Method and system for identifying traveling wave parameters of alternating current transmission line on line

Abstract

The invention discloses an AC power transmission line traveling wave parameter online identification method and system. The method comprises the following steps: constructing a network element time domain model and a lossless uniform transmission line time domain model of a to-be-identified AC power transmission line; connecting the two sections of lossless uniform transmission lines in series with a plurality of concentrated resistors to obtain a lossy transmission line model of the AC line to be tested, and obtaining a first lossy transmission line time domain model and a second lossy transmission line time domain model according to the lossless uniform transmission line time domain model of each lossless uniform transmission line, according to the first lossy transmission line time domain model and the second lossy transmission line time domain model, a fitness target function is constructed, on the basis of the fitness target function, electrical quantity information on the two sides of the lossy transmission line models is used for conducting grouping iteration optimization on the to-be-identified parameters, a final identification result is obtained, and the parameter identification accuracy is improved through the method.

Description

Technical Field

[0001] The present invention relates to the technical field of transmission line parameter identification, and particularly to an online identification method and system for traveling wave parameters of an AC transmission line. Background Art

[0002] Accelerating the construction of a clean, low-carbon, safe and efficient energy system has become a major national requirement. Ensuring the safe and stable operation of new energy units is particularly important. For the AC outgoing lines of new energy power stations, when a fault occurs on the line, the system voltage will drop deeply, significantly reducing the system's ability to withstand fault impacts. In severe cases, it may lead to large-scale disconnection of new energy, posing more stringent requirements for the operating speed of relay protection.

[0003] Most existing projects still use traditional power frequency quantity protection, and the operating speed is limited by the window length of the Fourier algorithm, making it difficult to be significantly improved. The new protection principle with higher parameter accuracy requirements has a faster operating speed and can meet the requirements of the AC outgoing lines of new energy power stations. However, accurate line parameters are difficult to obtain online in actual projects, and the line parameters will gradually change along with system operation, engineering transformation, and line aging. Therefore, it is urgent to conduct research on how to obtain accurate parameters of AC lines online.

[0004] At present, the research on transmission line parameter identification by domestic and foreign scholars mainly includes offline identification methods and online identification methods. The offline identification methods for transmission line parameters mainly include theoretical calculation methods, instrument methods, digital methods, frequency sweeping methods, etc. The Carson formula is a classic theoretical calculation method that calculates line parameters through geometric structures such as towers, conductors, and ground wires. The instrument method makes appropriate connections to the measured line and uses various instruments such as voltmeters, ammeters, wattmeters, and frequency meters to calculate line parameters by measuring basic quantities such as voltage and current. The digital method uses single-chip microcontrollers and digital signal processing technologies to improve the data quality of the instrument method and partially improve the measurement accuracy. The frequency sweeping method determines the frequency with a relatively high signal-to-noise ratio as the applied test power frequency by frequency sweeping, injects interference signals before the line is put into operation or during outage maintenance, and uses the data calculation method of the traditional instrument method to identify line parameters. The offline measurement method is usually used to obtain parameters before the transmission line is put into operation, and an independent measurement circuit or additional power supply needs to be built at the test site. The operation steps are numerous and the error deviation is relatively obvious. Secondly, due to the influence of long-term operation, climate environment, temperature change, etc., the line parameters measured at the initial stage of project construction are difficult to accurately reflect the actual operation of the power grid. Therefore, it is particularly important to measure line parameters online during the normal operation of the system.

[0005] Online parameter identification methods for transmission lines mainly include parameter identification methods based on data from Supervisory Control And Data Acquisition (SCADA) systems, parameter identification methods based on data from Phase Measurement Units (PMUs), and parameter identification methods based on fault recorder data. The line parameter identification method based on the SCADA data acquisition system mainly includes two categories: the augmented state estimation method and the measurement residual sensitivity analysis method. The augmented state estimation method increases the number of variables on the basis of traditional state estimation, takes the line parameters to be identified as augmented state variables, and performs state estimation in combination with the original state variables. The measurement residual sensitivity method characterizes the relationship between the state estimation residuals and the line parameters, establishes a residual sensitivity matrix in combination with the system measurement equation, and uses an optimization algorithm to iteratively optimize and correct the incorrect parameters. The wide-area measurement system uses technologies such as the Global Positioning System, PMUs, and high-speed communication networks to synchronously collect the voltage and current phasors of each node in the power system, improving the real-time state perception ability of the power system. The data collected by the PMU device has time stamps and high measurement accuracy, and the electrical quantities between nodes can be synchronously calculated, providing a new idea for the identification of transmission line parameters. Fault recorder data is usually used to analyze the cause of faults and mainly includes pre-fault steady-state operation information, fault transient information, and post-fault steady-state information, including the instantaneous sampled values of voltage and current on both sides of the line. Similarly, fault recorder data can also be used as known measurement values to identify the parameters of transmission lines.

[0006] The parameter identification method based on SCADA data is mainly used to identify the parameters of all lines in the network. It requires a large number of equations and has a high dimension of state variables, which is prone to numerical instability. The parameter identification method based on PMU data can calculate the parameters of a single transmission line. However, there are few PMUs installed on existing lines, and most of the considered transmission line models are lumped parameter models, which are difficult to apply to long-distance high-voltage transmission lines. The parameter identification method based on fault recorder data is severely affected by the transient aperiodic component in terms of calculation accuracy and is difficult to apply to relay protection schemes with high requirements for line parameter accuracy. Moreover, there is no research on the related parameter identification methods for characterizing the wave process of transmission lines, and the practical application of new protection principles is restricted. Summary of the Invention

[0007] To solve the above technical problems, an embodiment of the present invention provides an online identification method and system for traveling wave parameters of an AC transmission line to solve the problem of low parameter identification accuracy caused by factors such as ignoring the influence of the distributed capacitance to the ground in existing AC line parameter identification methods.

[0008] The first aspect of the embodiments of the present invention provides an on-line identification method for traveling wave parameters of an AC transmission line, and the method includes: Construct a time-domain model of network elements and a time-domain model of a lossless uniform transmission line for the AC transmission line to be identified; Connect multiple lumped resistors in series with two lossless uniform transmission lines to obtain a lossy transmission line model of the AC line to be measured, and obtain a lossy transmission line time-domain model according to the time-domain models of the lossless uniform transmission lines. Among them, the lossy transmission line time-domain model includes a first lossy transmission line time-domain model and a second lossy transmission line time-domain model; According to the first lossy transmission line time-domain model and the second lossy transmission line time-domain model, construct a fitness objective function. Based on the fitness objective function, use the electrical quantity information on both sides of the lossy transmission line model to perform grouped iterative optimization on the parameters to be identified, and obtain the final identification result. Among them, the parameters to be identified include wave impedance, lumped resistance, and traveling wave transmission duration.

[0009] In a possible implementation manner of the first aspect, constructing a time-domain model of network elements and a time-domain model of a lossless uniform transmission line for the AC transmission line to be identified includes: Use the central difference method to construct a time-domain model of a resistance element, a time-domain model of an inductance element, a time-domain model of a capacitance element, a series time-domain model, and a time-domain model of a lossless uniform transmission line. Among them, the series time-domain model is a time-domain model of a series connection of a resistor and an inductor, and the time-domain model of the lossless uniform transmission line is: In the formula, is the historical term, is the wave impedance, is the voltage at time is the current at time in is the voltage before time is the current before time

[0010] In a possible implementation manner of the first aspect, obtaining a lossy transmission line time-domain model according to the time-domain models of the lossless uniform transmission lines includes: Obtain a lossy transmission line time-domain model according to the time-domain models of the lossless uniform transmission lines. Among them, the first lossy transmission line time-domain model is: In the formula, is the first lossy transmission line time-domain model, is the wave impedance, is a historical item, is the voltage value of the first side at time, is the lumped resistance equivalent to the full length of the line; The second lossy transmission line time-domain model is: In the formula, is the second lossy transmission line time-domain model, is the wave impedance, is a historical item, is the voltage value of the second side at time, is the lumped resistance equivalent to the full length of the line.

[0011] In a possible implementation of the first aspect, according to the first lossy transmission line time-domain model and the second lossy transmission line time-domain model, a fitness objective function is constructed, including: Determine the midpoint of a lossless uniform transmission line, and divide the lossless uniform transmission line into two segments by the midpoint to obtain the first segment of the line and the second segment of the line; Use the lossy transmission line model to simplify and equivalent the first segment of the line and the second segment of the line respectively, to obtain the first time-domain expression and the second time-domain expression, where the first time-domain expression is: In the formula, is the current value at point of the first side at time, is the voltage value at point of the first side at time, is the time for the traveling wave to propagate from point of the first side to the midpoint, , is a historical item, which can be calculated according to the current and voltage sampling values at points before time and points F; The second time-domain expression is: In the formula, is the current value at point F at time, is the voltage value at point at time, is the time for the traveling wave to propagate from point , is a historical item, which can be calculated according to Before time Obtained from the current and voltage sampling values at points and F Adjust the first time-domain expression and the second time-domain expression respectively to obtain the adjusted first time-domain expression and the adjusted second time-domain expression; According to the adjusted first time-domain expression and the adjusted second time-domain expression, obtain the fitness objective function, where the fitness objective function is: In the formula, Is the number of sampling points used in the improved particle swarm algorithm, Is the wave impedance, Is the lumped resistance equivalent to the full length of the line, For the traveling wave from the first side The time for the point to propagate to the midpoint.

[0012] In a possible implementation of the first aspect, use the electrical quantity information on both sides of the lossy transmission line model to perform grouped iterative optimization on the parameters to be identified, and obtain the final identification result, including: Use the Karenbauer phase-mode conversion matrix to decouple the voltages and currents on both sides to obtain the decoupled voltage and current values; Divide the parameters to be identified into two groups to obtain the first group of parameters to be identified and the second group of parameters to be identified; Take the first group of parameters to be identified as known quantities, update the fitness objective function to obtain the first fitness objective function, and perform iterative identification on the second group of parameters to be identified according to the first fitness objective function and the decoupled voltage and current values to obtain the first identification result; Take the first identification result as a known quantity, update the fitness objective function to obtain the second fitness objective function, and perform iterative identification on the first group of parameters to be identified according to the second fitness objective function to obtain the second identification result; Judge whether the first identification result and the second identification result meet the preset conditions. If they meet, determine the first identification result and the second identification result as the final identification result. If they do not meet, continue with iterative identification.

[0013] In a possible implementation of the first aspect, the first group of parameters to be identified includes the wave impedance. When taking the first group of parameters to be identified as known quantities, it includes: Calculate the initial value of the wave impedance, where the calculation method of the initial value of the wave impedance is: In the formula, Is the initial value of the wave impedance, Represents the electrical quantity value at 50Hz frequency.

[0014] In a possible implementation of the first aspect, the preset condition is whether the difference between the recognition result obtained in the current iteration and the recognition result obtained in the previous iteration is less than a preset value.

[0015] To solve the same technical problem, a second aspect of the embodiments of the present invention provides an on-line identification system for traveling wave parameters of an AC transmission line. The system includes: A first construction module, configured to construct a time-domain model of network elements of the AC transmission line to be identified and a time-domain model of a lossless uniform transmission line; A second construction module, configured to connect two lossless uniform transmission lines in series with a plurality of lumped resistors to obtain a lossy transmission line model of the AC line to be measured, and obtain a lossy transmission line time-domain model according to the time-domain models of the lossless uniform transmission lines. The lossy transmission line time-domain model includes a first lossy transmission line time-domain model and a second lossy transmission line time-domain model; An identification module, configured to construct a fitness objective function according to the first lossy transmission line time-domain model and the second lossy transmission line time-domain model, and based on the fitness objective function, use the electrical quantity information on both sides of the lossy transmission line model to perform grouped iterative optimization on the parameters to be identified to obtain a final identification result, where the parameters to be identified include wave impedance, lumped resistance, and traveling wave transmission duration.

[0016] In a possible implementation of the second aspect, the first construction module includes a time-domain model construction unit, where the time-domain model construction unit is configured to use the central difference method to construct a time-domain model of a resistance element, a time-domain model of an inductance element, a time-domain model of a capacitance element, a series time-domain model, and a time-domain model of a lossless uniform transmission line. The series time-domain model is a time-domain model of a resistor and an inductor in series, and the time-domain model of the lossless uniform transmission line is: In the formula, is the historical term, is the wave impedance, is the voltage at time is at the current at time is the voltage before time is the current before time

[0017] In a possible implementation of the second aspect, the second construction module includes a lossy transmission line time-domain model construction unit, where The lossy transmission line time-domain model construction unit is used to obtain the lossy transmission line time-domain model based on the lossless uniform transmission line time-domain models of each lossless uniform transmission line. Among them, the first lossy transmission line time-domain model is as follows: In the formula, is the first lossy transmission line time-domain model, is the wave impedance, is the historical term, is the voltage value on the first side at time, is the lumped resistance equivalent to the full length of the line; The second lossy transmission line time-domain model is as follows: In the formula, is the second lossy transmission line time-domain model, is the wave impedance, is the historical term, is the voltage value on the second side at time, is the lumped resistance equivalent to the full length of the line.

[0018] The third aspect of the embodiments of the present invention provides a computer device, including: A memory for storing a computer program; A processor for implementing the steps of the online identification method for traveling wave parameters of an AC transmission line as in the first aspect when executing the computer program.

[0019] The fourth aspect of the embodiments of the present invention provides a storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the online identification method for traveling wave parameters of an AC transmission line as in the first aspect are implemented.

[0020] The technical solution of the present invention has the following advantages: The on-line identification method for traveling wave parameters of an AC transmission line provided by an embodiment of the present invention constructs a time-domain model of network elements of the AC transmission line to be identified and a time-domain model of a lossless uniform transmission line; connects two lossless uniform transmission lines in series with multiple lumped resistors to obtain a lossy transmission line model of the AC line to be measured, and obtains a first lossy transmission line time-domain model and a second lossy transmission line time-domain model according to the time-domain models of the lossless uniform transmission lines. According to the first lossy transmission line time-domain model and the second lossy transmission line time-domain model, a fitness objective function is constructed. Based on the fitness objective function, the electrical quantity information on both sides of the lossy transmission line model is used to perform grouped iterative optimization on the parameters to be identified, and a final identification result is obtained. The above method deduces the time-domain model of the lossy uniform transmission line according to the traveling wave transmission characteristics, and then uses the improved particle swarm algorithm to perform grouped iterative optimization on the parameters to be identified, improving the accuracy of parameter identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0022] Figure 1 It is a flowchart of the on-line identification method for traveling wave parameters of an AC transmission line in an embodiment of the present invention; Figure 2 It is a schematic diagram of the time-domain model of the resistance element in the on-line identification method for traveling wave parameters of an AC transmission line in an embodiment of the present invention; Figure 3 It is a schematic diagram of the time-domain model of the inductance element in the on-line identification method for traveling wave parameters of an AC transmission line in an embodiment of the present invention; Figure 4 It is a schematic diagram of the time-domain model of the capacitance element in the on-line identification method for traveling wave parameters of an AC transmission line in an embodiment of the present invention; Figure 5 It is a schematic diagram of the time-domain model of the series element of resistance and inductance in the on-line identification method for traveling wave parameters of an AC transmission line in an embodiment of the present invention; Figure 6 It is a schematic diagram of the time-domain model of a lossless uniform transmission line in the on-line identification method for traveling wave parameters of an AC transmission line in an embodiment of the present invention; Figure 7 It is a schematic diagram of a time-domain model of a transmission line considering losses in the on-line identification method for traveling wave parameters of an AC transmission line in an embodiment of the present invention; Figure 8Schematic diagram of another transmission line time-domain model considering losses for the on-line identification method of traveling wave parameters of AC transmission lines in the embodiments of the present invention; Figure 9 Schematic diagram of the uniform transmission line model for the on-line identification method of traveling wave parameters of AC transmission lines in the embodiments of the present invention; Figure 10 Flowchart of the traveling wave parameter identification method based on the improved particle swarm algorithm for the on-line identification method of traveling wave parameters of AC transmission lines in the embodiments of the present invention; Figure 11 Schematic diagram of the large-scale new energy power station sending-out system for the on-line identification method of traveling wave parameters of AC transmission lines in the embodiments of the present invention; Figure 12 Schematic diagram of the wave impedance identification result for the on-line identification method of traveling wave parameters of AC transmission lines in the embodiments of the present invention; Figure 13 Schematic diagram of the equivalent concentrated resistance identification result for the on-line identification method of traveling wave parameters of AC transmission lines in the embodiments of the present invention; Figure 14 Schematic diagram of the transmission duration identification result for the on-line identification method of traveling wave parameters of AC transmission lines in the embodiments of the present invention; Figure 15 Comparison result diagram of voltage measurement values of different line models for the on-line identification method of traveling wave parameters of AC transmission lines in the embodiments of the present invention; Figure 16 Comparison result diagram of current measurement values of different line models for the on-line identification method of traveling wave parameters of AC transmission lines in the embodiments of the present invention; Figure 17 System block diagram of the on-line identification system for traveling wave parameters of AC transmission lines in the embodiments of the present invention. Detailed implementation manners

[0023] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0024] In the description of the present invention, it should be noted that the terms "first", "second", and "third" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance.

[0025] The on-line identification method of traveling wave parameters of AC transmission lines provided by the embodiments of the present invention is as Figure 1 shown Figure 1It is a flowchart for on-line identification of traveling wave parameters of an AC transmission line, including steps S101 to S103, and the specific steps are as follows: S101: Construct a time-domain model of network elements and a time-domain model of a lossless uniform transmission line for the AC transmission line to be identified.

[0026] In this embodiment, to construct a time-domain model of network elements and a time-domain model of a lossless uniform transmission line for the AC transmission line to be identified, specifically, a time-domain model of network elements is constructed by using the central difference theorem to remove differential terms.

[0027] In one embodiment, constructing a time-domain model of network elements and a time-domain model of a lossless uniform transmission line for the AC transmission line to be identified includes: Using the central difference method to construct a time-domain model of a resistance element, a time-domain model of an inductance element, a time-domain model of a capacitance element, a series time-domain model, and a time-domain model of a lossless uniform transmission line. Among them, the series time-domain model is a time-domain model of a series connection of a resistance and an inductance, and the time-domain model of the lossless uniform transmission line is: In the formula, is the historical term, is the wave impedance, is the voltage at time is at the current at time is the voltage before time is the current before time

[0028] In this embodiment, the time-domain model of the resistance element is as shown in Figure 2 The time-domain equation of which does not contain differential terms and is often used to represent the loss of the line. The expression is: In the formula, is the voltage at one end of the resistance at time is the voltage at the other end of the resistance at time is the voltage at the other end of the resistance at time is the voltage at the other end of the resistance at time is the current of the resistance at time is the current of the resistance at time is the resistance value of the resistance.

[0029] The time-domain model of the inductance element is as shown in Figure 3 As an energy storage element, the time-domain equation of the inductance contains differential terms. The expression is: In the formula, is the voltage at one end of the inductor at moment, is the voltage at the other end of the inductor at moment, is the inductance value. Since the time-domain model of the inductor element contains a differential term, using the central difference theorem to remove the differential term, we can get: Rearranging the above formula and simplifying it to: In the formula, is the voltage at one end of the inductor at moment, is the voltage at the other end of the inductor at moment, is the inductance value, is the current value of the inductor. In the formula, is the single sampling interval time, is the historical term, is the voltage at one end of the inductor at time t, is the voltage at the other end of the inductor at moment, is the inductance value, is the voltage at one end of the inductor at moment, is the voltage at the other end of the inductor at moment.

[0030] Combining Equation (4) and Equation (5), the current value of the inductor element time-domain model at the current moment can be calculated by recursively updating the historical value and the voltage value at the current moment.

[0031] The time-domain model of the capacitor element is as shown in Figure 4 . As an energy storage element, the time-domain equation of the capacitor contains a differential term, and the time-domain model is: In the formula, is the current of the capacitor at moment, is the capacitance value, is the voltage at one end of the capacitor at moment, is the voltage at the other end of the capacitor at moment.

[0032] Using the central difference theorem to remove the differential term from Equation (6), we can get: Rearranging Equation (7) can be simplified to: (8) (9) Wherein, is the historical term and can be calculated using the current and voltage sampling values at the previous sampling moment; is the voltage at one end of the capacitor at moment, is the voltage at the other end of the capacitor at moment.

[0033] Combining Equation (8) and Equation (9), the current value of the capacitor element time-domain model at the current moment can be calculated by recursively updating the historical value and the voltage value at the current moment.

[0034] The time-domain model of a series connection of a resistor and an inductor is as shown in Figure 5 and is commonly used as a lumped parameter equivalent model of a transmission line. Its linear ordinary differential equation is: Wherein, is the voltage at one end of the series connection of the resistor and the inductor at moment, is the voltage at the other end of the series connection of the resistor and the inductor at moment, is the current of the series connection of the resistor and the inductor at moment, is the inductance value, is the capacitance value.

[0035] Equation (10) contains a differential term. Using the central difference theorem to remove the differential term, we can obtain: Rearranging Equation (11) can be simplified to: Wherein, is the historical term, is the voltage at one end of the series connection of the resistor and the inductor at moment, is the voltage at the other end of the series connection of the resistor and the inductor at moment.

[0036] The time-domain model of a lossless uniform transmission line is as shown in Figure 6 . The lossless uniform transmission line ignores the line resistance and conductance. Its partial differential equation for voltage and current is: Wherein, is the inductance value in the lossless uniform transmission line, is the capacitance value in a lossless uniform transmission line, is the voltage value of the lossless uniform transmission line at position at time is the voltage value of the lossless uniform transmission line at position at time

[0037] The d'Alembert solutions of equations (14) and (15) are: wherein, and are expressed as and functions, is the wave impedance of the lossless line, , is the wave velocity, = 3×10 8 m / s.

[0038] Multiply both sides of equation (17) by the wave impedance , and add it to equation (16), we can get: It can be seen from equation (18) that if does not change, then will not change either. Let the propagation time of the traveling wave on the line be , we can get: Arrange equation (19), it can be simplified to: wherein, is the voltage at the starting point of the lossless uniform transmission line at time, is the current at the starting point of the lossless uniform transmission line at time, is the voltage at the ending point of the lossless uniform transmission line at time, is the current at the ending point of the lossless uniform transmission line at time, is the history term, which can be calculated by using the sampled values of the current and voltage on the opposite side of the line time ago.

[0039] Combining equations (20) and (21), the historical value and the voltage value at the current time can be recursively updated, and then the current value of the time-domain model of the lossless uniform transmission line at the current time can be calculated.

[0040] S102: Connect two lossless uniform transmission lines in series with multiple lumped resistors to obtain a lossy transmission line model of the AC line to be measured. According to the time-domain models of the lossless uniform transmission lines, obtain the time-domain model of the lossy transmission line. Among them, the time-domain model of the lossy transmission line includes the first time-domain model of the lossy transmission line and the second time-domain model of the lossy transmission line.

[0041] In this embodiment, the time-domain model of the lossless uniform transmission line ignores the resistance and conductance of the line, resulting in certain calculation errors. To increase the accuracy of the model, one or more segments of lossless uniform transmission lines can be used, with lumped resistors connected in series between the segments, to equivalent the uniform lossy transmission line.

[0042] The transmission line model considering losses can be equivalent to a lossless uniform transmission line connected in series with two lumped resistors, and the time-domain model is as Figure 7 shown.

[0043] According to the traveling wave transmission equation in Equation (19), the time-domain expression of the transmission line model considering losses can be derived as: In the formula, is the lumped resistor equivalent to the full length of the line, , is the voltage value on the side at time, is the current value on the side at time, is the voltage value on the side at time,

[0044] After arranging Equation (22), it can be simplified to: In the formula, is the historical term, which can be calculated using the sampled values of the current and voltage on the opposite side of the line time ago. By comparing Equation (20) and Equation (23), it can be seen that when two lumped resistors are connected in series to the lossless transmission line, the measured value and historical value coefficients in the equation need to be corrected, improving the accuracy of the model.

[0045] According to Equation (23), the lossy transmission line equation can be constructed. By recursively updating the historical value on the side of the line and the voltage value at the current time k on the k side, calculate the voltage value on the However, the accuracy of the line equivalent model often does not meet the requirements of electromagnetic transient simulation. Two sections of lossless uniform transmission lines are connected in series with four concentrated resistors to equivalent the lossy transmission line and improve the accuracy of the line equivalent model.

[0046] In one embodiment, the time domain model of the lossy transmission line is obtained according to the time domain model of the lossless uniform transmission line of each lossless uniform transmission line, including: The lossy transmission line time domain model is obtained according to the lossless uniform transmission line time domain model of each lossless uniform transmission line, wherein the first lossy transmission line time domain model is: In the formula, is the time domain model of the first lossy transmission line, is the wave impedance, For historical items, is the voltage value of the first side at time t, It is the concentrated resistance equivalent to the entire length of the line; The time domain model of the second lossy transmission line is: In the formula, is the time domain model of the second lossy transmission line, is the wave impedance, For historical items, is the voltage value of the second side at time t, It is the concentrated resistance equivalent to the entire length of the line.

[0047] In this embodiment, two sections of lossless uniform transmission lines are connected in series with four concentrated resistors to perform equivalent to the lossy transmission line, thereby improving the accuracy of the line equivalent model. The time domain model is as follows: Figure 8 As shown, the time domain expression of the lossy transmission line model is: In the formula, for Time to The middle moment of time, , for The voltage at the midpoint of the two lossless transmission lines at time, for The current at the midpoint of two lossless transmission lines at time t.

[0048] Equations (24) to (27) respectively represent the corresponding relationship between the voltage and current on both sides of the line at different times. By simultaneously eliminating the variables at the intermediate time, the first lossy transmission line time domain model can be obtained as follows: In the formula, is the time-domain model of the first lossy transmission line, is the wave impedance, is the history term, is the voltage value at the first side at time t, is the lumped resistance equivalent to the full length of the line; The time-domain model of the second lossy transmission line is: In the formula, is the time-domain model of the second lossy transmission line, is the wave impedance, is the history term, is the voltage value at the second side at time t, is the lumped resistance equivalent to the full length of the line.

[0049] Both Equation (28) and Equation (29) are time-domain expressions of a lossy transmission line equivalent to two lossless uniform transmission lines in series with four lumped resistances. Among them, Equation (28) calculates the current value at the current moment on the side using the historical values of the electrical quantities on both sides of the line, while Equation (29) calculates the current value at the current moment on the side using the historical values of the electrical quantities on both sides of the line. The above time-domain expressions of the lossy transmission line can be used for parameter identification and research on new protection principles.

[0050] S103: According to the time-domain model of the first lossy transmission line and the time-domain model of the second lossy transmission line, construct a fitness objective function. Based on the fitness objective function, use the electrical quantity information on both sides of the lossy transmission line model to perform grouped iterative optimization on the parameters to be identified, and obtain the final identification result. Among them, the parameters to be identified include wave impedance, lumped resistance, and traveling wave transmission duration.

[0051] In this embodiment, one of the cores of the particle swarm optimization algorithm lies in the construction of the fitness objective function. Through the above-derived lossy transmission line equation, the current value at any position on the line at the current moment can be calculated using the electrical quantity values on both sides of the line, and a suitable objective function can be constructed. Then, using the proposed traveling wave parameter identification method based on the improved particle swarm algorithm, the traveling wave parameters to be identified , and are divided into two groups for cyclic iterative optimization. The identification dimension is reduced, and at the same time, the optimization difficulty of the algorithm is also reduced, and the final identification result is obtained.

[0052] In one embodiment, according to the time-domain model of the first lossy transmission line and the time-domain model of the second lossy transmission line, constructing a fitness objective function includes: Determine the midpoint of a lossless uniform transmission line, and use the midpoint to divide the lossless uniform transmission line into two segments to obtain the first segment of the line and the second segment of the line; The first - stage line and the second - stage line are respectively simplified and equivalent using a lossy transmission line model to obtain a first time - domain expression and a second time - domain expression. Among them, the first time - domain expression is: In the formula, is the current value at the first - side point at time t, is the voltage value at the first - side point at time t, is the time for the traveling wave to propagate from the first - side point to the mid - point, , is a historical term and can be calculated based on the current and voltage sampling values at the point and the mid - point before time; The second time - domain expression is: In the formula, is the current value at point F at time t, is the voltage value at point F at time t, is the time for the traveling wave to propagate from the first - side point to the mid - point, , is a historical term and can be calculated based on the current and voltage sampling values at the point and point F before time; The first time - domain expression and the second time - domain expression are respectively adjusted to obtain an adjusted first time - domain expression and an adjusted second time - domain expression; Based on the adjusted first time - domain expression and the adjusted second time - domain expression, a fitness objective function is obtained. Among them, the fitness objective function is: In the formula, is the number of sampling points used in the improved particle swarm algorithm, is the wave impedance, is the lumped resistance equivalent to the full length of the line, is the time for the traveling wave to propagate from the first - side point to the mid - point.

[0053] In this embodiment, the Karenbauer transformation matrix is used for phase - mode transformation, transforming the A - B - C phases in the phase domain into the 0 - 1 - 2 modes in the mode domain. Subsequent analyses, unless otherwise specified, all represent the 1 - mode. For example: In the formula, is the value after the phase-mode transformation.

[0054] Taking Figure 8 the uniformly distributed transmission line shown as an example, assuming that F is the midpoint of the line, a uniformly distributed transmission line is divided into two parts, and a model of two lossless uniformly distributed transmission lines in series with four lumped resistors is used to simplify and equivalent the first line segment k-F and the second line segment F-m. Taking the first line segment k-F as an example, the time-domain expressions are written according to Eqs. (28) and (29): where is the current value at the first side at time t, is the voltage value at the first side at time t, is the time for the traveling wave to propagate from the first side to the midpoint, , is the current value at point F at time t, is the voltage value at point t at time t, is the time for the traveling wave to propagate from the first side to the midpoint, , is the historical term, which can be calculated according to the current and voltage sampling values at point and F two points before time and can be calculated according to the current and voltage sampling values at

[0055] It should be noted that the first side refers to the k side, and the second side refers to the m side.

[0056] By combining Eqs. (31) and (32), will be eliminated, and the voltage value at point F can be calculated through the electrical quantity information of the k-side line in Eq. (33). Similarly, the voltage value at point F can be calculated through the electrical quantity information of the m-side line in Eq. (34). is the voltage value at the first side at point at time is the voltage value at the first side at point at time is the voltage value at the second side at point at time is the voltage value at the first side at point at time For the first side point The current value at the moment, For the first side point The current value at the moment, For the second side point The current value at the moment, For the first side point Current value at the moment.

[0057] Combining equation (33) and equation (34), we can get , and Function . Functions in multiple time sections The minimum sum of squares is the optimization goal, and the fitness objective function of the particle swarm optimization algorithm is set as: In the formula, To improve the number of sampling points used by the particle swarm algorithm, is the wave impedance, is the concentrated resistance equivalent to the entire length of the line, For the traveling wave from the first side The time it takes for a point to propagate to the midpoint.

[0058] It should be noted that the traveling wave transmission time The larger probability is not an integer, and linear interpolation is needed to reduce the calculation error.

[0059] According to the fitness objective function set in formula (37), the electrical values ​​on both sides of the line are used to treat the identification parameters , and Perform iterative optimization.

[0060] In one embodiment, the electrical quantity information on both sides of the lossy transmission line model is used to perform iterative optimization on the parameters to be identified in groups to obtain the final identification result, including: The voltage and current on both sides are decoupled using the Karenbauer phase mode conversion matrix to obtain the decoupled voltage and current values; Dividing the parameters to be identified into two groups, obtaining a first group of parameters to be identified and a second group of parameters to be identified; Taking the first group of parameters to be identified as known quantities, updating the fitness objective function to obtain a first fitness objective function, and iteratively identifying the second group of parameters to be identified according to the first fitness objective function and the decoupled voltage and current values ​​to obtain a first identification result; Taking the first identification result as a known quantity, update the fitness objective function to obtain a second fitness objective function, and perform iterative identification on the first set of parameters to be identified according to the second fitness objective function to obtain a second identification result; Determine whether the first identification result and the second identification result meet the preset conditions. If they meet, determine the first identification result and the second identification result as the final identification results. If they do not meet, continue with iterative identification.

[0061] In this embodiment, is defined as the first set of parameters, and is defined as the second set of parameters. In each round of optimization process, only one set of parameters (the first set or the second set) is identified first, and then the result obtained from the previous step of identification is used as the initial condition to cyclically identify the other set of parameters, so that the identification result continuously approaches and converges to the solution of Equation (35).

[0062] First, take the wave impedance as a known quantity, and identify the second set of parameters and . A reasonable initial value of the wave impedance helps to improve the optimization speed and accuracy of the algorithm. For a uniformly transposed transmission line model with bundled conductors at the 220 kV voltage level, usually the inductive reactance value is one order of magnitude higher than the resistance value. It is reasonable to approximately use the calculated at 50 Hz steady state as the initial value of the characteristic impedance of the lossless line.

[0063] In the optimization process of the proposed improved particle swarm algorithm, it is necessary to consider the boundaries of the positions and velocities of the parameters to be identified, and reduce the probability of the appearance of non-expected solutions through reasonable boundary constraint conditions. For the wave impedance , its initial value can be calculated according to Equation (38). Taking a 100 km AC line as an example, its position coordinate boundary condition is -10, +10], and the velocity boundary condition is [-0.01, 0.01]; for the concentrated resistance of the uniformly transposed transmission line, taking a 100 km AC line as an example, its position coordinate boundary condition is [0, 10], and the velocity boundary condition is [-0.01, 0.01]; for the traveling wave transmission time , taking a 100 km AC line as an example, with the traveling wave transmission speed of 300 km / ms and the sampling frequency of 5 kHz, its position coordinate boundary condition is [0, 1], and the velocity boundary condition is [-0.01, 0.01].

[0064] The overall flow of the traveling wave parameter identification scheme based on the improved particle swarm algorithm is as shown in Figure 10As shown below, the specific process is described as follows: (1) Use the Karenbauer phase conversion matrix to decouple the voltage and current on both sides of the line to obtain the wave impedance of the lossless transmission line Taking this as the initial value, the fitness objective function can be expressed as: In the formula, is the number of sampling points used in the improved particle swarm optimization algorithm, is the lumped resistance equivalent to the full length of the line, is the time for the traveling wave to propagate from the first side point to the midpoint.

[0065] The identified lumped resistance of the uniform transmission line and the traveling wave transmission time , the variables of the fitness objective function change from 3 to 2, and the identification dimension drops from three-dimensional to two-dimensional, reducing the optimization difficulty of the algorithm; (2) Take the and identified in step (1) as known quantities and then identify the characteristic impedance. At this time, the fitness objective function can be expressed as: In the formula, is the number of sampling points used in the improved particle swarm optimization algorithm, is the lumped resistance equivalent to the full length of the line, is the time for the traveling wave to propagate from the first side point to the midpoint.

[0066] The variables of the fitness objective function change from 3 to 1, and the identification dimension drops from three-dimensional to one-dimensional, further obtaining the identification result of the characteristic impedance of the lossless transmission line . The first round of parameter identification is completed, and the identification results are respectively , and ; (3) Repeat the above process, and the parameters obtained from each identification are used as known quantities for the next identification. If there is no obvious change in the q-th round of parameter identification results compared with the (q - 1)-th round of identification results, stop the identification process; otherwise, continue the iterative optimization and use the results of the last round as the final parameter identification values.

[0067] In one embodiment, the preset condition is whether the difference between the currently iterated identification result and the previous iterated identification result is less than the preset value.

[0068] In this embodiment, if there is no obvious change in the parameter identification result of the q-th round compared with that of the (q-1)-th round, the identification process is stopped, that is, whether the difference between the currently iterated identification result and the previous iterated identification result is less than a preset value, and the preset value is preferably 1%.

[0069] To verify the feasibility of the proposed traveling wave parameter identification scheme based on the improved particle swarm optimization algorithm, a large-scale new energy power station outgoing system as shown in Figure 11 is established in PSCAD. The rated voltage of the AC line is 220 kV, and a full-power inverter station is selected for the new energy power station with a rated power of 450 MW.

[0070] The AC line is determined as the object of parameter identification, the line length is 100 km, the line head is named the power station side (r side), the line end is named the system side (g side), the sampling frequency is 5 kHz, and the particle scale = 2000 during the optimization process of the particle swarm algorithm, the maximum number of iterations per round = 10000, and the maximum number of iteration rounds = 20.

[0071] Using the proposed parameter identification scheme, the parameters of the AC line in the large-scale new energy outgoing system as shown in Figure 11 are identified to verify the accuracy of the proposed parameter identification method. The traveling wave parameter identification result based on the improved particle swarm algorithm is as shown in Figures 12 - 14 shown. Figure 12 is the identification result of the wave impedance . Through five rounds of iterative identification by the particle swarm algorithm, the identification accuracy of has been greatly improved. Among them, the identification value of in the fifth round is 231.891 Ω, and the identification accuracy reaches 99.5%, which can accurately identify

[0072] Figure 13 is the identification result of the equivalent concentrated resistance . Through five rounds of iterative identification by the particle swarm algorithm, the identification accuracy of has been greatly improved. Among them, the identification value of in the fifth round is 1.0712 Ω, and the identification accuracy reaches 99.4%, which can accurately identify

[0073] Figure 14 is the identification result of the transmission duration . Through five rounds of iterative identification by the particle swarm algorithm, the identification accuracy of The identification value is 0.1685 ms, and the identification accuracy reaches 99.6%, which can identify relatively accurately .

[0074] It can be seen from the above analysis that the traveling wave parameters identified based on the improved particle swarm optimization algorithm 、 and all have good accuracy. The parameter identification results of each round of cyclic iteration are shown in Table 1. After the fifth round of iterative optimization, the identified parameters tend to be stable, and the relative error is less than 1%, verifying that the proposed traveling wave parameter identification scheme has high accuracy.

[0075] Table 2 compares the parameter identification accuracies of the standard particle swarm optimization algorithm and the proposed improved particle swarm optimization algorithm. It can be seen that by optimizing the different parameter groups through cyclic iteration, the dimension of the identified parameters is reduced, and the proposed improved particle swarm optimization algorithm has higher accuracy than the standard particle swarm optimization algorithm.

[0076] Table 1 Calculation results of traveling wave parameters based on the improved particle swarm optimization algorithm Table 2 Comparison results of the accuracy of the particle swarm optimization algorithm The reliability of the proposed traveling wave parameter identification scheme is verified by the parameter identification results under simulation noise interference. A 30 dB noise signal is superimposed on the measurement data on both sides of the AC line, and the line parameter identification results are shown in Table 3.

[0077] It can be seen from Table 3 that under the interference of a 30 dB noise signal, the accuracy of the first-round parameter identification is low, and the identification accuracy of the equivalent line concentrated resistance is only 82.1%; however, through multiple cyclic iteration optimizations, the accuracy of the fifth-round parameter identification is significantly improved, and the accuracies of the three parameters to be identified are all higher than 97%. Comparing Table 2 and Table 3, the accuracy of the AC line parameter identification method proposed in the present invention is affected by noise interference, but the identification accuracy still meets the requirements for protection use.

[0078] Table 3 Calculation results of the proposed parameter identification scheme under noise interference To further verify the feasibility of the proposed traveling wave parameter identification scheme, it is also necessary to verify the accuracy of the time-domain transmission line model considering losses established for Equations (28) and (29). Using the parameter identification results in this chapter, a lossy transmission line model is established in PSCAD to simulate the electrical quantity values of a large-scale new energy transmission system under different AC line models. By comparing the voltages and currents of different line models, the correctness of the proposed time-domain transmission line model is verified, and the specific simulation results are as Figure 15 and Figure 16 shown.

[0079] Figure 15 This is the comparison result of the line voltage waveforms between the proposed parameter identification model, the frequency-variable parameter model, and the Berreman model. It can be seen that the voltage waveforms of the proposed parameter identification model, the frequency-variable parameter model, and the Berreman model almost completely overlap. The maximum relative error appears at the peaks and valleys of the waveform, and the maximum relative error does not exceed 1.3%.

[0080] Figure 16 This is the comparison result of the line terminal current waveforms between the proposed parameter identification model, the frequency-variable parameter model, and the Berreman model. It can be seen that the current waveforms of the proposed parameter identification model, the frequency-variable parameter model, and the Berreman model almost completely overlap. The maximum relative error appears at the peaks and valleys of the waveform, and the maximum relative error does not exceed 1.2%. It can be seen that the proposed time-domain model of the transmission line considering losses has high accuracy and can be used to improve the particle swarm optimization algorithm for line traveling wave parameter identification.

[0081] In the time domain, the present invention constructs a system of linear ordinary differential equations for different network elements and lossless transmission lines through the central difference method. According to the traveling wave transmission characteristics, the time-domain model of the lossy uniform transmission line is derived, which has higher accuracy than the traditional lumped parameter line model. Moreover, an improved particle swarm optimization algorithm is proposed, which uses the instantaneous values of electrical quantities at multiple time sections to group and iteratively optimize the parameters to be identified, reducing the variable dimension in the iterative optimization process and improving the accuracy of parameter identification. The relative error of the identified parameters is less than 1%.

[0082] Furthermore, the present invention can online identify the traveling wave parameters of AC lines, and the relevant parameters can be used for the research of modern protection principles and control strategies, providing parameter support for the development of new technologies.

[0083] The online traveling wave parameter identification system 1700 for AC transmission lines provided by the embodiment of the present invention, as Figure 17 shown, Figure 17 is a block diagram of the online traveling wave parameter identification system for AC transmission lines, including: The first construction module 1701 is used to construct the time-domain model of the network elements of the AC transmission line to be identified and the time-domain model of the lossless uniform transmission line; The second construction module 1702 is used to connect two sections of lossless uniform transmission lines in series with multiple lumped resistors to obtain the lossy transmission line model of the AC line to be measured, and obtain the time-domain model of the lossy transmission line according to the time-domain models of the lossless uniform transmission lines of each lossless uniform transmission line, where the time-domain model of the lossy transmission line includes the first time-domain model of the lossy transmission line and the second time-domain model of the lossy transmission line; The identification module 1703 is configured to construct a fitness objective function according to the first lossy transmission line time-domain model and the second lossy transmission line time-domain model. Based on the fitness objective function, the electrical quantity information on both sides of the lossy transmission line model is used to perform grouped iterative optimization on the parameters to be identified, and the final identification result is obtained. The parameters to be identified include wave impedance, concentrated resistance, and traveling wave transmission duration.

[0084] In one embodiment, the first construction module 1701 includes a time-domain model construction unit, where The time-domain model construction unit is configured to use the central difference method to construct a resistor element time-domain model, an inductor element time-domain model, a capacitor element time-domain model, a series time-domain model, and a lossless uniform transmission line time-domain model. The series time-domain model is a time-domain model of a resistor and an inductor in series. The lossless uniform transmission line time-domain model is: In the formula, is the historical term, is the wave impedance, is the voltage at time t, is the current at time t, is the voltage before is the current before

[0085] In one embodiment, the second construction module 1702 includes a lossy transmission line time-domain model construction unit, where The lossy transmission line time-domain model construction unit is configured to obtain the lossy transmission line time-domain model according to the lossless uniform transmission line time-domain models of each lossless uniform transmission line. The first lossy transmission line time-domain model is: In the formula, is the first lossy transmission line time-domain model, is the wave impedance, is the historical term, is the voltage value on the first side at time, is the concentrated resistance equivalent to the full length of the line; The second lossy transmission line time-domain model is: In the formula, is the second lossy transmission line time-domain model, is the wave impedance, is the historical term, is the voltage value on the second side at time, is the concentrated resistance equivalent to the full length of the line.

[0086] The specific implementation manner of the on-line identification system for traveling wave parameters of AC transmission lines is basically the same as the specific embodiment of the above-mentioned method for on-line identification of traveling wave parameters of AC transmission lines, and will not be described in detail here.

[0087] In an embodiment of the present application, a computer device is provided. The computer device includes a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the above steps are implemented; the computer device provided in this embodiment has the same implementation principle and technical effects as the above method embodiment, and will not be described in detail here.

[0088] In an embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the above steps are implemented; the computer-readable storage medium provided in this embodiment has the same implementation principle and technical effects as the above method embodiment, and will not be described in detail here.

[0089] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered that the scope described in this specification.

[0090] The specific embodiments described above have further elaborated on the purpose, technical solutions, and beneficial effects of the present invention. It should be understood that the above description is only specific embodiments of the present invention and is not used to limit the protection scope of the present invention. In particular, it is pointed out that for those skilled in the art, any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An online identification method for traveling wave parameters of an AC transmission line, characterized in that: include: Construct the time domain model of network components and lossless uniform transmission line of the AC transmission line to be identified; Connecting two sections of lossless uniform transmission lines in series with a plurality of concentrated resistors to obtain a lossy transmission line model of the AC line to be tested, and obtaining a lossy transmission line time domain model according to the lossless uniform transmission line time domain models of each of the lossless uniform transmission lines, wherein the lossy transmission line time domain model includes a first lossy transmission line time domain model and a second lossy transmission line time domain model; According to the first lossy transmission line time domain model and the second lossy transmission line time domain model, a fitness objective function is constructed. Based on the fitness objective function, the electrical quantity information on both sides of the lossy transmission line model is used to perform grouped iterative optimization on the parameters to be identified to obtain a final identification result, wherein the parameters to be identified include wave impedance, concentrated resistance and traveling wave transmission time.

2. The method for online identification of traveling wave parameters of an AC transmission line according to claim 1, characterized in that: The method of constructing a network element time domain model of the AC transmission line to be identified and a lossless uniform transmission line time domain model comprises: The central difference method is used to construct a time domain model of a resistor element, a time domain model of an inductor element, a time domain model of a capacitor element, a series time domain model and a lossless uniform transmission line time domain model, wherein the series time domain model is a time domain model of a resistor and an inductor in series, and the lossless uniform transmission line time domain model is: In the formula, For historical items, is the wave impedance, is the voltage at time t, is the current at time t, for The voltage before time, for Current before time.

3. The method for online identification of traveling wave parameters of an AC transmission line according to claim 1, characterized in that: The step of obtaining a lossy transmission line time domain model according to the lossless uniform transmission line time domain model of each lossless uniform transmission line comprises: A lossy transmission line time domain model is obtained according to the lossless uniform transmission line time domain model of each lossless uniform transmission line, wherein the first lossy transmission line time domain model is: In the formula, is the time domain model of the first lossy transmission line, is the wave impedance, For historical items, is the voltage value of the first side at time t, It is the concentrated resistance equivalent to the entire length of the line; The time domain model of the second lossy transmission line is: In the formula, is the time domain model of the second lossy transmission line, is the wave impedance, For historical items, is the voltage value of the second side at time t, It is the concentrated resistance equivalent to the entire length of the line.

4. The method for online identification of traveling wave parameters of an AC transmission line according to claim 1, characterized in that: The constructing a fitness objective function according to the first lossy transmission line time domain model and the second lossy transmission line time domain model comprises: Determine a midpoint of a section of lossless uniform transmission line, and use the midpoint to divide the section of lossless uniform transmission line into two sections to obtain a first section and a second section; The first section of the line and the second section of the line are simplified and equalized respectively by using a lossy transmission line model to obtain a first time domain expression and a second time domain expression, wherein the first time domain expression is: In the formula, For the first side The current value at point t is For the first side The voltage value at point t, For the traveling wave from the first side The time it takes for a point to propagate to the midpoint, , For historical items, you can Before time The current and voltage sampling values ​​of the point and midpoint are calculated; The second time domain expression is: In the formula, is the current value at point F at time t, for The voltage value at point t, For the traveling wave from the first side The time it takes for a point to propagate to the midpoint, , For historical items, you can Before time The current and voltage sampling values ​​at points A and F are obtained by calculation; Adjusting the first time domain expression and the second time domain expression respectively to obtain an adjusted first time domain expression and an adjusted second time domain expression; According to the adjusted first time domain expression and the adjusted second time domain expression, a fitness objective function is obtained, wherein the fitness objective function is: In the formula, To improve the number of sampling points used by the particle swarm algorithm, is the wave impedance, is the concentrated resistance equivalent to the entire length of the line, For the traveling wave from the first side The time it takes for a point to propagate to the midpoint.

5. The method for online identification of traveling wave parameters of AC transmission lines according to claim 1, characterized in that: The method of using the electrical quantity information on both sides of the lossy transmission line model to perform iterative optimization on the parameters to be identified in groups to obtain the final identification result includes: The voltage and current on both sides are decoupled using the Karenbauer phase mode conversion matrix to obtain the decoupled voltage and current values; Dividing the parameters to be identified into two groups to obtain a first group of parameters to be identified and a second group of parameters to be identified; Taking the first group of parameters to be identified as known quantities, updating the fitness objective function to obtain a first fitness objective function, and iteratively identifying the second group of parameters to be identified according to the first fitness objective function and the decoupled voltage and current values ​​to obtain a first identification result; Taking the first identification result as a known quantity, updating the fitness objective function to obtain a second fitness objective function, and iteratively identifying the first group of parameters to be identified according to the second fitness objective function to obtain a second identification result; It is determined whether the first identification result and the second identification result meet a preset condition. If so, the first identification result and the second identification result are determined to be final identification results. If not, iterative identification is continued.

6. The method for online identification of traveling wave parameters of an AC transmission line according to claim 5, characterized in that: The first group of parameters to be identified includes wave impedance. When the first group of parameters to be identified is used as a known quantity, it includes: Calculate the initial value of the wave impedance, wherein the initial value of the wave impedance is calculated as follows: In the formula, is the initial value of wave impedance in the particle swarm algorithm, Indicates the electrical value at a frequency of 50 Hz.

7. The method for online identification of traveling wave parameters of an AC transmission line according to claim 5, characterized in that: The preset condition is whether the difference between the identification result obtained in the current iteration and the identification result obtained in the previous iteration is less than a preset value.

8. An online identification system for traveling wave parameters of AC transmission lines, characterized in that: include: The first construction module is used to construct a network component time domain model and a lossless uniform transmission line time domain model of the AC transmission line to be identified; A second construction module is used to connect two sections of lossless uniform transmission lines in series with a plurality of concentrated resistors to obtain a lossy transmission line model of the AC line to be tested, and to obtain a lossy transmission line time domain model according to the lossless uniform transmission line time domain models of each of the lossless uniform transmission lines, wherein the lossy transmission line time domain model includes a first lossy transmission line time domain model and a second lossy transmission line time domain model; The identification module is used to construct a fitness objective function according to the first lossy transmission line time domain model and the second lossy transmission line time domain model. Based on the fitness objective function, the electrical quantity information on both sides of the lossy transmission line model is used to group and iteratively optimize the parameters to be identified to obtain the final identification result, wherein the parameters to be identified include wave impedance, concentrated resistance and traveling wave transmission time.

9. The AC transmission line traveling wave parameter online identification system according to claim 8, characterized in that: The first building module includes a time domain model building unit, wherein: The time domain model construction unit is used to construct a resistance element time domain model, an inductance element time domain model, a capacitance element time domain model, a series time domain model and a lossless uniform transmission line time domain model by using a central difference method, wherein the series time domain model is a time domain model of a resistor and an inductor in series, and the lossless uniform transmission line time domain model is: In the formula, For historical items, is the wave impedance, is the voltage at time t, is the current at time t, for The voltage before time, for Current before time.

10. The AC transmission line traveling wave parameter online identification system according to claim 8, characterized in that: The second building module includes a lossy transmission line time domain model building unit, wherein: The lossy transmission line time domain model construction unit is used to obtain a lossy transmission line time domain model according to the lossless uniform transmission line time domain model of each lossless uniform transmission line, wherein the first lossy transmission line time domain model is: In the formula, is the time domain model of the first lossy transmission line, is the wave impedance, For historical items, is the voltage value of the first side at time t, It is the concentrated resistance equivalent to the entire length of the line; The time domain model of the second lossy transmission line is: In the formula, is the time domain model of the second lossy transmission line, is the wave impedance, For historical items, is the voltage value of the second side at time t, It is the concentrated resistance equivalent to the entire length of the line.

11. A computer device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the method for online identification of traveling wave parameters of an AC transmission line as claimed in any one of claims 1 to 7 when executing the computer program.

12. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the steps of the method for online identification of traveling wave parameters of an AC transmission line as claimed in any one of claims 1 to 7 are implemented.

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