AC transmission line state estimation fault phase selection method, system, device and medium

Abstract

The present application relates to the technical field of power system relay protection, and particularly relates to an alternating current transmission line state estimation fault phase selection method, system, device and medium, comprising mapping three-phase voltage and current components in a three-phase alternating current transmission line, which are coupled with each other, from a phase domain to a mode domain space, to obtain mode domain voltage and current components on a new energy side and a power grid side; constructing a system measurement equation based on the mode domain voltage and current components to obtain an optimal estimation value; calculating a residual normalized sum of squares according to the optimal estimation value, and screening out an in-zone fault line by comparing the residual normalized sum of squares with a chi-square distribution threshold; performing secondary decoupling on the same fault current data of the in-zone fault line, and determining a fault phase according to a residual normalized sum of squares ratio of each mode domain component under a multi-mode phase-mode transformation combination. The state estimation method combining phase-mode transformation and the Bergeron model realizes fast and accurate phase selection of alternating current transmission line faults, and effectively improves the fault identification accuracy.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power system relay protection technology, and in particular to an alternating current transmission line state estimation fault phase selection method, system, device and medium. BACKGROUND

[0002] Under the background of large-scale new energy access to power systems, the protection of alternating current transmission lines is facing unprecedented challenges. With the increasing generation capacity of wind power, photovoltaic and other new energy stations year by year, the structural characteristics of power systems have changed significantly. The traditional alternating current frequency quantity protection gradually exposes many adaptability problems when dealing with large-scale high proportion of new energy access. Its fault characteristics are significantly different from synchronous generators, which increases the risk of protection misoperation or misoperation. A large number of power electronic devices in new energy power sources are extremely sensitive to overvoltage and overcurrent, and have weak ability to withstand fault impact, so current limiting measures are often taken. This not only weakens the sensitivity of overcurrent protection and differential protection, but also makes the fault response process more complex and uncertain.

[0003] In traditional power systems, the protection of alternating current transmission lines mainly relies on classic alternating current frequency quantity protection, such as longitudinal differential protection and distance protection. However, with the increasing access capacity of new energy, these classic protection principles still have adaptability problems in new energy power systems due to the characteristics of traditional synchronous machines, which cannot guarantee the safe and stable operation of new energy station transmission lines. Another type is the protection of new principles based on fault transient characteristics. The protection of new principles based on fault transient characteristics is divided into single-ended protection principle and double-ended protection principle. Although the action speed is fast, there are still many problems in actual application, such as the protection dead zone at the voltage zero point of the protection scheme based on traveling wave characteristics, the high requirement for protection sampling rate, the influence of noise interference and transition resistance, etc.

[0004] The alternating current transmission line state estimation protection principle is a new protection technology with the advantages of fast action speed, strong reliability and no influence of external system control, which provides a new solution to the performance degradation problem of traditional protection. However, the fault phase selection function of the current alternating line state estimation protection can only identify the fault phase of single-phase ground fault, and it is difficult to accurately determine the fault phase of two-phase short-circuit fault, two-phase short-circuit ground fault and three-phase fault, which brings difficulties to fault isolation and fault analysis. Therefore, the existing technology has many deficiencies in dealing with the protection needs of new energy station alternating current transmission lines, especially in the fault phase selection function, which seriously restricts the overall performance of the protection system. Therefore, it is urgent to provide a fault phase selection method that can effectively solve the defects of the existing technology to improve the reliability of alternating current transmission line state estimation protection. SUMMARY

[0005] To solve the above technical problems, the application provides an AC power transmission line state estimation fault phase selection method, system, device and medium.

[0006] In a first aspect, the application provides an AC power transmission line state estimation fault phase selection method, which comprises the following steps:

[0007] The three-phase voltage and current components in the three-phase AC power transmission line are mapped from the phase domain to the modal domain space by using a phase-mode transformation matrix to obtain modal domain voltage and current components on the new energy side and the power grid side.

[0008] Based on the Bergeron transmission line model, the uniform lossy transmission line is equivalent to two lossless transmission lines in series with four concentrated resistors, and the modal domain voltage and current components are taken as inputs to construct system measurement equations through state variables.

[0009] The system measurement equations are solved by using a weighted least squares estimation model to obtain optimal estimates of the state variables.

[0010] According to the optimal estimates, the residual normalized sum of squares of the measurement estimates and the actual measurement values in the modal domain is calculated, and the intra-zone fault line is screened out by comparing the residual normalized sum of squares with the chi-square distribution threshold.

[0011] The same fault current data of the intra-zone fault line is decoupled twice by using a multi-mode phase-mode transformation combination to generate the residual normalized sum of squares of each modal component under the multi-mode phase-mode transformation combination.

[0012] According to the residual normalized sum of squares ratio of each modal component under the multi-mode phase-mode transformation combination, the fault phase is determined, and the corresponding trip command is generated according to the fault phase to control the circuit breaker to act to complete fault isolation.

[0013] In further embodiments, the step of mapping the three-phase voltage and current components in the three-phase AC power transmission line from the phase domain to the modal domain space by using a phase-mode transformation matrix to obtain modal domain voltage and current components on the new energy side and the power grid side comprises:

[0014] Real-time acquisition of three-phase voltage instantaneous sampling values and three-phase current instantaneous sampling values on both sides of the AC power transmission line is performed to obtain three-phase voltage and current components; the two sides of the AC power transmission line include the new energy side and the power grid side of the AC power transmission line.

[0015] The three-phase voltage and current components are mapped from the phase domain to the modal domain space to obtain modal domain voltage and current components on the new energy side and the power grid side; the modal domain voltage and current components include zero-mode components, one-mode components and two-mode components.

[0016] In a further implementation, the step of constructing the system measurement equations based on the Berylone transmission line model, which equates a uniform lossy transmission line to two lossless transmission lines connected in series with four lumped resistors, and using the modal domain voltage and current components as inputs, includes:

[0017] Obtain AC transmission line parameters; the AC transmission line parameters include resistance per unit length, inductance per unit length, capacitance per unit length, and total line length;

[0018] Based on the AC transmission line parameters, the uniform lossy AC transmission line is equivalent to two lossless AC transmission lines connected in series with four lumped resistors using the Berylone transmission line model, thus obtaining the equivalent lossless transmission line model.

[0019] Based on the lossless transmission line model after equivalent transformation, the key parameters of the lossless transmission line are calculated; the key parameters of the lossless transmission line include characteristic impedance, propagation time, and attenuation coefficient.

[0020] Based on the key parameters of the lossless transmission line and the voltage and current components of the modal domain, a dynamic voltage-current relationship equation between the new energy side and the grid side of the AC transmission line is established.

[0021] The estimated values ​​of the modal domain voltage and modal domain current on both sides of the AC transmission line at the current moment are defined as state variables, and the dynamic voltage-current relationship equation is combined with the state variables to construct the system measurement equation.

[0022] In a further implementation, the step of solving the system measurement equations using a weighted least squares estimation model to obtain the optimal estimates of the state variables includes:

[0023] A residual vector is constructed based on the difference between the actual measured values ​​in the system measurement equations and the virtual measured values ​​estimated based on the current state variables; the actual measured values ​​are the modal domain voltage and current components of the new energy side and the grid side.

[0024] With minimizing the weighted sum of squares of the residual vector as the optimization objective, a residual weighted sum of squares minimization objective function is constructed;

[0025] The optimal estimated values ​​of the state variables are obtained by using the Jacobian matrix to correlate the state variables with the actual measured values, and by using the weighted least squares method to solve the objective function that minimizes the weighted sum of squares of the residuals; the actual measured values ​​include real measured values ​​and virtual measured values.

[0026] In a further implementation, the step of calculating the normalized sum of squares of the residuals between the measured estimated value and the actual measured value in the modulus domain based on the optimal estimated value, and screening out faulty lines in the area by comparing the normalized sum of squares of the residuals with the chi-square distribution threshold, includes:

[0027] inputting the optimal estimation value into a system measurement equation, calculating a measurement estimation value in a modal domain, and calculating a residual estimation between the measurement estimation value and an actual measurement value;

[0028] normalizing the residual estimation to obtain a normalized residual, and calculating a sum of squares of the normalized residual according to a total number of the actual measurement values to obtain a residual normalized sum of squares;

[0029] determining a degree of freedom according to a difference between the total number of the actual measurement values and a number of state variables in the system measurement equation, and querying a chi-square distribution threshold from a chi-square distribution table using the degree of freedom;

[0030] comparing the calculated residual normalized sum of squares with the chi-square distribution threshold, and if the residual normalized sum of squares is greater than the chi-square distribution threshold, judging that an in-zone fault occurs in the line, and screening out an in-zone fault line; otherwise, the line is in normal operation.

[0031] In further embodiments, the in-zone fault includes an in-zone single-phase ground fault, an in-zone two-phase short-circuit fault, and an in-zone three-phase ground fault.

[0032] In further embodiments, the multi-mode phase-mode transformation combination includes a standard phase sequence transformation, a cyclic phase sequence transformation, and an inverse phase sequence transformation.

[0033] In a second aspect, the present application provides an alternating current transmission line state estimation fault selection system, which comprises:

[0034] a phase-mode mapping module configured to map three-phase voltage and current components coupled to each other in a three-phase alternating current transmission line from a phase domain to a modal domain space using a phase-mode transformation matrix to obtain modal domain voltage and current components on a new energy side and a power grid side;

[0035] a measurement construction module configured to equivalently convert a uniform lossy transmission line into two lossless transmission lines connected in series and four lumped resistors based on a Bergeron transmission line model, and to construct a system measurement equation by state variables using the modal domain voltage and current components as inputs;

[0036] an optimal estimation module configured to solve the system measurement equation using a weighted least square estimation model to obtain an optimal estimation value of the state variables;

[0037] a fault analysis module configured to calculate a residual normalized sum of squares of the measurement estimation value in the modal domain and the actual measurement value according to the optimal estimation value, and to screen out an in-zone fault line by comparing the residual normalized sum of squares with a chi-square distribution threshold;

[0038] a secondary decoupling module, configured to perform secondary decoupling on the same fault current data of the fault line in the area by using a multi-mode phase-mode transformation combination, to generate a residual normalized square sum of each modal component under the multi-mode phase-mode transformation combination;

[0039] a fault selection module, configured to determine a fault phase according to a residual normalized square sum ratio of each modal component under the multi-mode phase-mode transformation combination, and generate a corresponding trip instruction according to the fault phase to control the circuit breaker to act to complete fault isolation.

[0040] In further embodiments, the phase-mode mapping module is specifically configured to:

[0041] real-time acquisition of three-phase voltage instantaneous sampling values and three-phase current instantaneous sampling values on both sides of the AC power transmission line to obtain three-phase voltage and current components; the two sides of the AC power transmission line include a new energy side and a power grid side of the AC power transmission line;

[0042] mapping of the three-phase voltage and current components from a phase domain to a modal domain space to obtain modal voltage and current components of the new energy side and the power grid side; the modal voltage and current components include zero-mode components, one-mode components, and two-mode components.

[0043] In further embodiments, the measurement construction module is specifically configured to:

[0044] acquisition of AC power transmission line parameters; the AC power transmission line parameters include unit length resistance, unit length inductance, unit length capacitance, and total length of the line;

[0045] based on the AC power transmission line parameters, equivalent conversion of a uniform lossy AC power transmission line into a form of two lossless AC transmission lines in series with four lumped resistors by using a Bergeron transmission line model to obtain an equivalent converted lossless transmission line model;

[0046] calculation of lossless transmission line key parameters from the equivalent converted lossless transmission line model; the lossless transmission line key parameters include characteristic impedance, propagation time, and attenuation coefficient;

[0047] establishment of a dynamic voltage-current relationship equation between the new energy side and the power grid side of the AC power transmission line according to the lossless transmission line key parameters and the modal voltage and current components;

[0048] definition of modal voltage and current estimation values at the current moment on both sides of the AC power transmission line as state variables, and combination of the dynamic voltage-current relationship equation and the state variables to construct a system measurement equation.

[0049] In further embodiments, the optimal estimation module is specifically configured to:

[0050] A residual error vector is constructed according to a difference between a real measurement value in a system measurement equation and a virtual measurement value estimated based on a current state variable; the real measurement value is a voltage and current component in a modulus domain of a new energy side and a power grid side;

[0051] A residual error weighted sum of squares minimization objective function is constructed with a weighted sum of squares of the residual error vector being minimized as an optimization objective;

[0052] An optimal estimation value of the state variable is obtained by using a weighted least square method to solve the residual error weighted sum of squares minimization objective function, with a Jacobian matrix being used to associate the state variable with an actual measurement value; the actual measurement value includes the real measurement value and the virtual measurement value.

[0053] In further embodiments, the fault analysis module is specifically configured to:

[0054] The optimal estimation value is input into the system measurement equation to calculate a measurement estimation value in the modulus domain and to calculate a residual error estimation between the measurement estimation value and the actual measurement value;

[0055] The residual error estimation is normalized to obtain a normalized residual error, and a sum of squares of the normalized residual error is calculated according to a total number of the actual measurement values to obtain a residual error normalized sum of squares;

[0056] A degree of freedom is determined according to a difference between the total number of the actual measurement values and a number of the state variables in the system measurement equation, and a chi-square distribution threshold is queried from a chi-square distribution table by using the degree of freedom;

[0057] The calculated residual error normalized sum of squares is compared with the chi-square distribution threshold, and if the residual error normalized sum of squares is greater than the chi-square distribution threshold, it is determined that an in-zone fault occurs in the line, and an in-zone fault line is screened out; otherwise, the line is in normal operation.

[0058] In further embodiments, the in-zone fault includes an in-zone single-phase ground fault, an in-zone two-phase short-circuit fault and an in-zone three-phase ground fault.

[0059] In further embodiments, the multi-mode phase-mode transformation combination includes a standard phase sequence transformation, a cyclic phase sequence transformation and an inverse phase sequence transformation.

[0060] In a third aspect, the present application further provides a computer device including a processor and a memory, the processor being connected with the memory, the memory being used to store a computer program, and the processor being used to execute the computer program stored in the memory to enable the computer device to execute steps of the above method.

[0061] In a fourth aspect, the present application further provides a computer readable storage medium, wherein a computer program is stored in the computer readable storage medium, and the computer program is executed by a processor to implement the steps of the above method.

[0062] The present application provides an alternating current transmission line state estimation fault phase selection method, system, device and medium, the method maps the three-phase voltage and current components coupled with each other in the three-phase alternating current transmission line from the phase domain to the mode domain space through the phase-mode transformation matrix, obtains the mode domain voltage and current components of the new energy side and the power grid side; based on the Bergeron transmission line model, the uniform lossy transmission line is equivalent to two lossless transmission lines in series with four concentrated resistors, and the mode domain voltage and current components are input, and the system measurement equation is constructed through the state variable; the optimal estimation value of the state variable is obtained by solving the system measurement equation by using the weighted least square estimation model; according to the optimal estimation value, the residual normalized sum of squares of the measurement estimation value and the actual measurement value in the mode domain is calculated, and the intra-zone fault line is screened out by comparing the residual normalized sum of squares with the chi-square distribution threshold; the same fault current data of the intra-zone fault line is decoupled again by using a multi-mode phase-mode transformation combination, and the residual normalized sum of squares of each mode domain component under the multi-mode phase-mode transformation combination is generated; according to the residual normalized sum of squares ratio of each mode domain component under the multi-mode phase-mode transformation combination, the fault phase is determined, and the corresponding trip instruction is generated according to the fault phase to control the circuit breaker to act to complete fault isolation. Compared with the prior art, the method realizes rapid and accurate phase selection of alternating current transmission line fault by combining the state estimation method of phase-mode transformation and Bergeron model, and automatically generates a trip instruction to isolate the fault area, effectively improves the rapid detection and accurate positioning of the intra-zone fault of the alternating current transmission line, and ensures the stable operation of the power grid. BRIEF DESCRIPTION OF DRAWINGS

[0063] Figure 1 is the flowchart of the alternating current transmission line state estimation fault phase selection method provided by the embodiment of the present application;

[0064] Figure 2 is the schematic diagram of the Bergeron transmission line model provided by the embodiment of the present application;

[0065] Figure 3 is the process block diagram of the alternating current transmission line state estimation protection fault phase selection provided by the embodiment of the present application;

[0066] Figure 4 is the topology example diagram of the new energy through flexible DC transmission system provided by the embodiment of the present application;

[0067] Figure 5 is the system block diagram of the alternating current transmission line state estimation fault phase selection provided by the embodiment of the present application;

[0068] Figure 6Fig. 1 is a structural schematic diagram of a computer device according to an embodiment of the present application.

[0069] Label explanation: 101, phase-mode mapping module; 102, measurement construction module; 103, optimal estimation module; 104, fault analysis module; 105, secondary decoupling module; 106, fault phase selection module. DETAILED DESCRIPTION

[0070] The embodiments of the present application are specifically described below with reference to the drawings. The embodiments are given only for illustrative purposes and cannot be understood as limiting the present application. The accompanying drawings are only for reference and illustration and do not constitute a limitation on the scope of patent protection of the present application, because many changes can be made to the present application without departing from the spirit and scope of the present application.

[0071] Reference Figure 1 The embodiments of the present application provide a fault phase selection method for state estimation of an AC transmission line, as shown in the accompanying drawings, the method comprises the following steps: Figure 1

[0072] S1. Using a phase-mode transformation matrix to map three-phase voltage and current components coupled with each other in a three-phase AC transmission line from a phase domain to a mode domain space to obtain mode domain voltage and current components on a new energy side and a power grid side.

[0073] In some embodiments, the step of using a phase-mode transformation matrix to map three-phase voltage and current components coupled with each other in a three-phase AC transmission line from a phase domain to a mode domain space to obtain mode domain voltage and current components on a new energy side and a power grid side comprises:

[0074] Real-time acquisition of three-phase voltage instantaneous sampling values and three-phase current instantaneous sampling values on both sides of an AC transmission line to obtain three-phase voltage and current components; the two sides of the AC transmission line include a new energy side of the AC transmission line and a power grid side of the AC transmission line;

[0075] Mapping the three-phase voltage and current components from the phase domain to the mode domain space to obtain mode domain voltage and current components on the new energy side and the power grid side; the mode domain voltage and current components include zero-mode components, one-mode components, and two-mode components.

[0076] ​Specifically, the embodiment installs voltage transformers and current transformers at the new energy side and the grid side of the alternating current transmission line respectively, and ensures that the sampling devices such as the voltage transformers and the current transformers have high precision and real-time performance, so as to accurately capture the instantaneous changes of the voltage and the current, and then start the sampling devices in real time to start collecting the three-phase voltage instantaneous sampling values and the three-phase current instantaneous sampling values at the new energy side and the grid side, and pre-process the three-phase voltage instantaneous sampling values and the three-phase current instantaneous sampling values, such as denoising and filtering, so as to improve the accuracy of the data. Meanwhile, the embodiment constructs a Karenbauer transformation matrix according to the definition of Karenbauer transformation, and the Karenbauer transformation matrix is a 3x3 matrix, which is used to convert the three-phase voltage and current components from the phase domain to the modal domain, and the specific form of the Karenbauer transformation matrix S is:

[0077]

[0078] For the three-phase voltage instantaneous sampling values and the three-phase current instantaneous sampling values at the new energy side and the grid side, the embodiment respectively adopts the Karenbauer transformation matrix S to perform transformation, so as to obtain the zero-mode component, the one-mode component and the two-mode component at the new energy side and the grid side. These modal components are independent of each other, and are no longer coupled with each other like the phase domain components. The specific transformation formula is:

[0079]

[0080]

[0081] In the formula, S is the Karenbauer transformation matrix; is the modal domain current zero-mode component at the new energy side or the grid side; is the modal domain current one-mode component at the new energy side or the grid side; is the modal domain current two-mode component at the new energy side or the grid side; is the A-phase current instantaneous sampling value at the new energy side or the grid side; is the B-phase current instantaneous sampling value at the new energy side or the grid side; is the C-phase current instantaneous sampling value at the new energy side or the grid side; is the modal domain voltage zero-mode component at the new energy side or the grid side; is the modal domain voltage one-mode component at the new energy side or the grid side; is the modal domain voltage two-mode component at the new energy side or the grid side; is the A-phase voltage instantaneous sampling value at the new energy side or the grid side; is the B-phase voltage instantaneous sampling value at the new energy side or the grid side; is the C-phase voltage instantaneous sampling value at the new energy side or the grid side; The names of the new energy side and the grid side of the alternating current line respectively; it should be noted that the subsequent analysis indicates the modulus domain without special instructions, and the modulus of 0, 1 or 2 is no longer explicitly indicated.

[0082] S2. Based on the Bergeron transmission line model, the uniform lossy transmission line is equivalent to two lossless transmission lines in series with four concentrated resistors, and the modulus domain voltage and current components are taken as inputs, and the system measurement equation is constructed by state variables.

[0083] In some embodiments, the step of equivalent uniform lossy transmission line to two lossless transmission lines in series with four concentrated resistors based on the Bergeron transmission line model, and taking the modulus domain voltage and current components as inputs, and constructing the system measurement equation by state variables includes:

[0084] Obtaining the parameters of the alternating current transmission line; the parameters of the alternating current transmission line include the unit length resistance, the unit length inductance, the unit length capacitance and the total length of the line;

[0085] Based on the parameters of the alternating current transmission line, the Bergeron transmission line model is used to equivalent the uniform lossy alternating current transmission line to two lossless alternating current transmission lines in series with four concentrated resistors, and the equivalent conversion of the lossless transmission line model is obtained;

[0086] According to the equivalent conversion of the lossless transmission line model, the key parameters of the lossless transmission line are calculated; the key parameters of the lossless transmission line include characteristic impedance, propagation time and attenuation coefficient;

[0087] According to the key parameters of the lossless transmission line and the modulus domain voltage and current components, the dynamic voltage-current relationship equation of the new energy side and the grid side of the alternating current transmission line is established;

[0088] The modulus domain voltage and current estimation values of the two sides of the alternating current transmission line at the current time are defined as state variables, and the dynamic voltage-current relationship equation and the state variables are combined to construct the system measurement equation.

[0089] Specifically, for a given alternating current transmission line, the parameters of the alternating current transmission line can be obtained from the power system database or by field measurement, and the parameters of the alternating current transmission line include the unit length resistance , the unit length inductance , the unit length capacitance and the total length of the line These AC transmission line parameters reflect the electrical characteristics and physical structure of the line. The Berylon transmission line model is an equivalent method for handling lossy transmission lines. It treats a lossy transmission line as a combination of a lossless transmission line and a lumped resistor. In this embodiment, based on the definition of the Berylon model and the AC transmission line parameters, the uniformly lossy AC transmission line is equivalently transformed according to the Berylon model to construct an equivalent lossless transmission line model. Two lossless transmission lines are connected to four lumped resistors according to the structure of the Berylon model to form an equivalent transmission line model. The two lossless transmission lines are located on both sides of the line, and a lumped resistor is connected in series at both ends of each transmission line to simulate the lossy characteristics of the line. Thus, the entire line is equivalent to two lossless transmission lines connected in series with four lumped resistors. The resistance value of the lumped resistors is determined by the line parameters and length. That is, the resistance connected in series at both ends of each lossless transmission line is the product of the resistance per unit length of the line and half the length of the line. In this embodiment, the length of each lossless transmission line is half the original line length. Beryllon transmission line model, such as Figure 2 As shown, in Figure 2 In the diagram, the r-side represents the renewable energy side of the AC transmission line, and the g-side represents the grid side of the AC transmission line.

[0090] This embodiment calculates the equivalent characteristic impedance, propagation time, and attenuation coefficient of a lossless transmission line based on the equivalent transformation model. Specifically, the characteristic impedance of a lossless transmission line is one of its important parameters, reflecting the transmission characteristics of the line. This embodiment calculates the equivalent characteristic impedance, propagation time, and attenuation coefficient based on the inductance per unit length of the line. and capacitance per unit length Equivalent characteristic impedance It can be calculated using the following formula:

[0091]

[0092] The characteristic impedance formula states that it is proportional to the square root of the inductance and capacitance per unit length. It reflects the influence of the inductive and capacitive characteristics of the line on the transmission characteristics, while also considering the propagation time. The propagation time represents the time required for an electromagnetic wave to propagate through a transmission line. It depends on the length of the line and the speed of signal propagation. It can be calculated using the following formula:

[0093]

[0094] In the formula, The total length of the line is given by the propagation time, which reflects the delay of the signal in the transmission line and is of great significance for analyzing the dynamic response and time-domain characteristics of the line.

[0095] The attenuation coefficient reflects the attenuation effect of line loss on traveling waves. It can be calculated by the following formula:

[0096]

[0097] In the modal domain (i.e. positive sequence, negative sequence or zero sequence component), the embodiment considers the characteristics of the lossless transmission line, and establishes a dynamic voltage-current relationship equation of the new energy side and the grid side by using the characteristic impedance, propagation time and modal domain voltage and current components of the lossless transmission line. The equation describes the dynamic relationship between the voltages and currents on both sides of the line, which considers the propagation delay of the signal and the transmission characteristics of the line. Therefore, the equation contains coupling terms of the current time and the historical time (delay ), and the specific form is as follows:

[0098]

[0099] In the formula, is the current instantaneous sampling value of the new energy side; is the equivalent characteristic impedance; is the voltage instantaneous sampling value of the new energy side; is the attenuation coefficient; is the voltage instantaneous sampling value of the grid side; t is time; is the traveling wave propagation time; is the current instantaneous sampling value of the grid side; is the response of the current at the other end after time .

[0100] The dynamic voltage-current relationship equation shown in the above equation can be used to conveniently calculate the voltages and currents on both sides of the line. In the modeling process, the influence of the distributed capacitance is considered, the calculation error is reduced, and the equation can be used for the research of dynamic state estimation protection. Since the line is equivalent to two lossless transmission lines in series and four concentrated resistances in the embodiment, the influence of the resistances needs to be considered in the above equation, i.e. the voltage drop after adding resistances at both ends, and the modal domain voltage estimation value and the modal domain current estimation value on both sides of the alternating current transmission line at the current time are defined as state variables. These state variables reflect the estimation state of the voltages and currents on both sides of the line, are key variables in state estimation and fault detection, and the historical values are defined as the measurement values and state variables before the delay The dynamic voltage-current relationship equation and the state variables are combined to construct a system measurement equation, which relates the modal domain voltage and current values obtained by measurement to the state variables, and is used to describe the relationship between the system state variables and the measurement values, and the specific form is as follows:

[0101]

[0102] The above formula can be derived in the following form:

[0103]

[0104] In the formula, This is the estimated modal voltage on the renewable energy side of the AC transmission line at the current time t. In order to be in The estimated modal voltage on the grid side of the AC transmission line before the specified time, i.e., the delay. The state variables before; is a column vector of measured values, containing both real and virtual measured values; H is the Jacobian matrix; A column vector of state variables; Let be the column vector of historical values; e is the phasor of measurement error, and it is assumed that the measurement error follows a normal distribution.

[0105] This embodiment simplifies complex lossy lines into a combination of lossless lines and lumped resistors using the Berylon model, and decouples three-phase quantities using the Karenbauer transform. Finally, it constructs system measurement equations based on state variables and historical data, providing a foundation for subsequent state estimation and protection criteria. In this embodiment, the system measurement equations contain three types of information: measured values, state variables, and historical values. Measured values ​​include real and virtual measured values. Real measured values ​​are data directly measured by voltage and current transformers; virtual measured values ​​represent the physical laws satisfied by a healthy line, and are usually represented by 0 in practice. State variables represent quantities in the system measurement equations that are difficult to measure directly and change over time. These state variables include the estimated current and voltage values ​​on both sides of the line at the current moment (denoted as...). , , , ,in, This is the estimated value of the modal current on the renewable energy side of the AC transmission line at the current time t. This represents the estimated modal current on the grid side of the AC transmission line at the current time t; historical values ​​include the measured historical values ​​of voltage and current on both sides of the line, as well as the historical values ​​of state variables.

[0106] S3. Solve the system measurement equations using a weighted least squares estimation model to obtain the optimal estimates of the state variables.

[0107] In some implementations, the step of solving the system measurement equations using a weighted least squares estimation model to obtain the optimal estimates of the state variables includes:

[0108] A residual vector is constructed based on the difference between the actual measured values ​​in the system measurement equations and the virtual measured values ​​estimated based on the current state variables; the actual measured values ​​are the modal domain voltage and current components of the new energy side and the grid side.

[0109] A residual weighted sum of squares minimization objective function is constructed with a weighted sum of squares of the residuals as an optimization objective;

[0110] The optimal estimation value of the state variable is obtained by using the weighted least squares method to solve the residual weighted sum of squares minimization objective function by using the Jacobian matrix to associate the state variable with the actual measurement value; the actual measurement value includes the real measurement value and the virtual measurement value.

[0111] Specifically, the system measurement equation can be used to determine that the number of measurement values is greater than the number of state variables, which indicates that the system is observable. Based on this determination, the optimal estimation value of the state variable can be further solved by using the dynamic state estimation method and by using mathematical methods. The weighted least squares (WLS) estimation model is selected to solve the state estimation problem, and the model is constructed by taking the weighted sum of squares of the residuals (i.e., the difference between the measurement value and the measurement estimation value) as the criterion function:

[0112]

[0113] When the line parameters are known and the measurement function is in a linear form, the Jacobian matrix H is a constant matrix. Under this condition, considering that the errors of different measurement values are different, a weight matrix W is introduced to construct the objective function. In order to solve the minimum value of the objective function, the Jacobian matrix is used to associate the state variable and the actual measurement value. In the iterative solving process, the nonlinear equation is linearized near its current estimation value, and the minimum value of the objective function is iteratively solved. In each iteration, the estimation value of the state variable is updated. When the value of the objective function converges to a small enough value, the current estimation value of the state variable is considered as the optimal estimation value. The optimal estimation value is used for the voltage and current estimation value closest to the actual line state. The optimal estimation value of the state variable can be calculated by the following formula:

[0114]

[0115] As shown in the following formula, after obtaining the optimal estimation value of the state variable, the optimal estimation value can be substituted into the system measurement equation to obtain the estimation value of the measurement and the normalized sum of squares of the residuals: Figure 3

[0116]

[0117]

[0118] ​

[0119] J = (Y - WH)T(W - H) where J is a residual weighted sum of squares minimization objective function; W is a weight matrix; Y is a residual vector; H is an optimal estimate; Y is a measurement estimate; S is a residual normalized sum of squares; p is a total number of measurement estimates in the system measurement equation; num is a measurement estimate index in the system measurement equation; Ynum is the numth measurement estimate; Ynum is the numth measurement value; S is a measurement standard deviation.

[0120] The elements of the Jacobian matrix in the embodiment are partial derivatives of the measurement values in the system measurement equation with respect to the state variables, which reflect the sensitivity of the measurement values to the state variables. By calculating the Jacobian matrix, the nonlinear relationship between the state variables and the measurement values can be linearized, which facilitates subsequent optimization solving.

[0121] S4. According to the optimal estimate, a residual normalized sum of squares of the measurement estimates and the actual measurement values in the modulus field is calculated, and a line fault line in the area is screened out by comparing the residual normalized sum of squares with a chi-square distribution threshold.

[0122] In some embodiments, the step of calculating the residual normalized sum of squares of the measurement estimates and the actual measurement values in the modulus field according to the optimal estimate, and screening out the line fault line in the area by comparing the residual normalized sum of squares with the chi-square distribution threshold comprises:

[0123] The optimal estimate is input into the system measurement equation, the measurement estimates in the modulus field are calculated, and a residual estimate between the measurement estimates and the actual measurement values is calculated;

[0124] The residual estimate is normalized to obtain a normalized residual, and a sum of squares of the normalized residual is calculated according to a total number of the actual measurement values to obtain a residual normalized sum of squares;

[0125] A degree of freedom is determined according to a difference between the total number of the actual measurement values and the number of state variables in the system measurement equation, and a chi-square distribution threshold is queried from a chi-square distribution table using the degree of freedom;

[0126] The calculated residual normalized sum of squares is compared with the chi-square distribution threshold, if the residual normalized sum of squares is greater than the chi-square distribution threshold, it is judged that a line fault in the area occurs, and the line fault line in the area is screened out; otherwise, the line is in normal operation.

[0127] The embodiment can effectively determine whether the line has an internal fault by calculating the residual normalized sum of squares. Specifically, when the protected line is in a normal state (i.e., the deviation between the measured value and the measured estimated value is small, and the mathematical model is highly matched with the physical line), the residual normalized sum of squares conforms to the chi-square distribution. Otherwise, if an internal fault occurs in the protected line, the deviation between the measured value and the measured estimated value is significantly increased, and the mathematical model is no longer matched with the physical line. At this time, the residual normalized sum of squares deviates from the chi-square distribution and no longer conforms to the chi-square distribution. The probability density function of the chi-square distribution is shown in the following formula:

[0128]

[0129] In the formula, P(F) is a confidence level; is the residual normalized sum of squares; is a chi-square distribution threshold in a chi-square distribution table, which is obtained by querying the chi-square distribution table according to the degree of freedom F; is a probability density function of the chi-square distribution; s is an integral variable; and F is a degree of freedom of the chi-square distribution; is the residual normalized sum of squares is greater than the chi-square threshold is a confidence level.

[0130] When the system measurement equation is determined, the degree of freedom F of the chi-square distribution is determined. The confidence level P(F) is an important index for measuring the matching degree of the mathematical model and the physical line and further reflects the characteristics of the chi-square distribution. As can be seen from the probability density curve of the chi-square distribution, when the chi-square distribution value is large, the corresponding probability is low. In the embodiment, the confidence level can be expressed in the form of the probability density function of the chi-square distribution by integrating the probability density function. In the formula, the chi-square distribution threshold is obtained by querying the chi-square distribution table according to the degree of freedom F. The confidence level represents the probability that the residual normalized sum of squares is greater than the threshold. Therefore, when the residual normalized sum of squares is large, the confidence level is low, which indicates that the value conforms to the chi-square distribution with a small probability, that is, the matching degree of the mathematical model and the physical line is low, indicating that the protected line may have an internal fault. Conversely, when the residual normalized sum of squares is small, the confidence level is high, indicating that the value conforms to the chi-square distribution with a large probability, that is, the matching degree of the mathematical model and the physical line is high, and the protected line is in a normal state.

[0131] Based on the above principle, the line new energy r-side protection device is provided with the following action criterion. When the following action criterion conditions are met, the line r-side protection device sends a trip exit signal. At this time, the circuit breaker on the protected line r side should trip immediately to ensure the safe and stable operation of the power grid. The action criterion is specifically expressed as:

[0132]

[0133] In the formula, is a trip outlet signal sent by a line new energy side protection device, represents that tripping is needed, represents that tripping is not needed; is a protection action criterion window length; is a protection action threshold value; is an allowable signal of a main criterion of the line new energy side protection device, represents that tripping is allowed, represents that tripping is not allowed; is a residual normalized square sum of the line new energy side.

[0134] S5. The same fault current data of the fault line in the area are decoupled again by using the multi-mode phase-mode transformation combination to generate the residual normalized square sum of each mode domain component under the multi-mode phase-mode transformation combination.

[0135] S6. The fault phase is determined according to the residual normalized square sum ratio of each mode domain component under the multi-mode phase-mode transformation combination, and the corresponding tripping instruction is generated according to the fault phase to control the action of the circuit breaker to complete fault isolation.

[0136] The relay protection device of the alternating current transmission line of the voltage level of 220 kV and above needs to be equipped with a fault phase selection function to ensure that the protection device can accurately judge and take corresponding protection actions when a fault occurs. Specifically, when a single-phase ground fault occurs in the protected line, the protection device should be able to identify the fault phase and trip the corresponding single-phase circuit breaker. For two-phase short circuit, two-phase short circuit grounding or three-phase short circuit fault, the three-phase circuit breaker needs to be tripped. The protection principle described in the embodiment has a fault phase selection function and does not need additional auxiliary criteria. In the embodiment, the Karenbauer transformation formula is used to convert the measured data from the time domain to the mode domain for analysis. Through phase-mode transformation, three-phase voltage and current components can be converted into mode domain components, including zero-mode component, one-mode component and two-mode component information. For example, after the phase-mode transformation of step S1, the 1-mode component contains the measurement information of phases A and B, and the 2-mode component contains the measurement information of phases A and C. After the phase-mode transformation of the first rewritten formula, the 1-mode component contains the measurement information of phases B and C, and the 2-mode component contains the measurement information of phases A and B. After the phase-mode transformation of the second rewritten formula, the 1-mode component contains the measurement information of phases A and C, and the 2-mode component contains the measurement information of phases B and C. The first rewritten formula is specifically as follows:

[0137]

[0138] The second rewritten formula is specifically as follows:

[0139]

[0140] wherein, is the current value under the zero-mode component obtained by the first rewritten formula; is the current value under the one-mode component obtained by the first rewritten formula; is the current value under the two-mode component obtained by the first rewritten formula; is the A-phase current instantaneous sampling value at the new energy side or the grid side; is the B-phase current instantaneous sampling value at the new energy side or the grid side; is the C-phase current instantaneous sampling value at the new energy side or the grid side; is the current value under the zero-mode component obtained by the second rewritten formula; is the current value under the one-mode component obtained by the second rewritten formula; is the current value under the two-mode component obtained by the second rewritten formula.

[0141] In this embodiment, the A-phase single-phase ground fault of the protected line is taken as an example. The A-phase actual measurement value is decomposed into each mode through different phase-mode transformation modes, which will cause the change of the residual error of the corresponding mode. Through step S1, the residual error of two modes will be increased by decomposing into 1-mode and 2-mode. Through the first rewritten formula, the residual error of 2-mode will be increased by decomposing into 2-mode. Through the second rewritten formula, the residual error of 1-mode will be increased by decomposing into 1-mode. The BC two-phase lines of the non-fault phase are in the normal operation state. Although the single-phase ground fault can cause the voltage of the non-fault phase to rise, the line model does not change, so it will not cause the residual error to increase. By using this characteristic, this embodiment can perform fault phase selection through different phase-mode transformation modes. The multi-mode phase-mode transformation combination includes standard phase sequence transformation, cyclic phase sequence transformation and inverse sequence phase sequence transformation. In order to quantitatively analyze, this embodiment defines the residual error normalized square sum of each mode component, and judges the fault type (including three single-phase ground faults AG, BG and CG, three phase-to-phase short circuit faults AB, BC and AC, and three phase-to-phase short circuit ground faults ABG, BCG and ACG) according to the ratio thereof, and determines the specific fault phase selection method. In this embodiment, the residual error normalized square sum of the 1-mode current decomposed by step 1 is , the residual error normalized square sum of the 2-mode current is ; the residual error normalized square sum of the 1-mode current decomposed by the first rewritten formula is , the residual error normalized square sum of the 2-mode current is ; the residual error normalized square sum of the 1-mode current decomposed by the second rewritten formula is , and the residual error normalized square sum of the 2-mode current is Table 1 lists the residual ratio characteristics of each mode under different fault types in detail. By comparing the residual ratio, the fault type can be accurately determined. For example, when the residual ratio of a certain mode is 0 or close to 0, it indicates that the phase corresponding to the mode has not failed. When the residual ratio is close to 1, it indicates that the phase corresponding to the mode has failed. In addition, for two-phase short circuit and two-phase short circuit to ground fault, the unit cell with residual ratio of 1 can be further analyzed to distinguish them. If all residual ratios do not meet the table content, it can be determined as a three-phase fault. In this embodiment, the value range of the "1" cell is set as [0.9, 1.1], and the value range of the "0" cell is set as (0, 0.01). The specific fault selection method is shown in Table 1:

[0142] Table 1

[0143]

[0144] To verify the feasibility of the proposed AC transmission line state estimation protection fault selection method, this embodiment builds a new energy through flexible DC transmission system simulation model in PSCAD / EMTDC as shown in Figure 4 The flexible DC transmission system uses a true bipolar structure of flexible DC transmission scheme, and the rated voltage of the DC line is set to 800 kV. Among them, the MMC1 controller adopts a fixed AC voltage and AC frequency control strategy, and the MMC2 controller adopts a fixed DC voltage and fixed reactive power control strategy. The rated voltage of the AC line is 220 kV, and the new energy station uses a full-power inverter type power supply. The full-power inverter type power supply uses a fixed active power and fixed reactive power control mode. In this model, this embodiment determines the AC transmission line as the protection object, and the length of the line is 100 km. For easy analysis, this embodiment marks the new energy station of the line as the r side, and the grid side of the line as the g side. The sampling frequency is set to 5 kHz. In order to comprehensively evaluate the performance of the proposed protection scheme under different fault types and influencing factors, this embodiment simulates and verifies multiple fault scenarios, Figure 4 The fault positions are marked in Table 2, which include: f1 is the r-side out-of-zone near-end fault; f2 is the r-side in-zone first-end fault; f3 is the in-zone midpoint fault; f4 is the g-side in-zone first-end fault; and f5 is the g-side out-of-zone near-end fault.

[0145] In order to further explore the performance of the proposed fault selection method under different in-zone metallic fault scenarios, this embodiment sets multiple fault types at the f2, f3 and f4 positions of the AC line, and records the simulation results. Table 2 lists the simulation results under different fault positions and fault types, as shown in Table 2:

[0146] Table 2

[0147]

[0148] The simulation results of Table 2 show that the proposed protection principle can quickly and accurately identify various intra-zone faults in a very short time (within 2 ms), and specifically, in single-phase fault (such as A-phase, B-phase or C-phase fault), two-phase fault (such as BC-phase, CA-phase fault) or three-phase fault scenarios, the fault phase selection scheme can accurately determine the fault phase, for example, when an A-phase metallic fault occurs at f2 position, the protection devices at the r side and the g side can accurately identify the A-phase fault within about 1.5 ms to 1.9 ms, similarly, for BC-phase and CA-phase faults, and more serious three-phase faults, the protection devices also show good fault phase selection capability and fast action response, which fully verifies the effectiveness and reliability of the proposed fault phase selection method.

[0149] The embodiment of the present application provides a state estimation fault phase selection method for an alternating current transmission line, the method maps three-phase voltage and current components coupled with each other in a three-phase alternating current transmission line from a phase domain to a mode domain space through a phase-mode transformation matrix to obtain mode domain voltage and current components at a new energy side and a power grid side; based on a Bergeron transmission line model, a uniform lossy transmission line is equivalent to two lossless transmission lines in series with four concentrated resistors, and mode domain voltage and current components are taken as inputs, and a system measurement equation is constructed through a state variable; a weighted least square estimation model is used to solve the system measurement equation to obtain an optimal estimation value of the state variable; according to the optimal estimation value, a residual error normalized sum of squares of a measurement estimation value and an actual measurement value in the mode domain is calculated, and a zone fault line is screened out by comparing the residual error normalized sum of squares with a chi-square distribution threshold; a same fault current data of the zone fault line is decoupled twice by using a multi-mode phase-mode transformation combination to generate a residual error normalized sum of squares of each mode domain component under the multi-mode phase-mode transformation combination; the fault phase is determined according to a residual error normalized sum of squares ratio of each mode domain component under the multi-mode phase-mode transformation combination, and a corresponding trip instruction is generated according to the fault phase to control the action of a circuit breaker to complete fault isolation. Compared with the prior art, the method realizes rapid and accurate phase selection of the alternating current transmission line fault through the state estimation method combining the phase-mode transformation and the Bergeron model, and automatically generates a trip instruction to isolate the fault area, effectively improves the rapid detection and accurate positioning of the intra-zone fault of the alternating current transmission line, and guarantees the stable operation of the power grid.

[0150] It should be noted that the size of the serial number of each process does not mean the order of execution, and the execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0151] In one embodiment, as shown in Figure 5 The embodiment of the present application provides an alternating current transmission line state estimation fault phase selection system, the system comprises:

[0152] The phase-mode mapping module 101 is configured to map three-phase voltage and current components in a three-phase alternating current transmission line from a phase domain to a mode domain space by using a phase-mode transformation matrix, to obtain mode domain voltage and current components on a new energy side and a power grid side.

[0153] The measurement construction module 102 is configured to equivalently convert a uniform lossy transmission line into two lossless transmission lines in series with four lumped resistors based on a Bergeron transmission line model, and to construct a system measurement equation by using state variables and taking the mode domain voltage and current components as input.

[0154] The optimal estimation module 103 is configured to solve the system measurement equation by using a weighted least square estimation model, to obtain an optimal estimation value of the state variables.

[0155] The fault analysis module 104 is configured to calculate a residual normalized sum of squares of measurement estimation values and actual measurement values in the mode domain according to the optimal estimation value, and to screen out an in-zone fault line by comparing the residual normalized sum of squares with a chi-square distribution threshold.

[0156] The secondary decoupling module 105 is configured to perform secondary decoupling on the same fault current data of the in-zone fault line by using a multi-mode phase-mode transformation combination, to generate a residual normalized sum of squares of each mode domain component under the multi-mode phase-mode transformation combination.

[0157] The fault phase selection module 106 is configured to determine a fault phase according to a residual normalized sum of squares ratio of each mode domain component under the multi-mode phase-mode transformation combination, and to generate a corresponding tripping instruction according to the fault phase to control a circuit breaker to act to complete fault isolation.

[0158] In some embodiments, the phase-mode mapping module is specifically configured to:

[0159] Real-time acquisition of three-phase voltage instantaneous sampling values and three-phase current instantaneous sampling values on both sides of an alternating current transmission line to obtain three-phase voltage and current components; the both sides of the alternating current transmission line include a new energy side and a power grid side of the alternating current transmission line;

[0160] Mapping the three-phase voltage and current components from a phase domain to a mode domain space to obtain mode domain voltage and current components on the new energy side and the power grid side; the mode domain voltage and current components include zero-mode components, one-mode components and two-mode components.

[0161] In some embodiments, the measurement construction module is specifically configured to:

[0162] Obtaining alternating current transmission line parameters; the alternating current transmission line parameters include unit length resistance, unit length inductance, unit length capacitance and total length of the line;

[0163] Based on the AC transmission line parameters, a Bergeron transmission line model is used to equivalently convert the uniform lossy AC transmission line into a form of two lossless AC transmission lines in series with four lumped resistors, to obtain an equivalent converted lossless transmission line model;

[0164] According to the equivalent converted lossless transmission line model, lossless transmission line key parameters are calculated, including characteristic impedance, propagation time and attenuation coefficient;

[0165] According to the lossless transmission line key parameters and the modal domain voltage and current components, a dynamic voltage-current relationship equation of the AC transmission line new energy side and the grid side is established;

[0166] The modal domain voltage and current estimation values of the AC transmission line at the current time are defined as state variables, and the dynamic voltage-current relationship equation and the state variables are combined to construct a system measurement equation.

[0167] In some embodiments, the optimal estimation module is specifically configured to:

[0168] A residual error vector is constructed according to the difference between the real measurement values in the system measurement equation and the virtual measurement values estimated based on the current state variables; the real measurement values are the modal domain voltage and current components of the new energy side and the grid side;

[0169] A residual error weighted sum of squares minimization objective function is constructed with the weighted sum of squares minimization of the residual error vector as the optimization objective;

[0170] The optimal estimation value of the state variable is obtained by using the weighted least squares method to solve the residual error weighted sum of squares minimization objective function, using the Jacobian matrix to associate the state variable with the actual measurement value; the actual measurement value includes the real measurement value and the virtual measurement value.

[0171] In some embodiments, the fault analysis module is specifically configured to:

[0172] The optimal estimation value is input into the system measurement equation, the measurement estimation value under the modal domain is calculated, and the residual error estimation between the measurement estimation value and the actual measurement value is calculated;

[0173] The residual error estimation is normalized to obtain a normalized residual error, and the sum of squares of the normalized residual error is calculated according to the total number of actual measurement values, to obtain a residual error normalized sum of squares;

[0174] The degree of freedom is determined according to the difference between the total number of actual measurement values and the number of state variables in the system measurement equation, and the chi-square distribution threshold is queried from the chi-square distribution table using the degree of freedom;

[0175] The calculated residual normalized square sum is compared with a chi-square distribution threshold value, if the residual normalized square sum is greater than the chi-square distribution threshold value, it is judged that a line internal fault occurs, and an internal fault line is screened out; otherwise, the line is in normal operation.

[0176] In some embodiments, the internal fault includes an internal single-phase ground fault, an internal two-phase short circuit fault and an internal three-phase ground fault.

[0177] In some embodiments, the multi-mode phase-mode transformation combination includes a standard phase sequence transformation, a cyclic phase sequence transformation and an inverse phase sequence transformation.

[0178] The specific limitations of the AC power transmission line state estimation fault phase selection system can refer to the above limitations of the AC power transmission line state estimation fault phase selection method, which will not be repeated here. Those skilled in the art can realize that the various modules and steps described in combination with the embodiments disclosed in the present application can be realized in hardware, software or a combination of both. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0179] The embodiment of the present application provides an AC power transmission line state estimation fault phase selection system, the system maps the mutually coupled three-phase voltage and current components in the three-phase AC power transmission line from the phase domain to the mode domain space through a phase-mode mapping module, to obtain the mode domain voltage and current components on the new energy side and the power grid side; a measurement construction module equivalent uniform lossy transmission line to two lossless transmission lines in series with four concentrated resistors based on the Bergeron transmission line model, and takes the mode domain voltage and current components as input, to construct a system measurement equation through a state variable; an optimal estimation module solves the system measurement equation by using a weighted least squares estimation model, to obtain the optimal estimation value of the state variable; a fault analysis module calculates the residual normalized square sum of the measured and estimated values and the actual measured values in the mode domain according to the optimal estimation value, and screens out the internal fault line by comparing the residual normalized square sum with a chi-square distribution threshold value; a secondary decoupling module performs secondary decoupling on the same fault current data of the internal fault line by using a multi-mode phase-mode transformation combination, to generate the residual normalized square sum of each mode domain component under the multi-mode phase-mode transformation combination; and a fault phase selection module determines the fault phase according to the residual normalized square sum ratio of each mode domain component under the multi-mode phase-mode transformation combination, and generates a corresponding trip instruction to control the action of the circuit breaker to complete fault isolation. Compared with the prior art, the system realizes rapid and accurate phase selection of the AC power transmission line fault through the state estimation scheme combining phase-mode transformation and the Bergeron model, and automatically generates a trip instruction to isolate the fault area, effectively improving the rapid detection and accurate positioning of the internal fault of the AC power transmission line, and ensuring the stable operation of the power grid.

[0180] Figure 6 A computer device provided by an embodiment of the application includes a memory, a processor and a transceiver connected through a bus, the memory is configured to store a set of computer program instructions and data, and can transmit the stored data to the processor, the processor can execute the program instructions stored in the memory to perform the steps of the above method.

[0181] The memory can include a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories; the processor can be a central processing unit, a microprocessor, an application specific integrated circuit, a programmable logic device or a combination thereof. By way of example and not limitation, the programmable logic device can be a complex programmable logic device, a field programmable logic gate array, a general array logic or any combination thereof.

[0182] In addition, the memory can be a physically independent unit, or can be integrated with the processor.

[0183] Those skilled in the art can understand that the structure shown in the above embodiment is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied, and the specific computer device can include more or less components than those shown in the figure, or combine certain components, or have the same component arrangement. Figure 6 In one embodiment, the computer readable storage medium provided by the embodiment of the application stores a computer program, and the computer program is executed by the processor to realize the steps of the above method.

[0184] The method, system, device and medium provided by the embodiment of the application can quickly detect and accurately locate the fault in the AC transmission line area, can accurately identify the fault phase and generate a trip instruction, effectively isolates the fault area, and guarantees the stable operation of the power grid.

[0185]

[0186] ​In the above embodiments, all or part of the methods can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the methods can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transferred from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line) or wireless (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. integrated with one or more available media. The available media can be magnetic media (for example, floppy disk, hard disk, magnetic tape), optical media (for example, DVD), or semiconductor media (for example, SSD) and the like.

[0187] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments.

[0188] The above-described embodiments only express several preferred embodiments of the present application, which are described in detail and specifically, but should not be understood as limiting the scope of the patent. It should be noted that for ordinary skilled in the art, several improvements and replacements can be made without departing from the technical principles of the present application, and these improvements and replacements should be considered as the protection scope of the present application. Therefore, the protection scope of the present application patent should be subject to the protection scope of the claims.

Claims

1. An AC transmission line state estimation fault phase selection method characterized by, The method comprises the following steps: mapping three-phase voltage and current components coupled with each other in a three-phase alternating current transmission line from a phase domain to a modal domain space by using a phase-mode transformation matrix to obtain modal domain voltage and current components at a new energy side and a power grid side; the modal domain voltage and current components comprise a zero-mode component, a one-mode component and a two-mode component; equivalent the uniform lossy transmission line to two lossless transmission lines in series with four lumped resistors based on a Bergeron transmission line model, taking the modal domain voltage and current components as inputs, and constructing system measurement equations by using state variables; solving the system measurement equations by using a weighted least square estimation model to obtain optimal estimation values of the state variables; calculating a residual normalized sum of squares of measurement estimation values and actual measurement values in the modal domain according to the optimal estimation values, and screening out an in-zone fault line by comparing the residual normalized sum of squares with a chi-square distribution threshold; the in-zone fault comprises an in-zone single-phase ground fault, an in-zone two-phase short-circuit fault and an in-zone three-phase ground fault; decoupling the same fault current data of the in-zone fault line by using a multi-mode phase-mode transformation combination for a second time to generate a residual normalized sum of squares of each modal domain component under the multi-mode phase-mode transformation combination; the multi-mode phase-mode transformation combination comprises a standard phase sequence transformation, a cyclic phase sequence transformation and an inverse phase sequence transformation; determining a fault phase by comparing residual ratios according to the residual normalized sum of squares of each modal domain component under the multi-mode phase-mode transformation combination, and generating a corresponding trip command according to the fault phase to control a circuit breaker to act to complete fault isolation.

2. An AC transmission line state estimation faulted phase selection method as recited in claim 1, wherein, The step of mapping three-phase voltage and current components coupled with each other in a three-phase alternating current transmission line from a phase domain to a modal domain space by using a phase-mode transformation matrix to obtain modal domain voltage and current components at a new energy side and a power grid side comprises: collecting three-phase voltage instantaneous sampling values and three-phase current instantaneous sampling values at both sides of the alternating current transmission line in real time to obtain three-phase voltage and current components; the both sides of the alternating current transmission line comprise a new energy side and a power grid side of the alternating current transmission line; mapping the three-phase voltage and current components from the phase domain to the modal domain space to obtain modal domain voltage and current components at the new energy side and the power grid side.

3. An AC transmission line state estimation faulted phase selection method as recited in claim 2, wherein, The step of equivalent the uniform lossy transmission line to two lossless transmission lines in series with four lumped resistors based on a Bergeron transmission line model, taking the modal domain voltage and current components as inputs, and constructing system measurement equations by using state variables comprises: obtaining alternating current transmission line parameters; the alternating current transmission line parameters comprise a unit length resistance, a unit length inductance, a unit length capacitance and a total length of the line; equivalent the uniform lossy alternating current transmission line to two lossless alternating current transmission lines in series with four lumped resistors based on the Bergeron transmission line model according to the alternating current transmission line parameters to obtain an equivalent converted lossless transmission line model; calculating lossless transmission line key parameters according to the equivalent converted lossless transmission line model; the lossless transmission line key parameters comprise a characteristic impedance, a propagation time and an attenuation coefficient; establishing dynamic voltage-current relationship equations of the new energy side and the power grid side of the alternating current transmission line according to the lossless transmission line key parameters and the modal domain voltage and current components; The estimated values of the voltage and current in the modal domain at both sides of the AC transmission line at the current time are defined as state variables, and the dynamic voltage-current relationship equation is combined with the state variables to construct a system measurement equation.

4. An AC transmission line state estimation faulted phase selection method as recited in claim 1 wherein, The step of solving the system measurement equation by using a weighted least square estimation model to obtain the optimal estimated value of the state variable comprises: A residual error vector is constructed according to the difference between the real measurement value in the system measurement equation and the virtual measurement value estimated based on the current state variable; the real measurement value is the modal domain voltage and current component at the new energy side and the grid side; A weighted sum of residual errors minimization objective function is constructed by taking the weighted sum of squares of the residual error vector as the optimization objective; The optimal estimated value of the state variable is obtained by using the weighted least square method to solve the weighted sum of residual errors minimization objective function by using the Jacobian matrix to associate the state variable with the actual measurement value; the actual measurement value includes the real measurement value and the virtual measurement value.

5. An AC transmission line state estimation faulted phase selection method as recited in claim 1 wherein, The step of calculating the residual error normalized sum of squares of the measurement estimated value and the actual measurement value in the modal domain according to the optimal estimated value, and screening out the fault line in the area by comparing the residual error normalized sum of squares with the chi-square distribution threshold value comprises: The optimal estimated value is input into the system measurement equation to calculate the measurement estimated value in the modal domain, and the residual error estimate between the measurement estimated value and the actual measurement value is calculated; The residual error estimate is normalized to obtain a normalized residual error, and the sum of squares of the normalized residual error is calculated according to the total number of actual measurement values to obtain the residual error normalized sum of squares; The degrees of freedom are determined according to the difference between the total number of actual measurement values and the number of state variables in the system measurement equation, and the chi-square distribution threshold value is queried from the chi-square distribution table by using the degrees of freedom; The calculated residual error normalized sum of squares is compared with the chi-square distribution threshold value, if the residual error normalized sum of squares is greater than the chi-square distribution threshold value, it is judged that the line has an internal fault, and the fault line in the area is screened out; otherwise, the line is normal.

6. An AC transmission line state estimation fault phase selection system characterized by, The system comprises: A phase-mode mapping module is configured to map three-phase voltage and current components in a three-phase AC transmission line from a phase domain to a modal domain space by using a phase-mode transformation matrix to obtain modal domain voltage and current components at the new energy side and the grid side; the modal domain voltage and current components include zero-mode components, one-mode components and two-mode components; A measurement construction module is configured to equivalently convert a uniform lossy transmission line into two lossless transmission lines in series with four lumped resistors based on a Bergeron transmission line model, and construct a system measurement equation by using state variables and taking the modal domain voltage and current components as inputs; An optimal estimation module is configured to solve the system measurement equation by using a weighted least square estimation model to obtain the optimal estimated value of the state variable; A fault analysis module is configured to calculate the residual error normalized sum of squares of the measurement estimated value and the actual measurement value in the modal domain according to the optimal estimated value, and screen out the fault line in the area by comparing the residual error normalized sum of squares with the chi-square distribution threshold value; the internal fault includes an internal single-phase ground fault, an internal two-phase short-circuit fault and an internal three-phase ground fault. A secondary decoupling module is configured to perform secondary decoupling on the same fault current data of the fault line in the area by using a multi-mode phase-mode transformation combination, and generate residual normalized square sums of each mode domain component under the multi-mode phase-mode transformation combination; the multi-mode phase-mode transformation combination includes a standard phase sequence transformation, a cyclic phase sequence transformation, and an inverse phase sequence transformation; A fault phase selection module is configured to determine a fault phase by comparing residual ratios according to the residual normalized square sums of each mode domain component under the multi-mode phase-mode transformation combination, and generate a corresponding trip instruction according to the fault phase to control the circuit breaker to complete fault isolation.

7. An AC transmission line state estimation faulted phase selection system as recited in claim 6, wherein, The phase-mode mapping module is specifically configured to: collect three-phase voltage instantaneous sampling values and three-phase current instantaneous sampling values on both sides of the AC transmission line in real time to obtain three-phase voltage and current components; the two sides of the AC transmission line include a new energy side and a power grid side of the AC transmission line; map the three-phase voltage and current components from a phase domain to a mode domain space to obtain mode domain voltage and current components of the new energy side and the power grid side; the mode domain voltage and current components include a zero-mode component, a one-mode component, and a two-mode component.

8. An AC transmission line state estimation faulted phase selection system as recited in claim 7, wherein, The measurement construction module is specifically configured to: obtain AC transmission line parameters; the AC transmission line parameters include unit length resistance, unit length inductance, unit length capacitance, and total line length; equivalent the uniform lossy AC transmission line to a form of two lossless AC transmission lines in series with four concentrated resistances by using the Bergeron transmission line model based on the AC transmission line parameters to obtain an equivalent converted lossless transmission line model; calculate lossless transmission line key parameters according to the equivalent converted lossless transmission line model; the lossless transmission line key parameters include characteristic impedance, propagation time, and attenuation coefficient; establish a dynamic voltage-current relationship equation of the new energy side and the power grid side of the AC transmission line according to the lossless transmission line key parameters and the mode domain voltage and current components; define mode domain voltage and current estimation values of both sides of the AC transmission line at the current time as state variables, and combine the dynamic voltage-current relationship equation with the state variables to construct a system measurement equation.

9. An AC transmission line state estimation faulted phase selection system as recited in claim 6, wherein, The optimal estimation module is specifically configured to: construct a residual vector according to a difference between real measurement values in the system measurement equation and virtual measurement values estimated based on current state variables; the real measurement values are mode domain voltage and current components of the new energy side and the power grid side; construct a residual weighted square sum minimization objective function with minimization of a weighted square sum of the residual vector as an optimization objective; use a weighted least squares method to solve the residual weighted square sum minimization objective function by using a Jacobian matrix to associate the state variables with actual measurement values, to obtain optimal estimation values of the state variables; the actual measurement values include the real measurement values and the virtual measurement values.

10. An AC transmission line state estimation faulted phase selection system as recited in claim 6, wherein, The fault analysis module is specifically configured to: input the optimal estimation values into the system measurement equation, calculate measurement estimation values in the mode domain, and calculate residual estimation between the measurement estimation values and actual measurement values; normalizing the residual estimation to obtain a normalized residual, and calculating a sum of squares of the normalized residual according to the total number of actual measurement values to obtain a residual normalized sum of squares; determining a degree of freedom according to a difference between the total number of actual measurement values and the number of state variables in the system measurement equation, and querying a chi-square distribution threshold from a chi-square distribution table using the degree of freedom; comparing the calculated residual normalized sum of squares with the chi-square distribution threshold, and if the residual normalized sum of squares is greater than the chi-square distribution threshold, judging that a fault occurs in the line in the area, and screening out the line in the area with the fault; otherwise, the line is in normal operation.

11. A computer device, characterized by: The computer device comprises a processor and a memory, the processor is connected with the memory, the memory is used for storing a computer program, and the processor is used for executing the computer program stored in the memory, so that the computer device executes the method in any one of claims 1 to 5.

12. A computer-readable storage medium, characterized in that: The computer readable storage medium stores a computer program, and when the computer program is executed, the method in any one of claims 1 to 5 is implemented.

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