Electromagnetic transient hybrid simulation sub-network decoupling method and device

Abstract

The invention provides a sub-network decoupling method and device for electromagnetic transient hybrid simulation, and relates to the technical field of novel digital simulation of a power system.The method comprises the steps that overall variables of a power system are defined, a system state equation is established, a system network is divided into two sub-networks, and the system state variables are grouped through a matrix splitting method; obtaining a subsystem equation; the obtained subsystem equation is expanded, different integration forms are adopted for different variable groups, and an electromagnetic transient simulation calculation formula is obtained; the obtained electromagnetic transient simulation calculation formula is applied to the two subnets, state space vectors of the two subnets are traversed through circulation, a next moment value is calculated, and updating of the state space vectors of the whole system is completed; and updating the current moment, judging whether the current moment is longer than the maximum simulation duration or not, if not, returning to the subnet and entering the next time step calculation, otherwise, exiting the simulation, and completing the whole electromagnetic transient simulation process. The method has better numerical stability and calculation precision.

Description

Technical Field

[0001] This invention relates to the field of novel power system digital simulation technology, and in particular to a network decoupling method and apparatus for electromagnetic transient hybrid simulation. Background Technology

[0002] With the large-scale integration of new clean energy sources such as wind power and distributed photovoltaic power generation, new power systems are gradually exhibiting characteristics of "multi-timescale and wide-frequency domain". Traditional power system simulation tools cannot efficiently and accurately simulate the dynamic processes of high-frequency power electronic devices in new power systems at smaller timescales. In order to balance the requirements of simulation scale and computational efficiency, the parallel computing architecture of electromagnetic transient simulation is a suitable choice. Decoupling calculation between different sub-network systems in power system electromagnetic transient simulation has become the key to the accuracy and efficiency of system simulation calculation. Summary of the Invention

[0003] The present invention aims to at least partially solve one of the technical problems in the related art.

[0004] Therefore, the first objective of this invention is to propose a network decoupling method for electromagnetic transient hybrid simulation.

[0005] The second objective of this invention is to propose a network decoupling device for electromagnetic transient hybrid simulation.

[0006] The third objective of this invention is to provide an electronic device.

[0007] The fourth objective of this invention is to provide a computer-readable storage medium.

[0008] The fifth objective of this invention is to provide a computer program product.

[0009] To achieve the above objectives, a first aspect of the present invention proposes a network decoupling method for electromagnetic transient hybrid simulation, comprising: Define the overall variables of the power system, establish the system state equations, divide the system network into two subnets, and use the matrix splitting method to group the system state variables, dividing the coefficient matrix into a diagonal matrix and an off-diagonal matrix to obtain the subsystem equations; The obtained subsystem equations are expanded, and different integral forms are used for different variable groups. The equations are discretized using the implicit trapezoidal method and the forward Euler method respectively to obtain the electromagnetic transient simulation calculation formula. The obtained electromagnetic transient simulation formula is applied to the two subnets. The state space vectors of the two subnets are traversed by loops to calculate the value at the next time step, thus completing the update of the state space vector of the entire system. Update the current time and check if it exceeds the maximum simulation duration. If not, return to the subnet and proceed to the next time step calculation; otherwise, exit the simulation and complete the entire electromagnetic transient simulation process.

[0010] Optionally, the step of establishing the system state equation, dividing the system network into two subnets, and using the matrix splitting method to group the system state variables, dividing the coefficient matrix into a diagonal matrix and an off-diagonal matrix to obtain the subsystem equation, further includes: The state equations for the entire power system are established as shown in equation (1): (1), in, It is an N-dimensional column vector of the state of the power system network. Let t be the state vector of the power system network. Differentiate the N-dimensional column vector over time. The coefficient matrix is ​​an N×N dimensional matrix representing the system state vector. The coefficient matrix is ​​an N×N dimensional input vector of the system. Let N be the input N-dimensional column vector of the system at time t; The system state variables are grouped using the matrix splitting method, and the coefficient matrix is ​​divided into a diagonal matrix and a non-diagonal matrix to obtain the subsystem equation, as shown in equation (2): (2), in Coefficient matrix The diagonal matrix is ​​formed. Coefficient matrix An N×N dimensional matrix composed of off-diagonal elements.

[0011] Optionally, the process of expanding the obtained subsystem equations, using different integral forms for different variable groups, and discretizing the equations using the implicit trapezoidal rule and forward Euler method respectively to obtain the electromagnetic transient simulation calculation formula further includes: Expanding the obtained subsystem equations, we get equation (3), as shown below: (3), in, For the system The i-th element, Coefficient matrix The diagonal element of the i-th row, Let i be the value of the i-th element of the system state vector. The element in the i-th row and j-th column of the coefficient matrix Let j be the value of the j-th column element of the system state vector. For the i-th element of the input column vector, ; Through ( , Integrating equation (3) over a time period yields equation (4), as shown below: (4), in For simulating step size, For simulation time; By discretizing the left side of equation (4) using the implicit trapezoidal method and the right side using the forward Euler method, we obtain equation (5), as shown below: (5); By rearranging equation (5), we obtain the electromagnetic transient simulation calculation formula for the state space of the power system, as shown below: (6).

[0012] Optionally, the step of applying the obtained electromagnetic transient simulation formula to the two subnets, using loops to traverse the state space vectors of the two subnets respectively, calculating the next time value, and completing the update of the state space vector of the entire system, further includes: For subnet 1, iterate through all the state space variables of subnet 1 and solve using equation (7) in combination with equation (6). The values ​​of all state space variables in subnet 1 are given by equation (7) as follows: (7), in , Indicating the first subnet in subnet 1 The values ​​of state-space variables at time t. Indicating the first subnet in subnet 1 A state-space variable in time The value of time, It is related to state variables Coefficients related to its own dynamic characteristics State variables and The coupling coefficient between them It is an index mapping function used to map the index of an output variable. with the corresponding state variable index This association indicates that the i-th output corresponds to the i-th... One state variable; Subnet 1 is used in the following formula The calculated value at time t is assigned to the value at time t to update the state space vector of the entire power system network, as shown in the following formula: (8).

[0013] Optionally, the step of applying the obtained electromagnetic transient simulation formula to the two subnets, using loops to traverse the state space vectors of the two subnets respectively, calculating the next time value, and completing the update of the state space vector of the entire system, further includes: For subnet 2, iterate through all the state space variables of subnet 2 and solve using equation (9) in combination with equation (6). The values ​​of all state-space variables in subnet 2 are given by equation (9) as follows: (9), in , Indicating the second subnet The values ​​of state-space variables at time t. Indicating the first subnet in subnet 1 A state-space variable in time The value of time, It is related to state variables Coefficients related to its own dynamic characteristics State variables and The coupling coefficient between them It is an index mapping function used to map the index of an output variable. with the corresponding state variable index This association indicates that the i-th output corresponds to the i-th... One state variable; Subnet 2 is used in the following formula The calculated value at time t is assigned to the vector at time t to update the state space vector of the entire power system network, as shown in the following formula: ;(10)

[0014] To achieve the above objectives, a second aspect of the present invention provides a network decoupling device for electromagnetic transient hybrid simulation, comprising: The basic setting module defines the overall variables of the power system, establishes the system state equations, divides the system network into two subnets, and uses the matrix splitting method to group the system state variables, dividing the coefficient matrix into a diagonal matrix and an off-diagonal matrix to obtain the subsystem equations. The equation processing module expands the obtained subsystem equations, uses different integral forms for different variable groups, and discretizes the equations using the implicit trapezoidal method and the forward Euler method to obtain the electromagnetic transient simulation calculation formula. The subnet calculation module applies the obtained electromagnetic transient simulation formula to the two subnets, and uses loops to traverse the state space vectors of the two subnets respectively to calculate the value at the next time step, thus completing the update of the state space vector of the entire system. The loop termination module updates the current time and checks if it exceeds the maximum simulation duration. If not, it returns to the subnet and proceeds to the next time step calculation; otherwise, it exits the simulation, completing the entire electromagnetic transient simulation process.

[0015] To achieve the above objectives, a third aspect of the present invention provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of the first aspects.

[0016] To achieve the above objectives, a fourth aspect of the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of the first aspects.

[0017] To achieve the above objectives, a fifth aspect of the present invention provides a computer program product that, when executed by a processor, implements the method described in any one of the first aspects.

[0018] This invention provides a network decoupling method, device, electronic equipment, and storage medium for electromagnetic transient hybrid simulation. It decomposes the overall system into multiple independent subnets for parallel computation. Cross-regional power grid simulations that originally required several hours can be completed in half an hour, significantly improving engineering analysis efficiency. Network decoupling not only reduces the computational load on individual devices—allowing ordinary servers to perform tasks that previously required high-performance computing clusters, thus reducing hardware costs—but also flexibly adapts to changes in power grid topology, providing efficient and reliable simulation support for renewable energy grid integration and power grid fault analysis. Furthermore, this method can accurately capture transient interactions between subnets, providing reliable data support for power grid fault location and renewable energy grid integration stability analysis, contributing to the safe operation of the power system.

[0019] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0020] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart illustrating a network decoupling method for electromagnetic transient hybrid simulation provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of a network decoupling device for electromagnetic transient hybrid simulation provided in an embodiment of the present invention. Detailed Implementation

[0021] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0022] This invention provides a network decoupling method for electromagnetic transient hybrid simulation. Figure 1 This is a flowchart illustrating a network decoupling method for electromagnetic transient hybrid simulation provided in an embodiment of the present invention. Figure 1 As shown, the method includes the following steps: Step 101: Define the overall variables of the power system, establish the system state equations, divide the system network into two subnets, and use the matrix splitting method to group the system state variables, dividing the coefficient matrix into a diagonal matrix and an off-diagonal matrix to obtain the subsystem equations.

[0023] In one embodiment of the present invention, the overall variables of the power system are first defined, and the entire novel power system is assumed to have N state-space variables. It is an N-dimensional column vector of the state of the power system network. Let t be the state vector of the power system network. Differentiate the N-dimensional column vector over time. The coefficient matrix is ​​an N×N dimensional matrix representing the system state vector. The coefficient matrix is ​​an N×N dimensional input vector of the system. Let t be the N-dimensional column vector of the system's input at time t. The vectors and the system's topology and branch parameters are related and are known quantities. Let be the N-dimensional column vector of the system input at time t, which is known, and N be the total number of state variables of the system.

[0024] The entire power system network is divided into two subnets, subnet 1 and subnet 2. The state space vector of subnet 1 is... The vector dimension is N1, and the state space vector of subnet 2 is... The vector dimension is N², and N1 + N2 = N. An N¹-dimensional array IB1[N1] is set to store the indexes (i.e., state space vectors) of the N¹ state space variables of subnet 1 corresponding to the state space variables of the entire power network system. The corresponding element positions), the N2-dimensional array IB2[N2] stores the index (i.e., the state space vector) of the state space variables of the entire power network system corresponding to the N2 state space variables of subnet 2, respectively. (corresponding element position) For simulating step size, For simulation time, This represents the simulation duration.

[0025] The state equations for the entire power system are then established, as shown in equation (1): (1).

[0026] Furthermore, the system state variables are grouped using the matrix splitting method, and the coefficient matrix is ​​divided into groups. Dividing the matrix into diagonal and off-diagonal matrices, we obtain the subsystem equations, as shown in equation (2): (2), in Coefficient matrix The diagonal matrix is ​​formed. Coefficient matrix An N×N dimensional matrix composed of off-diagonal elements, where the focal element is 0, i.e. .

[0027] Step 102: Expand the obtained subsystem equations, use different integral forms for different variable groups, and discretize the equations using the implicit trapezoidal rule and forward Euler method respectively to obtain the electromagnetic transient simulation calculation formula.

[0028] In one embodiment of the present invention, the accurate expansion and discretization of the subsystem equations are the core steps to ensure simulation accuracy. Expanding the obtained subsystem equations yields equation (3), as shown below: (3), in, For the system The i-th element, Coefficient matrix The diagonal element of the i-th row, Let i be the value of the i-th element of the system state vector. The element in the i-th row and j-th column of the coefficient matrix Let j be the value of the j-th column element of the system state vector. For the i-th element of the input column vector, ; Through ( , Integrating equation (3) over a time period yields equation (4), as shown below: (4), in For simulating step size, This is the simulation time.

[0029] It is clear that the essence of integration is to transform continuous dynamic equations into numerical relationships between discrete time nodes, and to establish a system by calculating each integral term. Time and The correlation of state variables at different times is a key bridge connecting continuous systems and discrete simulations.

[0030] Furthermore, by discretizing the left side of equation (4) using the implicit trapezoidal rule and the right side using the forward Euler method, we obtain equation (5), as shown below: (5).

[0031] It is clear that for the left side of equation (4), since it includes the rate of change and damping term of the state variables themselves, which are directly related to the stability of the system, the implicit trapezoidal method is used for discretization; while the right side of equation (4) includes coupling terms of different state variables and external input terms, whose numerical changes are relatively smooth. In order to simplify the calculation and ensure real-time performance, the forward Euler method is used for discretization.

[0032] By rearranging equation (5), we obtain the electromagnetic transient simulation calculation formula for the state space of the power system, as shown below: (6).

[0033] Step 103: Apply the obtained electromagnetic transient simulation formula to the two subnets, and use loops to traverse the state space vectors of the two subnets respectively to calculate the value at the next time step, thus completing the update of the state space vector of the entire system.

[0034] In one embodiment of the present invention, the core of this step is to target the two subnets after the system is split, named subnet 1 and subnet 2, and to solve for the next time step by iterating through their state space vectors and combining them with the obtained simulation calculation formula. The variable values ​​are used to complete the iterative update of the state space vector of the entire power system, providing a data foundation for the continuous advancement of subsequent time-domain simulation.

[0035] Specifically, for subnet 1, all state space variables of subnet 1 are iterated through. The correspondence between the state space variables of subnet 1 and the state space variables of the entire network is solved using equation (7) in combination with equation (6). The values ​​of all state space variables in subnet 1 are given by equation (7) as follows: (7), in , Indicating the first subnet in subnet 1 The values ​​of state-space variables at time t. Indicating the first subnet in subnet 1 A state-space variable in time The value of time, It is related to state variables Coefficients related to its own dynamic characteristics State variables and The coupling coefficient between them It is an index mapping function used to map the index of an output variable. with the corresponding state variable index This association indicates that the i-th output corresponds to the i-th... There are several state variables.

[0036] Subnet 1 is used in the following formula The calculated value at time t is assigned to the value at time t, updating the state space vector of the entire power system network: (8).

[0037] Furthermore, for subnet 2, by iterating through all the state space variables of subnet 2 and establishing the correspondence between the state space variables of subnet 2 and the state space variables of the entire network, the solution is obtained by combining equation (9) with equation (6). The values ​​of all state-space variables in subnet 2 are given by equation (9) as follows: (9), in , Indicating the second subnet The values ​​of state-space variables at time t. Indicating the first subnet in subnet 1 A state-space variable in time The value of time, It is related to state variables Coefficients related to its own dynamic characteristics State variables and The coupling coefficient between them It is an index mapping function used to map the index of an output variable. with the corresponding state variable index This association indicates that the i-th output corresponds to the i-th... There are several state variables.

[0038] Subnet 2 is used in the following formula The calculated value at time t is assigned to the vector at time t, updating the state space vector of the entire power system network: (10).

[0039] Step 104: Update the current time and determine if it is greater than the maximum simulation duration. If not, return to the subnet and proceed to the next time step calculation; otherwise, exit the simulation and complete the entire electromagnetic transient simulation process.

[0040] In one embodiment of the present invention, the core logic of this step revolves around "constant update - duration judgment - process branching". Through clear timing rules, it is ensured that the simulation can not only continue to advance according to the preset step size, but also terminate precisely when the target duration is reached, thus ensuring the orderliness and integrity of the entire simulation process.

[0041] Specifically, let t = t + Δt, and determine whether the current time t is greater than the maximum simulation duration: if it is not satisfied, it means that the full-time domain simulation is not yet complete, and it is necessary to return to the subnet and enter the electromagnetic transient simulation calculation of the next time step; if it is satisfied, it means that the preset simulation goal has been achieved, exit the electromagnetic transient simulation calculation, output the calculated values ​​of the state space variables of subnet 1 and subnet 2, and finally complete the closed loop of the entire electromagnetic transient simulation process.

[0042] To achieve the above embodiments, the present invention also proposes a network decoupling device for electromagnetic transient hybrid simulation. Figure 2 This is a schematic diagram of a network decoupling device for electromagnetic transient hybrid simulation provided in an embodiment of the present invention. Figure 2 As shown, the device includes: The basic setting module 100 defines the overall variables of the power system, establishes the system state equations, divides the system network into two subnets, and uses the matrix splitting method to group the system state variables, dividing the coefficient matrix into a diagonal matrix and an off-diagonal matrix to obtain the subsystem equations. The equation processing module 200 expands the obtained subsystem equations, uses different integral forms for different variable groups, and discretizes the equations using the implicit trapezoidal method and the forward Euler method respectively to obtain the electromagnetic transient simulation calculation formula. The subnet calculation module 300 applies the obtained electromagnetic transient simulation calculation formula to the two subnets, and uses loops to traverse the state space vectors of the two subnets respectively to calculate the value at the next time step, thus completing the update of the state space vector of the entire system. The loop termination module 400 updates the current time and checks if it exceeds the maximum simulation duration. If not, it returns to the subnet and proceeds to the next time step calculation; otherwise, it exits the simulation and completes the entire electromagnetic transient simulation process.

[0043] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0044] To implement the above embodiments, the present invention also proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method provided in the foregoing embodiments.

[0045] To implement the above embodiments, the present invention also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.

[0046] To implement the above embodiments, the present invention also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.

[0047] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in this invention all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0048] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0049] This invention is intended to provide implementation schemes for users to selectively prevent the use or access to personal information data. That is, this disclosure is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information can be de-identified to protect user privacy.

[0050] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0051] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0052] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of the invention pertain.

[0053] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs 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: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0054] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any of the following techniques known in the art, or a combination thereof: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0055] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0056] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0057] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

[0058] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0059] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A network decoupling method for electromagnetic transient hybrid simulation, characterized in that, Includes the following steps: Define the overall variables of the power system, establish the system state equations, divide the system network into two subnets, and use the matrix splitting method to group the system state variables, dividing the coefficient matrix into a diagonal matrix and an off-diagonal matrix to obtain the subsystem equations; The obtained subsystem equations are expanded, and different integral forms are used for different variable groups. The equations are discretized using the implicit trapezoidal method and the forward Euler method respectively to obtain the electromagnetic transient simulation calculation formula. The obtained electromagnetic transient simulation formula is applied to the two subnets. The state space vectors of the two subnets are traversed by loops to calculate the value at the next time step, thus completing the update of the state space vector of the entire system. Update the current time and check if it exceeds the maximum simulation duration. If not, return to the subnet and proceed to the next time step calculation; otherwise, exit the simulation and complete the entire electromagnetic transient simulation process.

2. The method according to claim 1, characterized in that, The system state equations are established, the system network is divided into two subnets, and the system state variables are grouped using the matrix splitting method, dividing the coefficient matrix into diagonal and off-diagonal matrices to obtain the subsystem equations, which also include: The state equations for the entire power system are established as shown in equation (1): （1）， in, It is an N-dimensional column vector of the state of the power system network. Let t be the state vector of the power system network. Differentiate the N-dimensional column vector over time. The coefficient matrix is ​​an N×N dimensional matrix representing the system state vector. The coefficient matrix is ​​an N×N dimensional input vector of the system. Let N be the input N-dimensional column vector of the system at time t; The system state variables are grouped using the matrix splitting method, and the coefficient matrix is ​​divided into a diagonal matrix and a non-diagonal matrix to obtain the subsystem equation, as shown in equation (2): （2）， in Coefficient matrix The diagonal matrix is ​​formed. Coefficient matrix An N×N dimensional matrix composed of off-diagonal elements.

3. The method according to claim 2, characterized in that, The obtained subsystem equations are expanded, and different integral forms are used for different sets of variables. The equations are discretized using the implicit trapezoidal rule and the forward Euler method, respectively, to obtain the electromagnetic transient simulation calculation formula, which also includes: Expanding the obtained subsystem equations, we get equation (3), as shown below: （3）， in, For the system The i-th element, Coefficient matrix The diagonal element of the i-th row, Let i be the value of the i-th element of the system state vector. The element in the i-th row and j-th column of the coefficient matrix Let j be the value of the j-th column element of the system state vector. For the i-th element of the input column vector, ; Through ( , Integrating equation (3) over a time period yields equation (4), as shown below: （4）， in For simulating step size, For simulation time; By discretizing the left side of equation (4) using the implicit trapezoidal method and the right side using the forward Euler method, we obtain equation (5), as shown below: （5）； By rearranging equation (5), we obtain the electromagnetic transient simulation calculation formula for the state space of the power system, as shown below: （6）。 4. The method according to claim 3, characterized in that, The obtained electromagnetic transient simulation formula is applied to two subnets. The state space vectors of the two subnets are traversed using loops to calculate the next time step value, thus completing the update of the state space vector of the entire system. This also includes: For subnet 1, iterate through all the state space variables of subnet 1 and solve using equation (7) in combination with equation (6). The values ​​of all state space variables in subnet 1 are given by equation (7) as follows: （7）， in , Indicating the first subnet in subnet 1 The values ​​of state-space variables at time t. Indicating the first subnet in subnet 1 A state-space variable in time The value of time, It is related to state variables Coefficients related to its own dynamic characteristics State variables and The coupling coefficient between them It is an index mapping function used to map the index of an output variable. with the corresponding state variable index This association indicates that the i-th output corresponds to the i-th... One state variable; Subnet 1 is divided into subnets using the following formula. The calculated value at time t is assigned to the value at time t to update the state space vector of the entire power system network, as shown in the following formula: （8）。 5. The method according to claim 4, characterized in that, The obtained electromagnetic transient simulation formula is applied to two subnets. The state space vectors of the two subnets are traversed using loops to calculate the next time step value, thus completing the update of the state space vector of the entire system. This also includes: For subnet 2, iterate through all the state space variables of subnet 2 and solve using equation (9) in combination with equation (6). The values ​​of all state-space variables in subnet 2 are given by equation (9) as follows: （9）， in , Indicating the second subnet The values ​​of state-space variables at time t. Indicating the first subnet in subnet 1 A state-space variable in time The value of time, It is related to state variables Coefficients related to its own dynamic characteristics State variables and The coupling coefficient between them It is an index mapping function used to map the index of an output variable. with the corresponding state variable index This association indicates that the i-th output corresponds to the i-th... One state variable; Subnet 2 is used in the following formula The calculated value at time t is assigned to the vector at time t to update the state space vector of the entire power system network, as shown in the following formula: ；（10）。 6. A network decoupling device for electromagnetic transient hybrid simulation, characterized in that, include: The basic setting module defines the overall variables of the power system, establishes the system state equations, divides the system network into two subnets, and uses the matrix splitting method to group the system state variables, dividing the coefficient matrix into a diagonal matrix and an off-diagonal matrix to obtain the subsystem equations. The equation processing module expands the obtained subsystem equations, uses different integral forms for different variable groups, and discretizes the equations using the implicit trapezoidal method and the forward Euler method to obtain the electromagnetic transient simulation calculation formula. The subnet calculation module applies the obtained electromagnetic transient simulation formula to the two subnets, and uses loops to traverse the state space vectors of the two subnets respectively to calculate the value at the next time step, thus completing the update of the state space vector of the entire system. The loop termination module updates the current time and checks if it exceeds the maximum simulation duration. If not, it returns to the subnet and proceeds to the next time step calculation; otherwise, it exits the simulation, completing the entire electromagnetic transient simulation process.

7. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-5.

9. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1-5.

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