonic current, and construct the first regression equation based on the explanatory variable matrix and the explained variable matrix.

[0067] In some exemplary embodiments, after the computer device obtains the harmonic voltage and harmonic current at the point of common coupling in the power grid system, it can construct an explanatory variable matrix and a explained variable matrix based on the harmonic voltage and the harmonic current.

[0068] Specifically, assume that the harmonic voltage at the point of common coupling is and the harmonic current at the point of common coupling is . If the explanatory variable matrix constructed based on the harmonic voltage and the harmonic current is X and the explained variable matrix is Y, then , . Among them, t i represents the sample point serial number, i = 1, 2,..., N, and N is the total number of sample points.

[0069] Furthermore, after the computer device constructs the explanatory variable matrix and the explained variable matrix based on the harmonic voltage and the harmonic current, it can construct the first regression equation based on the explanatory variable matrix and the explained variable matrix.

[0070] Specifically, the first regression equation can be expressed as , where , is the harmonic voltage source on the power grid system side, is the harmonic impedance on the power grid system side; is the regression coefficient matrix at time

[0071] Step 202: Determine the degree of voltage change based on the harmonic voltage, and determine the first weight matrix based on the degree of voltage change.

[0072] In some exemplary embodiments, the computer device can determine the degree of voltage change based on the harmonic voltage.

[0073] Specifically, the degree of voltage change can be expressed as . As the time interval between two sample points increases, the degree of voltage change will also increase. Therefore, the difference between the harmonic impedance or background harmonics on the power grid system side and the moment of interest can be approximately judged by the degree of voltage change, where , , 。

[0074] Further, after the computer device determines the degree of voltage change according to the harmonic voltage, it can also determine the first weight matrix according to the degree of voltage change.

[0075] Specifically, the first weight matrix can be expressed as , where, when the degree of voltage change at a certain moment is less than one percent, it can be considered that the difference between the impedance of the power grid system or the background harmonics and the concerned moment at this moment is small, and the true information of the concerned moment can be effectively reflected. When the degree of voltage change is greater than three percent, it is considered that the true information of the concerned moment cannot be correctly reflected at this moment, and the weight value of this moment should be reduced.

[0076] In an exemplary embodiment, as Figure 3 shown, determining the harmonic impedance reference value and the background harmonic reference value according to the first regression equation and the first weight matrix includes the following steps:

[0077] Step 301: Based on the first regression equation and the first weight matrix, construct an optimization function with the goal of minimizing the weighted sum of squared residuals.

[0078] In some exemplary embodiments, after the computer device determines the first regression equation and the first weight matrix, it can construct an optimization function with the goal of minimizing the weighted sum of squared residuals based on the first regression equation and the first weight matrix.

[0079] Specifically, the optimization function can be expressed as 。

[0080] Step 302: Solve the optimization function by weighted least squares to obtain the harmonic impedance reference value and the background harmonic reference value.

[0081] In some exemplary embodiments, after the computer device constructs an optimization function with the goal of minimizing the weighted sum of squared residuals based on the first regression equation and the first weight matrix, it can solve the optimization function by weighted least squares to obtain the harmonic impedance reference value and the background harmonic reference value.

[0082] Specifically, the harmonic impedance reference value can be expressed as ,the background harmonic reference value can be expressed as ,the 。

[0083] In an exemplary embodiment, as Figure 4As shown, determining the second regression equation according to the harmonic impedance reference value and the first regression equation includes the following steps:

[0084] Step 401: Split the harmonic impedance reference value to obtain a basic impedance component and a time-varying impedance residual component.

[0085] In some exemplary embodiments, after obtaining the harmonic impedance reference value and the background harmonic reference value, the computer device may split the harmonic impedance reference value to obtain a basic impedance component and a time-varying impedance residual component.

[0086] Specifically, the basic impedance component can be expressed as , is the calculation result of local weighted regression, and the time-varying impedance residual component can be expressed as , and .

[0087] Step 402: Update the first regression equation based on the basic impedance component and the time-varying impedance residual component to obtain the second regression equation.

[0088] In some exemplary embodiments, after splitting the harmonic impedance reference value to obtain a basic impedance component and a time-varying impedance residual component, the computer device may update the first regression equation based on the basic impedance component and the time-varying impedance residual component to obtain the second regression equation.

[0089] Specifically, the computer device may substitute the basic impedance component and the time-varying impedance residual component into the first regression equation to obtain the second regression equation, that is .

[0090] In an exemplary embodiment, as Figure 5 shown, determining the second weight matrix according to the background harmonic reference value includes the following steps:

[0091] Step 501: Construct an auxiliary plane according to the background harmonic reference value.

[0092] In some exemplary embodiments, after obtaining the background harmonic reference value, the computer device may construct an auxiliary plane according to the background harmonic reference value.

[0093] Specifically, in order to screen sample points similar to the background harmonic reference value at the moment of interest, the real part and the imaginary part after normalizing the background harmonic reference value can be used as the abscissa and ordinate respectively to construct an auxiliary plane. Among them, the abscissa and ordinate of the auxiliary plane are represented by and Indication. The smaller the Euclidean distance between the sample points on the auxiliary plane, the more similar the reference value of the background harmonic is. Since the reference value of the background harmonic has the same change trend as the true value, the true values of the background harmonics of the sample points with more similar reference values of the background harmonics are also more similar. Among them, , .

[0094] Step 502, determine the second weight matrix according to the auxiliary plane and the reference value of the background harmonic.

[0095] In some exemplary embodiments, after constructing the auxiliary plane according to the reference value of the background harmonic, the computer device can determine the second weight matrix according to the auxiliary plane and the reference value of the background harmonic.

[0096] Specifically, the computer device can construct the second weight matrix based on the distance between the sample point and the sample point at the moment of interest. The second weight matrix can be expressed as , where , .

[0097] In an exemplary embodiment, determining the estimated value of the background harmonic according to the second regression equation and the second weight matrix includes: determining the estimated value of the background harmonic according to the second regression equation and the second weight matrix based on the geographically weighted regression algorithm.

[0098] In some exemplary embodiments, after determining the second regression equation and the second weight matrix, the computer device can determine the estimated value of the background harmonic according to the second regression equation and the second weight matrix based on the geographically weighted regression algorithm.

[0099] Specifically, the estimated value of the background harmonic can be determined by solving . Among them, .

[0100] Further, after determining the estimated value of the background harmonic according to the second regression equation and the second weight matrix based on the geographically weighted regression algorithm, the computer device can determine the estimated value of the harmonic impedance according to the estimated value of the background harmonic, the harmonic voltage and the harmonic current.

[0101] Specifically, the estimated value of the harmonic impedance .

[0102] The harmonic impedance determination method provided by this application. In practical applications, although the harmonic impedance on the grid system side and the background harmonics are time-varying, the difference between adjacent moments is usually small. However, the larger the time interval between sample points, the greater this difference may be. The regression equation is weighted according to the time interval, and smaller weights are assigned to sample points with a larger time interval from the moment of interest. The reference value of the harmonic impedance on the grid system side and the reference value of the background harmonics are solved through locally weighted regression; and the regression equation is corrected using the reference value of the harmonic impedance to reduce its underdetermined degree. At the same time, using the reference value of the background harmonics as prior information, sample points similar to the reference value of the background harmonics at each moment are respectively selected and given larger weights, and the background harmonic voltage values at each moment are solved one by one based on the selected data using geographically weighted regression. Then, the harmonic impedance on the grid system side is calculated using the harmonic voltage and harmonic current, effectively solving the problem that the harmonic impedance on the grid system side cannot be estimated under the condition of strong background harmonic fluctuations and non-constant harmonic impedance.

[0103] In an exemplary embodiment, as Figure 6 shown, another harmonic impedance determination method is provided, and this method includes the following steps:

[0104] Step 601: Construct an explanatory variable matrix and an explained variable matrix based on the harmonic voltage and the harmonic current, and construct the first regression equation based on the explanatory variable matrix and the explained variable matrix; determine the degree of voltage change based on the harmonic voltage;

[0105] Step 602: Determine the first weight matrix based on the degree of voltage change. Based on the first regression equation and the first weight matrix, construct an optimization function with the goal of minimizing the weighted sum of squared residuals; solve the optimization function through weighted least squares to obtain the reference value of the harmonic impedance and the reference value of the background harmonics;

[0106] Step 603: Split the reference value of the harmonic impedance to obtain a basic impedance component and a time-varying impedance residual component; perform update processing on the first regression equation based on the basic impedance component and the time-varying impedance residual component to obtain the second regression equation, and construct an auxiliary plane based on the reference value of the background harmonics; determine the second weight matrix based on the auxiliary plane and the reference value of the background harmonics;

[0107] Step 604: Based on the geographically weighted regression algorithm, determine the estimated value of the background harmonics according to the second regression equation and the second weight matrix, and determine the estimated value of the harmonic impedance according to the estimated value of the background harmonics, the harmonic voltage, and the harmonic current.

[0108] In an exemplary embodiment, the inventor of this application built in a modeling software as Figure 7The IEEE 13-bus power grid system shown is used to verify the accuracy of the harmonic impedance determination method provided in this application. This power grid system contains 13 buses and can represent a medium-sized industrial plant. The power grid system is powered by a 69 kV power source, and the distribution system operates at 13.8 kV. In the power grid system, 7 buses are connected to loads, the load at bus 13 is a harmonic source, and a harmonic source is added at bus 1, that is, the system-side harmonic source. Bus 13 is the bus of concern. Using the method provided in this application, the equivalent grid system-side harmonic impedance at bus 13 is estimated through the harmonic voltage and harmonic current measured at bus 13. 7th harmonic currents are injected at buses 1 and 13. The harmonic current injected at bus 1 is superimposed with a 10% random perturbation. At the same time, before injecting the current at bus 1, it is multiplied by m to reflect different background harmonic intensities. The harmonic current injected at bus 13 is superimposed with a 20% random perturbation, and a 10% random perturbation is superimposed on the load impedance. The capacitance value of the capacitor is set to 3000 var, and a sinusoidal half-wave fluctuation and a 10% random perturbation are superimposed on it. Table 1 and Figure 8 show the comparison results of using the harmonic impedance determination method provided in this application and using other harmonic impedance determination methods in different ways. Method 4 in Table 1 and Figure 8 is the harmonic impedance determination method provided in this application.

[0109] Table 1

[0110]

[0111] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0112] Based on the same inventive concept, the embodiments of this application also provide a harmonic impedance determination device for implementing the above-mentioned harmonic impedance determination method. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the harmonic impedance determination device provided below can refer to the limitations on the harmonic impedance determination method in the above text, and will not be repeated here.

[0113] In an exemplary embodiment, asFigure 9 As shown, a harmonic impedance determination device 900 is provided, including: a first determination module 901, a second determination module 902, and a third determination module 903, where:

[0114] The first determination module 901 is configured to construct a first regression equation and a first weight matrix according to the harmonic voltage and harmonic current at the common connection point in the power grid system, and determine a harmonic impedance reference value and a background harmonic reference value according to the first regression equation and the first weight matrix;

[0115] The second determination module 902 is configured to determine a second regression equation according to the harmonic impedance reference value and the first regression equation, and determine a second weight matrix according to the background harmonic reference value;

[0116] The third determination module 903 is configured to determine a background harmonic estimated value according to the second regression equation and the second weight matrix, and determine a harmonic impedance estimated value according to the background harmonic estimated value, the harmonic voltage, and the harmonic current.

[0117] In one embodiment, the first determination module 901 is specifically configured to construct an explanatory variable matrix and an explained variable matrix according to the harmonic voltage and the harmonic current, and construct the first regression equation according to the explanatory variable matrix and the explained variable matrix; determine the degree of voltage change according to the harmonic voltage, and determine the first weight matrix according to the degree of voltage change.

[0118] In one embodiment, the second determination module 902 is specifically configured to split the harmonic impedance reference value to obtain a basic impedance component and a time-varying impedance residual component; update the first regression equation based on the basic impedance component and the time-varying impedance residual component to obtain the second regression equation.

[0119] In one embodiment, the second determination module 902 is specifically configured to construct an auxiliary plane according to the background harmonic reference value; determine the second weight matrix according to the auxiliary plane and the background harmonic reference value.

[0120] In one embodiment, the third determination module 903 is specifically configured to determine a background harmonic estimated value according to the second regression equation and the second weight matrix based on the geographically weighted regression algorithm.

[0121] In one embodiment, the first determination module 901 is specifically configured to construct an optimization function with the goal of minimizing the weighted residual sum of squares based on the first regression equation and the first weight matrix; solve the optimization function by weighted least squares to obtain the harmonic impedance reference value and the background harmonic reference value.

[0122] Each module in the above harmonic impedance determination device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so as to facilitate the processor to call and execute the operations corresponding to each of the above modules.

[0123] In an exemplary embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 10 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements a harmonic impedance determination method.

[0124] In an exemplary embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 11As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, near field communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a method for determining harmonic impedance. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse, etc.

[0125] Those skilled in the art can understand that Figure 10 and Figure 11 the structure shown in is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0126] In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

[0127] According to the harmonic voltage and harmonic current at the common connection point in the power grid system, construct a first regression equation and a first weight matrix, and determine the harmonic impedance reference value and the background harmonic reference value according to the first regression equation and the first weight matrix;

[0128] Determine a second regression equation according to the harmonic impedance reference value and the first regression equation, and determine a second weight matrix according to the background harmonic reference value;

[0129] Determine the background harmonic estimation value according to the second regression equation and the second weight matrix, and determine the harmonic impedance estimation value according to the background harmonic estimation value, the harmonic voltage, and the harmonic current.

[0130] In one embodiment, when the processor executes the computer program, the following steps are further implemented: construct an explanatory variable matrix and an explained variable matrix according to the harmonic voltage and the harmonic current, and construct the first regression equation according to the explanatory variable matrix and the explained variable matrix; determine the degree of voltage change according to the harmonic voltage, and determine the first weight matrix according to the degree of voltage change.

[0131] In one embodiment, when the processor executes the computer program, the following steps are further implemented: split the harmonic impedance reference value to obtain a basic impedance component and a time-varying impedance residual component; perform an update process on the first regression equation based on the basic impedance component and the time-varying impedance residual component to obtain the second regression equation.

[0132] In one embodiment, when the processor executes the computer program, the following steps are further implemented: construct an auxiliary plane according to the background harmonic reference value; determine the second weight matrix according to the auxiliary plane and the background harmonic reference value.

[0133] In one embodiment, when the processor executes the computer program, the following steps are further implemented: based on the geographically weighted regression algorithm, determine the background harmonic estimation value according to the second regression equation and the second weight matrix.

[0134] In one embodiment, when the processor executes the computer program, the following steps are further implemented: based on the first regression equation and the first weight matrix, construct an optimization function with the goal of minimizing the weighted residual sum of squares; solve the optimization function by weighted least squares to obtain the harmonic impedance reference value and the background harmonic reference value.

[0135] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0136] Construct a first regression equation and a first weight matrix according to the harmonic voltage and the harmonic current at the point of common coupling in the power grid system, and determine the harmonic impedance reference value and the background harmonic reference value according to the first regression equation and the first weight matrix;

[0137] Determine a second regression equation according to the harmonic impedance reference value and the first regression equation, and determine a second weight matrix according to the background harmonic reference value;

[0138] Determine the background harmonic estimation value according to the second regression equation and the second weight matrix, and determine the harmonic impedance estimation value according to the background harmonic estimation value, the harmonic voltage, and the harmonic current.

[0139] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: constructing an explanatory variable matrix and an explained variable matrix according to the harmonic voltage and the harmonic current, and constructing the first regression equation according to the explanatory variable matrix and the explained variable matrix; determining the degree of voltage change according to the harmonic voltage, and determining the first weight matrix according to the degree of voltage change.

[0140] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: splitting the harmonic impedance reference value to obtain a basic impedance component and a time-varying impedance residual component; updating the first regression equation based on the basic impedance component and the time-varying impedance residual component to obtain the second regression equation.

[0141] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: constructing an auxiliary plane according to the background harmonic reference value; determining the second weight matrix according to the auxiliary plane and the background harmonic reference value.

[0142] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: determining the background harmonic estimated value based on the geographically weighted regression algorithm, according to the second regression equation and the second weight matrix.

[0143] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: constructing an optimization function with the goal of minimizing the weighted sum of squared residuals based on the first regression equation and the first weight matrix; solving the optimization function by weighted least squares to obtain the harmonic impedance reference value and the background harmonic reference value.

[0144] In one embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0145] Constructing a first regression equation and a first weight matrix according to the harmonic voltage and the harmonic current at the point of common coupling in the power grid system, and determining the harmonic impedance reference value and the background harmonic reference value according to the first regression equation and the first weight matrix;

[0146] Determining a second regression equation according to the harmonic impedance reference value and the first regression equation, and determining a second weight matrix according to the background harmonic reference value;

[0147] Determining the background harmonic estimated value according to the second regression equation and the second weight matrix, and determining the harmonic impedance estimated value according to the background harmonic estimated value, the harmonic voltage, and the harmonic current.

[0148] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: constructing an explanatory variable matrix and an explained variable matrix according to the harmonic voltage and the harmonic current, and constructing the first regression equation according to the explanatory variable matrix and the explained variable matrix; determining a degree of voltage change according to the harmonic voltage, and determining the first weight matrix according to the degree of voltage change.

[0149] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: splitting the harmonic impedance reference value to obtain a basic impedance component and a time-varying impedance residual component; updating the first regression equation based on the basic impedance component and the time-varying impedance residual component to obtain the second regression equation.

[0150] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: constructing an auxiliary plane according to the background harmonic reference value; determining the second weight matrix according to the auxiliary plane and the background harmonic reference value.

[0151] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: determining a background harmonic estimated value based on the geographically weighted regression algorithm, according to the second regression equation and the second weight matrix.

[0152] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: constructing an optimization function with the goal of minimizing the weighted sum of squared residuals based on the first regression equation and the first weight matrix; solving the optimization function by weighted least squares to obtain the harmonic impedance reference value and the background harmonic reference value.

[0153] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, artificial intelligence (AI) processors, etc., without limitation.

[0154] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in the present application.

[0155] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation to the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method for determining harmonic impedance, characterized in that, The method includes: Constructing a first regression equation and a first weight matrix based on the harmonic voltage and harmonic current at the point of common coupling in the power grid system, and determining a harmonic impedance reference value and a background harmonic reference value according to the first regression equation and the first weight matrix; Determining a second regression equation according to the harmonic impedance reference value and the first regression equation, and determining a second weight matrix according to the background harmonic reference value; Determining a background harmonic estimated value according to the second regression equation and the second weight matrix, and determining a harmonic impedance estimated value according to the background harmonic estimated value, the harmonic voltage, and the harmonic current.

2. The method according to claim 1, characterized in that, The constructing a first regression equation and a first weight matrix based on the harmonic voltage and harmonic current at the point of common coupling in the power grid system includes: Constructing an explanatory variable matrix and an explained variable matrix based on the harmonic voltage and the harmonic current, and constructing the first regression equation according to the explanatory variable matrix and the explained variable matrix; Determining the degree of voltage change according to the harmonic voltage, and determining the first weight matrix according to the degree of voltage change.

3. The method according to claim 1, characterized in that, The determining a second regression equation according to the harmonic impedance reference value and the first regression equation includes: Splitting the harmonic impedance reference value to obtain a basic impedance component and a time-varying impedance residual component; Updating the first regression equation based on the basic impedance component and the time-varying impedance residual component to obtain the second regression equation.

4. The method according to claim 1, wherein The determining a second weight matrix according to the background harmonic reference value includes: Constructing an auxiliary plane according to the background harmonic reference value; Determining the second weight matrix according to the auxiliary plane and the background harmonic reference value.

5. The method according to claim 1, wherein The determining a background harmonic estimated value according to the second regression equation and the second weight matrix includes: Determining a background harmonic estimated value based on the geographically weighted regression algorithm according to the second regression equation and the second weight matrix.

6. The method according to claim 1, characterized in that The determining a harmonic impedance reference value and a background harmonic reference value according to the first regression equation and the first weight matrix includes: Constructing an optimization function with the goal of minimizing the weighted sum of squared residuals based on the first regression equation and the first weight matrix; Solving the optimization function by weighted least squares to obtain the harmonic impedance reference value and the background harmonic reference value.

7. A harmonic impedance determination device, characterized in that, The device includes: A first determination module, configured to construct a first regression equation and a first weight matrix based on the harmonic voltage and harmonic current at the point of common coupling in the power grid system, and determine a harmonic impedance reference value and a background harmonic reference value according to the first regression equation and the first weight matrix; A second determination module, configured to determine a second regression equation according to the harmonic impedance reference value and the first regression equation, and determine a second weight matrix according to the background harmonic reference value; A third determination module, configured to determine a background harmonic estimated value according to the second regression equation and the second weight matrix, and determine a harmonic impedance estimated value according to the background harmonic estimated value, the harmonic voltage, and the harmonic current.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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