Harmonic impedance estimation method and system based on minimum correlation

Abstract

The invention relates to a harmonic impedance estimation method and system based on minimum correlation, and the method comprises the following steps: collecting a voltage time sequence and a current time sequence of a PCC point in a power system, extracting each voltage harmonic component and each current harmonic component through employing a fast Fourier transform method, fast-changing components of each harmonic voltage and harmonic current are further extracted; and a harmonic impedance optimization model with minimum correlation is constructed based on the fast-changing component of each harmonic current, optimization is carried out under constraint conditions by adopting an optimization algorithm, each harmonic impedance estimation value is obtained, and the correlation refers to the correlation between a real part and an imaginary part of each current harmonic component on two sides of a PCC point. Compared with the prior art, the method has the advantages that the interference of background harmonic fluctuation on an estimation result is more effectively suppressed, and the like.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power systems, in particular to a harmonic impedance estimation method and system based on minimum correlation. BACKGROUND

[0002] In the operation and management of power systems, accurately defining the harmonic responsibility of the system side and the user side is crucial for ensuring the safe and stable operation of the power grid and maintaining the legal rights and interests of all parties. Traditional harmonic responsibility analysis methods often require direct access to internal key equipment for measurement, which not only affects the normal operation of the power grid to some extent, but also may lead to a significant increase in cost due to complex equipment modification and maintenance, making it difficult to implement large-scale and high-frequency use.

[0003] The "non-intrusive" harmonic responsibility analysis method emerged as the times required. When the power grid is in normal operation, this method only needs to measure the harmonic voltage at the point of common coupling (PCC point) and measure the harmonic current on the common line, and then use a specific algorithm to quantitatively evaluate the harmonic responsibility of the system side and the user side. Since this method does not require intrusive operation on the power grid and has little interference with the normal operation of the power grid, and the measurement equipment is relatively simple and low-cost, it can be used repeatedly. In the case of high enough algorithm calculation speed, real-time evaluation of the harmonic responsibility of the system side and the user side can even be achieved. However, although the "non-intrusive" method does not affect the normal operation of the power grid during the process, it relies only on the measured harmonic voltage and current data to quantitatively analyze the harmonic responsibility of both sides, which puts high demands on the accuracy, reliability and adaptability of the algorithm used. SUMMARY

[0004] The purpose of the present application is to provide a harmonic impedance estimation method and system based on minimum correlation for accurate harmonic impedance estimation.

[0005] The purpose of the present application can be achieved by the following technical solutions: A harmonic impedance estimation method based on minimum correlation, comprising the following steps: Collecting the voltage time sequence and current time sequence of the PCC point in the power system, using the fast Fourier transform method to extract the harmonic components of each voltage and current, and further extracting the fast-varying components of each harmonic voltage and current; Based on the fast-varying components of each harmonic current, a harmonic impedance optimization model based on minimum correlation is constructed, and an optimization algorithm is used to optimize under the constraint condition to obtain the harmonic impedance estimation value, wherein the correlation refers to the correlation between the real and imaginary parts of each current harmonic component on both sides of the PCC point.

[0006] Further, the PCC point is a connection point between the user side and the system side, and the user side and the system side are respectively located on two sides of the PCC point.

[0007] Further, the fast-varying components of the harmonic voltage and the harmonic current are extracted by using a median filtering method.

[0008] Further, in the case that there are nonlinear elements on two sides of the PCC point, the nonlinear elements are equivalent to harmonic sources at the harmonic frequency, and the remaining elements are regarded as linear impedances, and the harmonic voltage components and the harmonic current components are calculated based on the superposition principle.

[0009] Further, the hth harmonic voltage component and the hth harmonic current component are respectively represented as: In the formula, 、 is the hth harmonic voltage component measured at the PCC point and the hth harmonic current component measured on the public line, 、 is the hth equivalent harmonic current of the user side and the system side, 、 is the hth equivalent harmonic impedance of the user side and the system side.

[0010] Further, the fast-varying components of the hth harmonic current of the user side and the system side 、 and the hth equivalent harmonic impedance of the user side and the system side corresponding thereto 、 satisfy the following relationship: In the formula, 、 is the fast-varying component of the hth harmonic voltage and the hth harmonic current at the PCC point.

[0011] Further, the harmonic impedance optimization model with the minimum correlation includes a target function and corresponding constraint conditions, and the construction steps of the target function include: Supposing that the fast-varying components of the harmonic current of the system side and the user side are nearly 0 in correlation, a target function is designed, and the expression of the hth target function is as follows: In which: In the formula, F is the hth target function, represents the correlation coefficient between x and y , and , fast varying component of hth harmonic current of the user side and the system side, Re x represents the real part of x , Im x represents the imaginary part of x ; The design step of the constraint condition comprises: Considering the voltage fluctuation of the system side, we have: wherein, , is the hth voltage harmonic component measured at the PCC point and the hth current harmonic component measured on the public line, is the system side voltage, , is the hth equivalent harmonic impedance of the user side and the system side; Further calculation gives: wherein, n is a sampling point, and the value range is 1-N, N is the sample number, is the hth equivalent harmonic impedance of the system side at the sampling point n , is the system side voltage at the sampling point n , , is the hth voltage harmonic component and the hth current harmonic component at the sampling point n ; is the harmonic impedance calculation at each sampling point, and the impedance second-order change and the power grid voltage second-order change are introduced into the following formula: wherein, Δ Z u,h n , , Δ 2 Z u,h n , are the hth first-order system side impedance change, the first-order system side voltage change, the second-order system side impedance change and the second-order system side voltage change, respectively; Due to the stability of the power system grid, in the extremely short time interval of adjacent sampling points, Δ 2 Z u,h n , ​​​​​The value of is almost 0, so the value of is almost 0, and thus the value of is almost 0. 2 Z u,h ( n )、 The norm linear combination of and is taken as a constraint condition, and the constraint condition is expressed as: In the formula, is a constraint condition.

[0012] Further, the correlation coefficient between the and is x The Pearson correlation coefficient method is used to calculate the correlation coefficient, and the operation expression of the Pearson correlation coefficient method is: y In the formula, is the i th sample value of x, x is the sample mean of x, i is the i th sample value of y, is the sample mean of y, x is the sample quantity. y Further, the optimization algorithm includes one of a conjugate gradient method, a particle swarm optimization algorithm, a genetic algorithm and a simulated annealing algorithm. i The application also provides a harmonic impedance estimation system based on minimum correlation, which comprises: y A processing unit is used to collect voltage time sequence and current time sequence of a PCC point in a power system, extract voltage harmonic components and current harmonic components by using a fast Fourier transform method, and further extract fast-changing components of the harmonic voltage and the harmonic current. An optimization unit is used to construct a harmonic impedance optimization model based on the fast-changing components of the harmonic current, and obtain harmonic impedance estimation values by using an optimization algorithm under a constraint condition, wherein the correlation refers to the correlation between real parts and imaginary parts of the harmonic current components on both sides of the PCC point.

[0013] Compared with the prior art, the application has the following beneficial effects:

[0014] Compared with the prior art, the application has the following beneficial effects: Compared with the prior art, the application has the following beneficial effects:

[0015] Compared with the prior art, the application has the following beneficial effects: ​​​​​(1) This invention provides a non-intrusive method for estimating harmonic impedance, namely, based on the independence of fast-changing components, using the Pearson correlation coefficient to model the correlation between the real and imaginary parts of the harmonic current on the user side and the system side, and using an optimization algorithm to find the optimal solution, thereby obtaining accurate harmonic impedance on the user side and the system side.

[0016] (2) This invention makes full use of the fast-changing components in the voltage and current signals of the PCC point, extracts the fast-changing components through median filtering, and then uses the Pearson correlation coefficient to model the results. Compared with traditional methods, it can more effectively suppress the interference of background harmonic fluctuations on the estimation results.

[0017] (3) This invention is based entirely on the natural operation data of the power grid and belongs to the “non-intervention method”. It not only avoids the risk of system disturbance, but also has good economy and practicality, and is suitable for long-term, real-time harmonic responsibility monitoring and management.

[0018] (4) The harmonic impedance estimation results obtained by the present invention can be further used to accurately divide the harmonic responsibility on both sides of the PCC point, providing technical support for the safe and stable operation of the power grid. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the method flow of the present invention; Figure 2 This is a schematic diagram of a nonlinear circuit containing a fundamental frequency and an h-th harmonic in the Norton equivalent circuit of an embodiment of the present invention. Figure 3 This is a schematic diagram of the linear circuit under the h-th harmonic in the Norton equivalent circuit of this invention. Figure 4 This is a system structure block diagram of the present invention. Detailed Implementation

[0020] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0021] Example 1 This embodiment provides a harmonic impedance estimation method based on minimum correlation, such as... Figure 1 As shown, the method includes the following steps: Step 1: Collect the voltage and current time series of PCC points in the power system, and use the FFT method to extract the harmonic components of voltage and current.

[0022] In this embodiment, the PCC point is the connection point between the user side and the system side, with the user side and the system side on either side of the PCC point.

[0023] The embodiment is based on wideband detection technology to collect voltage and current time series of PCC point in power system, and uses FFT (Fast Fourier Transform) method to extract voltage and current harmonic components.

[0024] As shown in the figure, Figure 2 In the power system, although both sides of PCC point contain nonlinear elements, by regarding the nonlinear part as a harmonic source, the circuit can be linearized at a certain (h) harmonic, and an equivalent linear circuit as shown in the figure can be obtained. h Figure 3 In this way, the superposition principle and other theorems only applicable to linear circuits are applicable.

[0025] Based on the superposition principle, we have: (1) In the formula, , Vh is the hth harmonic voltage component measured at the PCC point, and Ih is the hth harmonic current component measured on the public line, , Ih,sys and Ih,usr are the hth equivalent harmonic currents of the user side and the system side, , Zh,sys and Zh,usr are the hth equivalent harmonic impedances of the user side and the system side.

[0026] Step 2, further extract the fast-changing components of the harmonic voltage and harmonic current of the PCC point by using the median filter method.

[0027] Step 3, model the correlation between the real and imaginary parts of the harmonic currents of the user side and the system side by using Pearson correlation coefficient, and construct a harmonic impedance optimization model with minimum correlation.

[0028] The present application is based on the following assumptions: it is assumed that the correlation of the fast-changing components of the harmonic currents emitted by the system side and the user side is almost 0. The change of the system side current can be attributed to the fluctuation of the system side load; and the change of the user side current can be attributed to the dynamic operation of the user side load. Therefore, the following equation can be obtained: (2) In the formula, (3) In the above equation, F is the minimum correlation model, the Pearson correlation coefficient between x and y ; Re(x) represents the real part of x , and Im(x) represents the imaginary part of x .​ , respectively represent the fast varying components of the system-side and user-side harmonic currents. The Pearson correlation coefficient is calculated as follows: (4) According to equation (1), the relationship between the system-side and user-side harmonic currents , and their corresponding harmonic impedances Z u , Z c can be obtained as follows: (5) where , represent the fast varying components of the harmonic voltage and current at the PCC point. The fast varying components of the voltage and current of each harmonic can be extracted from the collected voltage and current data by FFT, and then obtained by using the median filtering technique. By solving equation (2) through an optimization algorithm, i.e., equation (2) is the objective function of the optimization algorithm, the system-side and user-side harmonic currents , can be solved, and thus the impedances Z u,h and Z c,h on both sides can be solved by substituting equation (5).

[0029] The following constraints are proposed for the system-side fluctuation: Considering the system-side voltage fluctuation, in combination with Figure 2 , we can obtain (6) From which we can deduce (7) where n is the sampling point, with a value range of 1 to N, and N is the number of samples. In fact, Z u,h , is time-varying, but the fluctuation is very small. To calculate the harmonic impedance value at each sampling point, the second-order change of impedance and the second-order change of grid voltage are introduced into the following equation: (8) (9) where Δ Z u,h ( n ) is the second-order change of the system-side harmonic current, Δ is the second-order change of the user-side harmonic current, Δ 2 Z u,h ( n ) is the second-order change of the system-side harmonic impedance, and Δ respectively, are the first-order system-side impedance variation, the first-order system-side voltage variation, the second-order system-side impedance variation, and the second-order system-side voltage variation.

[0030] Due to the stability of the power grid, in the extremely short time interval between adjacent sampling points, Δ 2 Z u,h The value of Δ n is almost 0, so the linear combination of the norms of Δ 2 Z u,h The norm of Δ n , and equation (2) can be constructed as follows: (10) In addition, in the constraint setting, different dynamic stability assumptions or improved constraint strategies can be introduced according to the actual power grid characteristics to adapt to the needs of power systems of different scales and complexities.

[0031] Step 4: Use an optimization algorithm to optimize under the constraint of the time-varying system-side parameters proposed according to the stability of the power grid.

[0032] In this embodiment, the conjugate gradient method is used for optimization calculation. After obtaining Z u,h , Z c,h , the harmonic responsibility division work can be performed.

[0033] In the optimization process, the conjugate gradient method can be replaced by other optimization algorithms such as particle swarm optimization (PSO), genetic algorithm (GA), and simulated annealing algorithm (SA) according to specific application scenarios to further improve the calculation efficiency and convergence performance.

[0034] Embodiment 2 This embodiment provides a harmonic impedance estimation system based on minimum correlation, as shown in Figure 4 , comprising: A processing unit is configured to collect voltage time series and current time series at a PCC point in a power system, extract voltage harmonic components and current harmonic components of each order using a fast Fourier transform method, and further extract fast-varying components of each harmonic voltage and current. The processing unit comprises: A collection module is configured to collect voltage time series and current time series at a PCC point based on a wideband detection technology; A harmonic component extraction module is configured to extract voltage harmonic components and current harmonic components of each order from the voltage time series and current time series collected by the collection module, and store the relevant data.​​ Fast-varying component extraction module: used for extracting fast-varying components of each voltage harmonic component and each current harmonic component based on a median filtering method and storing the fast-varying components.

[0035] Optimization unit: used for constructing a harmonic impedance optimization model with minimum correlation based on the fast-varying components of each harmonic current, searching for optimization under constraint conditions by using an optimization algorithm, obtaining an estimated value of each harmonic impedance, and storing the estimated value, wherein the correlation refers to correlation between real parts and imaginary parts of each current harmonic component on both sides of the PCC point.

[0036] If the above functions are realized in the form of software function units and sold or used as independent products, the functions can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application or parts of the present application that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0037] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer usable storage media (including but not limited to a disk storage, a CD-ROM, an optical storage, etc.) containing computer usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages, such as an object-oriented programming language Java and an interpreted scripting language JavaScript.

[0038] The present application is described with reference to flowcharts and / or block diagrams according to the methods, devices (systems), and computer program products of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be realized by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices produce a machine that implements the functions described in the flowcharts and / or block diagrams. Figure 1one or more processes and / or blocks Figure 1 an apparatus for performing the functions specified in the flowchart

[0039] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the flowchart Figure 1 one or more processes and / or blocks Figure 1 one or more blocks or steps

[0040] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions that are executed on the computer or other programmable apparatus provide steps for implementing the flowchart Figure 1 one or more processes and / or blocks Figure 1 one or more blocks or steps

[0041] While the preferred embodiments of the application have been described, additional variations and modifications can be made to the embodiments by those skilled in the art once they learn of the basic inventive concepts. Therefore, the appended claims are intended to cover all such additional variations and modifications as fall within the scope of the application.

[0042] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

Claims

1. A method of harmonic impedance estimation based on minimum correlation, characterized in that, The method comprises the following steps: The voltage time sequence and the current time sequence of the PCC point in the power system are collected, the voltage harmonic components and the current harmonic components are extracted by using the fast Fourier transform method, and the fast-changing components of the harmonic voltage and the harmonic current are further extracted; Based on the fast-changing components of the harmonic current, a harmonic impedance optimization model with minimum correlation is constructed, and an optimization algorithm is used to optimize under the constraint condition to obtain the harmonic impedance estimation value, wherein the correlation refers to the correlation between the real part and the imaginary part of the harmonic current components on both sides of the PCC point.

2. The method of claim 1, wherein, The PCC point is the connection point between the user side and the system side, and the user side and the system side are respectively on both sides of the PCC point.

3. The method of claim 1, wherein, The fast-changing components of the harmonic voltage and the harmonic current are extracted by using the median filtering method.

4. The method of claim 1, wherein, In the case that there is a nonlinear element on both sides of the PCC point, the nonlinear element is equivalent to a harmonic source at the harmonic frequency, the remaining elements are regarded as linear impedance, and the voltage harmonic components and the current harmonic components are calculated based on the superposition principle.

5. The method of claim 4, wherein, The hth voltage harmonic component and the hth current harmonic component are respectively represented as: wherein , is the hth voltage harmonic component measured at the PCC point and the hth current harmonic component measured on the public line, , is the hth equivalent harmonic current at the user side and the system side, , is the hth equivalent harmonic impedance at the user side and the system side.

6. The method of claim 5, wherein, fast varying components of hth harmonic currents on the user side and on the system side , the relationship between the hth equivalent harmonic impedance on the user side and on the system side corresponding to it , satisfies: wherein , is the fast varying component of the hth harmonic voltage, harmonic current at the PCC point.

7. The method of claim 1, wherein, The harmonic impedance optimization model with minimum correlation includes an objective function and corresponding constraint conditions, and the construction steps of the objective function include: Assuming that the fast-changing components of the harmonic current on the system side and the user side have a correlation close to 0, a target function is designed, and the expression of the hth target function is: Wherein: wherein F is a target function of hth order, denotes x the correlation coefficient between y and , is a fast varying component of the hth harmonic current on the user side and on the system side, Re (Re{Xh}) denotes x the real part of x , Im (Im{Xh}) denotes x the imaginary part of x ; The design steps of the constraint condition include: Considering the voltage fluctuation of the system side, the following can be obtained: wherein , is the hth voltage harmonic component measured at the PCC point and the hth current harmonic component measured on the public line, is the system-side voltage, , is the hth equivalent harmonic impedance between the user-side and the system-side; Further calculation is carried out as follows: wherein n is the sampling point, and the value range is 1 ~ N, N is the number of samples, is the sampling point n is the hth equivalent harmonic impedance at the system side, is the sampling point n is the voltage at the system side, , is the sampling point n is the hth voltage harmonic component and the hth current harmonic component; In order to calculate the harmonic impedance at each sampling point, the impedance second-order change and the grid voltage second-order change are introduced into the following formula: In the formula, Δ Z u,h ( n )、 , Δ 2 Z u,h ( n )、 respectively are a first-order system side impedance variation, a first-order system side voltage variation, a second-order system side impedance variation, and a second-order system side voltage variation. Due to the stability of the power system grid, the values of Δ 2 Z u,h ( n ), are almost 0 in the very short time interval between adjacent sampling points, so the norm linear combination of Δ 2 Z u,h ( n ), is taken as a constraint condition, which is expressed as: In the formula, are the constraint conditions.

8. The method of claim 7, wherein, The x correlation coefficient between y correlation coefficient between The Pearson correlation coefficient method is used for calculation, and the operation expression of the Pearson correlation coefficient method is: wherein is x the i sample value, is x the sample mean, is y the i sample value, is y the sample mean, is the number of samples.

9. The method of claim 1, wherein, The optimization algorithm includes one of the conjugate gradient method, the particle swarm optimization algorithm, the genetic algorithm and the simulated annealing algorithm.

10. A minimum correlation based harmonic impedance estimation system, characterized by, It comprises: The processing unit is used for collecting the voltage time sequence and the current time sequence of the PCC point in the power system, extracting the voltage harmonic components and the current harmonic components by using the fast Fourier transform method, and further extracting the fast-changing components of the harmonic voltage and the harmonic current; The optimization unit is used for constructing a harmonic impedance optimization model with minimum correlation based on the fast-changing components of the harmonic current, optimizing under the constraint condition by using an optimization algorithm, and obtaining the harmonic impedance estimation value, wherein the correlation refers to the correlation between the real part and the imaginary part of the harmonic current components on both sides of the PCC point.

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