Short-line power distribution network parallel simulation method and device based on long transmission delay, equipment and medium

Abstract

The invention relates to the technical field of power distribution network parallel simulation, in particular to a short-line power distribution network parallel simulation method and device based on long transmission delay, equipment and a medium, and the method comprises the steps: building a Bergeron decoupling model of a short-line power distribution network based on distribution parameter characteristics; according to the Bergeron decoupling model, in an error allowable range, increasing a capacitance parameter value of a line, prolonging transmission delay of a signal on the line, and reducing an interpolation error of a historical current source item; fault simulation is carried out under the situation of the short-line power distribution network, and the accuracy and effectiveness of the method are verified; compared with a traditional Bergeron line decoupling model, the method has the advantages that the signal transmission time is prolonged and the interpolation error in a traditional model is reduced while the line length is not changed, so that the problem that the linear interpolation error is relatively large when the traditional Bergeron model is applied to a short line scene can be reduced, and the simulation precision is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of parallel simulation of distribution networks, and particularly to a parallel simulation method, device, equipment and medium for short-line distribution networks based on long transmission delays. Background Art

[0002] The power grid is continuously transforming towards an intelligent power grid with new energy as the main body, and the access ratio of new energy will continue to rise. In the future, the characteristics of the new power system will become more and more prominent, specifically manifested as the "dual high" situation of high proportion of new energy and high proportion of power electronic devices, and the network architecture tends to be complex, thus posing higher requirements for the accuracy and complexity of system simulation.

[0003] To improve the simulation efficiency, the parallel multi-rate simulation method is one of the current research trends. Generally speaking, the Bergeron model can divide a large system into multiple subsystems by using the propagation characteristics of wave functions, so as to achieve parallel simulation. However, when this model is applied to distribution networks with shorter distances, it often leads to larger simulation errors. How to improve the simulation accuracy of the Bergeron line model in short-line distribution networks is worthy of in-depth study.

[0004] The information disclosed in this background art section is only intended to deepen the understanding of the overall background art of the present invention, and should not be regarded as an admission or any form of suggestion that this information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0005] The present invention provides a parallel simulation method, device, equipment and medium for short-line distribution networks based on long transmission delays, thus effectively solving the problems in the background art.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is: a parallel simulation method for short-line distribution networks based on long transmission delays, including the following steps:

[0007] S10: Based on the distributed parameter characteristics, establish a Bergeron decoupling model for the short-line distribution network;

[0008] S20: According to the Bergeron decoupling model, within the allowable error range, increase the capacitance parameter value of the line, extend the transmission delay of the signal on the line, and reduce the interpolation error of the historical current source term;

[0009] S30: Conduct fault simulation in the short-line distribution network scenario to verify the accuracy and effectiveness of the proposed method.

[0010] Further, in step S10, based on the distributed parameter characteristics, establishing a Bergeron decoupling model for the short-line distribution network, the steps include:

[0011] S11: Establish a distributed parameter transmission line model according to Kirchhoff's law of the distributed parameter transmission line;

[0012] S12: Simplify the distributed parameter transmission line model by ignoring the unit resistance and conductance of the line to obtain a partial differential equation set;

[0013] S13: Considering the propagation characteristics of the wave function, solve the partial differential equation set to obtain the voltage and current relationship model at the beginning and end of the line of the Bergeron decoupling model, and calculate the wave impedance and transmission delay of the line.

[0014] Further, in step S11, the distributed parameter transmission line model includes:

[0015]

[0016] Where x is the distance from the beginning k of the line to the differential unit dx, u and i are respectively the voltage and current magnitudes at x, and R, L, G, and C are respectively the unit resistance, inductance, conductance, and capacitance of the line.

[0017] Further, in step S13, the voltage and current relationship model at the beginning and end of the line of the Bergeron decoupling model includes:

[0018]

[0019] Where u k , i km are respectively the voltage and current at the beginning of the line, u m , i mk are respectively the voltage and current at the end of the line, Z C is the wave impedance, τ is the time required for the signal to propagate from the beginning k of the line to the end m, I k (t - τ), I m (t - τ) are historical current source terms.

[0020] Further, in step S13, the model for calculating the wave impedance and transmission delay of the line includes:

[0021]

[0022] Where Z C is the wave impedance, τ is the transmission delay of the short line, l is the line length, and L and C are respectively the unit inductance and capacitance of the line.

[0023] Further, in step S20, according to the Bergeron decoupling model, within the allowable error range, increase the capacitance parameter value of the line, extend the transmission delay of the signal on the line, and reduce the interpolation error of the historical current source term. The steps include:

[0024] S21: Within the allowable error range, adjust the unit capacitance parameter value of the line to the capacitance correction value so that the corrected transmission delay meets the requirement of being greater than the simulation step size. The model of the corrected transmission delay includes:

[0025]

[0026] In the formula, τ * is the corrected transmission delay, l is the line length, L is the unit inductance of the line, C * is the adjusted capacitance correction value, and h is the simulation step size;

[0027] S22: According to the adjusted capacitance correction value, verify whether the adjusted simulation error is controlled within the preset range.

[0028] Further, in step S22, verifying whether the adjusted simulation error is controlled within the preset range, the model includes:

[0029]

[0030] In the formula, ε(t) is the current error flowing through the line when the unit capacitance changes from C to C * ; i km is the current at the head end of the line, is the current at the head end of the line after parameter correction, τ and Z C are the transmission delay and characteristic impedance of the line respectively, τ * , are the transmission delay and characteristic impedance of the line after parameter correction respectively, λ(τ) is the delay coefficient, and u k is the voltage and current at the head end of the line.

[0031] Further, in step S30, in the established distribution network model with a voltage level of 4.16 kV and a decoupled line length of 10 km, set the single-phase grounding fault conditions that often occur to verify the accuracy and effectiveness of the present invention.

[0032] The present invention also includes a short-line distribution network parallel simulation device based on long transmission delay. Using the method as described above, it includes:

[0033] A model building unit for building a Bergeron decoupling model of a short-line distribution network based on distributed parameter characteristics;

[0034] A capacitance adjustment unit for increasing the capacitance parameter value of the line within the allowable error range according to the Bergeron decoupling model, extending the transmission delay of the signal on the line, and reducing the interpolation error of the historical current source term;

[0035] A simulation verification unit is used to perform fault simulation in the scenario of a short-line distribution network to verify the accuracy and effectiveness of the proposed method.

[0036] The present invention further includes a computer device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above-mentioned method is implemented.

[0037] The present invention further includes a storage medium, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned method is implemented.

[0038] The beneficial effects of the present invention are as follows:

[0039] Compared with the traditional Bergeron line decoupling model, the present invention provides a parallel simulation method for short-line distribution networks based on long transmission delays. While ensuring the line length remains unchanged, it extends the signal transmission time, reduces the interpolation error in the traditional model, and thus can reduce the problem of large linear interpolation errors when the traditional Bergeron model is applied to short-line scenarios, improving the simulation accuracy. Description of the Drawings

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0041] Figure 1 It is a flowchart of a parallel simulation method for short-line distribution networks based on long transmission delays;

[0042] Figure 2 It is a distributed parameter diagram of a single conductor;

[0043] Figure 3 It is a topological diagram of the IEEE 13-node system in Embodiment 2;

[0044] Figure 4 It is a simulation verification waveform diagram in Embodiment 2;

[0045] Figure 5 It is a structural schematic diagram of a parallel simulation device for short-line distribution networks based on long transmission delays;

[0046] Figure 6 It is a structural schematic diagram of a computer device. Detailed Embodiments

[0047] 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.

[0048] Embodiment 1:

[0049] As Figure 1 shown: A parallel simulation method for a short-line distribution network based on long transmission delay includes the following steps:

[0050] S10: Based on the distributed parameter characteristics, establish a Bergeron decoupling model for the short-line distribution network;

[0051] S20: According to the Bergeron decoupling model, within the allowable error range, increase the capacitance parameter value of the line, extend the transmission delay of the signal on the line, and reduce the interpolation error of the historical current source term;

[0052] S30: Conduct fault simulation in the short-line distribution network scenario to verify the accuracy and effectiveness of the proposed method.

[0053] Compared with the traditional Bergeron line decoupling model, the present invention patent provides a parallel simulation method for a short-line distribution network based on long transmission delay. While keeping the line length unchanged, it extends the signal transmission time, reduces the interpolation error in the traditional model, thereby reducing the problem of large linear interpolation error when the traditional Bergeron model is applied to the short-line scenario and improving the simulation accuracy.

[0054] By increasing the capacitance parameter, the transmission delay of the short line is extended, solving the interpolation error problem caused by the transmission delay approaching the simulation step size in the short-line scenario of the Bergeron model, thereby significantly improving the simulation accuracy of the model; the traditional Bergeron decoupling model performs well in the long-line scenario but has a large error in the short-line scenario; by optimizing the capacitance parameter, the adjusted Bergeron decoupling model can be applied to the short-line scenario, expanding the application range of the model.

[0055] This method only optimizes the model by adjusting the capacitance parameter, avoiding changes to the line length or other complex parameters, with the characteristics of low implementation difficulty and strong engineering applicability, and at the same time does not affect the simulation efficiency; by setting a fault scenario in the short-line distribution network scenario, the accuracy and effectiveness of the optimized model are verified, ensuring the application value of this method in the actual power system.

[0056] With the increase in the proportion of new energy access, the short-line distribution network is becoming increasingly important in the power system. The high-precision simulation ability of this method can better support the complex power grid environment with a high proportion of new energy, providing reliable simulation support for power system planning and operation.

[0057] As a preference of the above embodiments, in step S10, based on the characteristics of distribution parameters, a Bergeron decoupling model of a short-line distribution network is established, and the steps include:

[0058] S11: Establish a distributed parameter transmission line model according to Kirchhoff's law of the distributed parameter transmission line;

[0059] S12: Simplify the distributed parameter transmission line model by ignoring the unit resistance and conductance of the line to obtain a partial differential equation set;

[0060] S13: Considering the propagation characteristics of the wave function, solve the partial differential equation set to obtain the voltage and current relationship model at the beginning and end of the line of the Bergeron decoupling model, and calculate the wave impedance and transmission delay of the line.

[0061] In the Bergeron decoupling model, by simplifying the model (ignoring resistance and conductance), the computational complexity is reduced. At the same time, by solving the partial differential equation set and calculating the wave impedance and transmission delay, the physical characteristics of the model are ensured to be accurate. This method reduces unnecessary calculations while ensuring the simulation accuracy, making the simulation more efficient. By calculating the wave impedance and transmission delay, the consistency of the propagation characteristics of voltage and current in the model is ensured. The accurate calculation of the transmission delay and the correct solution of the wave impedance are the keys to the propagation of current and voltage, which ensures that the model can effectively reflect the actual physical behavior of the power system during the simulation process.

[0062] In this embodiment, in step S11, as Figure 2 shown, a distributed parameter transmission line model can be established according to Kirchhoff's law, including:

[0063]

[0064] In the formula, x is the distance from the beginning k of the line to the differential unit dx, u and i are the voltage and current magnitudes at x respectively, and R, L, G, and C are the unit resistance, inductance, conductance, and capacitance of the line respectively.

[0065] By using the distributed parameter model to describe the transmission line, the variation of voltage and current with distance in the power system can be more accurately reflected; compared with the traditional lumped parameter model, the distributed parameter model can more accurately simulate the propagation characteristics of current and voltage during transmission, so the simulation accuracy can be improved.

[0066] Ignoring the resistance and conductance of the line, take the partial derivatives of the above formula with respect to x respectively;

[0067]

[0068] In the formula, u and i are the voltage and current magnitudes at x respectively, and L and C are the unit inductance and capacitance of the line respectively.

[0069] By establishing a system of partial differential equations, the voltage and current distributions along the line can be accurately described. Especially in the scenario of short lines with long transmission delays, the tiny changes generated during the signal propagation process can be captured.

[0070] Among them, in step S13, the voltage and current relationship model at the beginning and end of the line in the Bergeron decoupling model includes:

[0071]

[0072] In the formula, u k , i km are the voltage and current at the beginning of the line respectively, u m , i mk are the voltage and current at the end of the line respectively, Z C is the wave impedance, τ is the time required for the signal to propagate from point k at the beginning of the line to point m at the end, I k (t - τ), I m (t - τ) are the historical current source terms.

[0073] Through the Bergeron decoupling model, the voltage and current are effectively decoupled between the beginning and end of the line, making the relationship between the current and voltage clearer and accurately reflecting their respective propagation characteristics, avoiding the errors and inaccuracies in the traditional model; by introducing the wave impedance and signal propagation time, this method can more accurately simulate the propagation characteristics of voltage and current on short lines; the traditional model may ignore the delay existing during the signal transmission, while the Bergeron decoupling model can more precisely capture the details of the voltage and current changes over time and position, thus improving the simulation accuracy.

[0074] Considering that when the traditional Bergeron decoupling model is applied to the short line scenario, the main source of error lies in that the value of the historical current term at the moment of (t - τ) often needs to be obtained through an interpolation algorithm, and the transmission delay τ of the short line is very small, and its value is close to the simulation step size h, thus bringing a large interpolation error.

[0075] In this embodiment, in step S13, the model for calculating the wave impedance and transmission delay of the line includes:

[0076]

[0077] In the formula, Z C is the wave impedance, τ is the transmission delay of the short line, l is the line length, and L, C are the unit inductance and capacitance of the line respectively.

[0078] By calculating the wave impedance Z CWith the propagation delay τ, it is possible to more accurately simulate the propagation characteristics of current and voltage in transmission lines. Especially in short-line distribution networks, this accurate calculation can eliminate the errors caused by ignoring these propagation characteristics, thereby improving the accuracy of the simulation.

[0079] As an optimization of the above embodiment, in step S20, according to the Bergeron decoupling model, within the allowable error range, increase the capacitance parameter value of the line, extend the signal transmission delay on the line, and reduce the interpolation error of the historical current source term. The steps include:

[0080] S21: Within the allowable error range, adjust the unit capacitance parameter value of the line to the capacitance correction value so that the corrected transmission delay meets the requirement of being greater than the simulation step size. The model of the corrected transmission delay includes:

[0081]

[0082] In the formula, τ * is the corrected transmission delay, l is the line length, L is the unit inductance of the line, C * is the adjusted capacitance correction value, and h is the simulation step size;

[0083] It can be seen that through parameter transformation, the transmission delay of the line is artificially increased, and the original interpolation error of the Bergeron model is reduced, which is beneficial to improving the simulation accuracy;

[0084] S22: According to the adjusted capacitance correction value, verify whether the adjusted simulation error is controlled within the preset range.

[0085] By adjusting the capacitance parameter of the line to the correction value, the transmission delay of the signal can be effectively extended, so as to better simulate the physical characteristics of the actual signal propagation in the power system. Extending the transmission delay helps to reduce the errors caused by signal propagation delay, ensure that the simulation results are more consistent with the actual system behavior, and thus improve the simulation accuracy.

[0086] To ensure that the line simulation after parameter modification does not affect the overall simulation accuracy of the system, it is necessary to estimate the error of parameter modification in advance. Usually, the Bergeron model can also be expressed as:

[0087]

[0088] In the formula, λ(τ) is the delay coefficient, and λ(τ) = f(t + τ) / f(t), where f(t) is the propagated signal.

[0089] According to the above model, the current i at the head of the line is obtained km and the corrected current Substitute into the following formula:

[0090] In this embodiment, in step S22, it is verified whether the simulation error after adjustment is controlled within a preset range. The model includes:

[0091]

[0092] In the formula, ε(t) is the current error flowing through the line when the unit capacitance changes from C to C * ; i km is the current at the head of the line, is the current at the head of the line after parameter correction, τ, Z C are the transmission delay and characteristic impedance of the line respectively, τ * , are the transmission delay and characteristic impedance of the line after parameter correction respectively, λ(τ) is the delay coefficient, u k is the voltage and current at the head of the line.

[0093] After knowing the input voltage and current signals of the line, the simulation error after parameter change can be calculated according to the above formula. Generally, the error needs to be ensured within 5%. By limiting the simulation error within 5%, the reliability of the adopted model and simulation results in practical applications is ensured. This is an important means to improve the credibility of the power system simulation model. Especially in the scenario of short-line distribution networks, it can accurately simulate the changes in current and voltage, helping system optimization and fault analysis.

[0094] By calculating the current error and adjusting the capacitance and other parameters, it can ensure that the simulation results are closer to the actual situation. By precisely controlling the current error, the simulation results are more in line with the behavior of the actual distribution network. Especially in the case of longer transmission delays or larger capacitance changes, the errors caused by these factors can be avoided.

[0095] Among them, in step S30, in the distribution network model with a built voltage level of 4.16 kV and a decoupled line length of 10 km, the frequently occurring single-phase grounding fault situation is set to verify the accuracy and effectiveness of the present invention, specifically including comparing the error between the simulation results and the actual situation to ensure that the simulation error is controlled within the preset range.

[0096] Embodiment 2:

[0097] The distribution network simulated in this embodiment is the IEEE 13-node system with a voltage level of 4.16 kV and a decoupled line length of 10 km. Its topological structure is as Figure 3 shown, and the parameters of the decoupled line are shown in Table 1.

[0098] Table 1 Parameter values of the decoupled line

[0099]

[0100] Considering the transmission delay of the original line Their values are all less than the simulation step size h = 5×10 -5 s, which may lead to non - convergence of the simulation. To solve this problem, let the new unit capacitance values be: C 1 * = 1.08421663×10 -7 、C 0 * = 5.187060801×10 -8 , and at this time the new transmission delay meets the requirement of τ > h. At the same time, combined with the input voltage and current signals, it can be verified that the line simulation error ε < 5%, meeting the requirements of electromagnetic transient simulation.

[0101] Set a single - phase grounding fault at node 671, with the fault start time being 0.05 s and the end time being 0.07 s. Taking the high - precision Π model in the short - line scenario as the simulation benchmark and the simulation time being 0.15 s, the parallel simulation results of the Bergeron decoupling model before and after parameter improvement are as Figure 4 shown.

[0102] It can be seen that by changing the capacitance parameter value of the line and increasing the signal transmission delay, the simulation accuracy has been greatly improved, which is helpful for the application of the Bergeron decoupling model in the short - line scenario.

[0103] The present invention also includes a short - line distribution network parallel simulation device based on long transmission delay, as Figure 5 shown, using the method as described above, including:

[0104] Establish a model unit for establishing a Bergeron decoupling model of a short - line distribution network based on distributed parameter characteristics;

[0105] A capacitance adjustment unit for increasing the capacitance parameter value of the line within the allowable error range according to the Bergeron decoupling model, extending the signal transmission delay on the line, and reducing the interpolation error of the historical current source term;

[0106] A simulation verification unit for performing fault simulation in the short - line distribution network scenario to verify the accuracy and effectiveness of the proposed method.

[0107] Please refer to Figure 6 the structural schematic diagram of the computer device provided by the embodiment of the present application shown. A computer device 400 provided by the embodiment of the present application includes: a processor 410 and a memory 420. The memory 420 stores a computer program executable by the processor 410, and when the computer program is executed by the processor 410, it executes the method as described above.

[0108] An embodiment of the present application also provides a storage medium 430, on which a computer program is stored, and when the computer program is run by a processor 410, the above method is executed.

[0109] Among them, the storage medium 430 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM for short), electrically erasable programmable read-only memory (EEPROM for short), erasable programmable read-only memory (EPROM for short), programmable read-only memory (PROM for short), read-only memory (ROM for short), magnetic memory, flash memory, magnetic disk or optical disk.

[0110] In the description of the present invention, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. The meaning of "a plurality" is two or more, unless otherwise specifically defined.

[0111] In the present invention, unless otherwise clearly specified and defined, the terms "mounted", "connected", "connected to", "fixed" and other terms should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or integrated; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the internal connection of two components or the interaction relationship between two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0112] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic descriptions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0113] Any process or method description represented in a flowchart or described in other ways herein can be understood to represent a module, segment, or part of code including one or more executable instructions for implementing a specific logical function or process. The scope of the preferred embodiments of the present invention includes additional implementations, where the functions can be executed in a way that is not in the order shown or discussed, including in a substantially simultaneous manner according to the functions involved or in the reverse order, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0114] The logic and / or steps represented in a flowchart or described in other ways herein, for example, can be considered as a sequenced list of executable instructions for implementing a logical function, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in conjunction with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection portion having one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other suitable processing as necessary, and then stored in a computer memory.

[0115] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0116] Those of ordinary skill in the art can understand that all or part of the steps carried by the method of the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0117] The above-mentioned storage medium can be a read-only memory, a magnetic disk or an optical disc, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A parallel simulation method for short-line distribution network based on long transmission delay, characterized in that: The steps include: S10: Based on the characteristics of distributed parameters, a Bergeron decoupling model of short-line distribution network is established; S20: According to the Bergeron decoupling model, within the allowable error range, increasing the capacitance parameter value of the line, extending the transmission delay of the signal on the line, and reducing the interpolation error of the historical current source term; S30: Fault simulation is performed in a short-line distribution network scenario to verify the accuracy and effectiveness of the proposed method.

2. The parallel simulation method for short-line distribution network based on long transmission delay according to claim 1 is characterized in that: In step S10, based on the distributed parameter characteristics, a Bergeron decoupling model of the short-line distribution network is established, and the steps include: S11: Based on Kirchhoff's law of distributed parameter transmission lines, a distributed parameter transmission line model is established; S12: Simplifying the distributed parameter transmission line model by neglecting the unit resistance and conductance of the line to obtain a group of partial differential equations; S13: Considering the propagation characteristics of the wave function, solving the partial differential equations, obtaining the voltage and current relationship model at both ends of the line of the Bergeron decoupling model, and calculating the wave impedance and transmission delay of the line.

3. The parallel simulation method for short-line distribution network based on long transmission delay according to claim 2 is characterized in that: In step S11, the distributed parameter transmission line model includes: Where x is the distance from the line head end k to the differential unit dx, u and i are the voltage and current at x, respectively, and R, L, G, and C are the unit resistance, inductance, conductance, and capacitance of the line, respectively.

4. The parallel simulation method for short-line distribution network based on long transmission delay according to claim 2 is characterized in that: In step S13, the voltage and current relationship model at both ends of the line of the Bergeron decoupling model includes: In the formula, u k 、i km are the voltage and current at the beginning of the line, u m 、i mk are the voltage and current at the end of the line, Z C is the wave impedance, τ is the time required for the signal to propagate from the beginning k of the line to the end m, I k (t-τ), I m (t-τ) is the history current source term.

5. The parallel simulation method for short-line distribution network based on long transmission delay according to claim 2 is characterized in that: In step S13, the model of calculating the wave impedance and transmission delay of the line includes: In the formula, Z C is the wave impedance, τ is the transmission delay of the short line, l is the line length, L and C are the unit inductance and capacitance of the line respectively.

6. The parallel simulation method for short-line distribution network based on long transmission delay according to claim 1 is characterized in that: In step S20, according to the Bergeron decoupling model, within the allowable error range, the capacitance parameter value of the line is increased, the transmission delay of the signal on the line is prolonged, and the interpolation error of the historical current source term is reduced. The steps include: S21: within the allowable error range, adjusting the unit capacitance parameter value of the line to a capacitance correction value, so that the corrected transmission delay meets the requirement of being greater than the simulation step size, and the model of the corrected transmission delay includes: In the formula, τ * is the corrected transmission delay, l is the line length, L is the unit inductance of the line, C * is the adjusted capacitance correction value, h is the simulation step length; S22: Verify, based on the adjusted capacitance correction value, whether the adjusted simulation error is controlled within a preset range.

7. The parallel simulation method for short-line distribution network based on long transmission delay according to claim 6 is characterized in that: In step S22, it is verified whether the adjusted simulation error is controlled within a preset range. The model includes: Where ε(t) is the change in unit capacitance from C to C * When the current error flowing through the line is km is the current at the beginning of the line, is the current at the head end of the line after parameter correction, τ, Z C are the transmission delay and characteristic impedance of the line, τ * , are the transmission delay and characteristic impedance of the line after parameter correction, λ(τ) is the delay coefficient, u k are the voltage and current at the beginning of the line.

8. The parallel simulation method for short-line distribution network based on long transmission delay according to claim 1 is characterized in that: In step S30, in a distribution network model with a voltage level of 4.16 kV and a decoupling line length of 10 km, a commonly occurring single-phase grounding fault situation is set to verify the accuracy and effectiveness of the present invention.

9. A parallel simulation device for short-line distribution network based on long transmission delay, characterized in that: Use of the method according to any one of claims 1 to 8, comprising: A model unit is established for establishing a Bergeron decoupling model of a short-line distribution network based on distributed parameter characteristics; A capacitance adjustment unit, used to increase the capacitance parameter value of the line within the allowable error range according to the Bergeron decoupling model, extend the transmission delay of the signal on the line, and reduce the interpolation error of the historical current source term; The simulation verification unit is used to perform fault simulation in the short-line distribution network scenario to verify the accuracy and effectiveness of the proposed method.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

11. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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