High-efficiency modeling method for electromagnetic transient simulation of modular multilevel converter battery energy storage

Abstract

This invention discloses an efficient modeling method for electromagnetic transient simulation of modular multilevel converter battery energy storage systems, belonging to the field of power system simulation technology. The method includes: determining multiple operating modes of a submodule in a modular multilevel converter battery energy storage system, and for each operating mode, writing the state equation of the submodule within one cycle; performing state averaging modeling on multiple state equations using a periodic averaging operator to obtain a state-space averaged circuit simulation model of the submodule; and processing the state-space averaged circuit simulation model using a discrete difference method to obtain a state-space averaged discrete analytical recursive model of the submodule. This technical solution can reflect the high-frequency dynamic characteristics affected by the switching process, simulate the unbalanced operating state of the submodule, and improve the simulation speed.

Description

Technical Field

[0001] This invention relates to the field of power system simulation technology, specifically to an efficient modeling method for electromagnetic transient simulation of modular multilevel converter battery energy storage. Background Technology

[0002] In response to the problems of power quality degradation and reduced grid connection reliability caused by the inherent intermittency and uncertainty of renewable energy, MMC-BESS (Modular Multilevel Converter-Battery Energy Storage System) has gradually become a promising solution due to its advantages of high efficiency, large capacity, high modularity and flexible adjustable energy storage capacity, as well as its ability to buffer power, peak shaving and valley filling, load balancing and frequency regulation.

[0003] Electromagnetic transient simulation is a common technique for studying circuit topology or verifying control algorithm design. In electromagnetic transient simulation software, a Detailed Switching Model (DSM) is often used for modeling. To ensure accurate simulation of switching behavior, a small simulation step size is required, and the system's admittance matrix needs to be recalculated and updated whenever a switching state changes. Due to the large number of power electronic switching devices and the high frequency of switching operations in MMC-BESS, using DSM for simulation imposes a significant computational burden, especially when the number of modules is high. DSM exhibits extremely low efficiency in power system simulations containing MMC-BESS.

[0004] To reduce the computational complexity of DSM, researchers have developed efficient models such as the average value model and the detailed equivalent model. The conventional average value model ignores switching dynamics and assumes that the capacitor voltages and battery states of charge within the bridge arm are balanced, thus treating the entire bridge arm as a controlled source and significantly improving simulation speed. However, this model cannot accurately reflect the high-frequency dynamic characteristics affected by the switching process, and it also struggles to simulate the unbalanced operating states between submodules, resulting in limited simulation accuracy under transient processes and non-ideal conditions. On the other hand, the Thevenin equivalent model reduces the size of the system admittance matrix by treating submodules as Thevenin circuits and can retain internal electrical information to some extent. However, its computational efficiency is still limited by the large number of submodules; each equivalent circuit still needs to participate in network solving. In complex systems containing energy storage units, real-time parameter updates and circuit solving still impose a significant computational load, making it difficult to meet the demands of real-time simulations or large-scale system analysis scenarios with extremely high simulation speed requirements. Summary of the Invention

[0005] The purpose of this invention is to provide an efficient modeling method for electromagnetic transient simulation of modular multilevel converter battery energy storage, so as to solve the technical problems existing in related technologies.

[0006] To achieve the above objectives, this invention provides an efficient modeling method for electromagnetic transient simulation of modular multilevel converter battery energy storage, comprising:

[0007] For a submodule in a modular multilevel converter battery energy storage system, multiple operating modes of the submodule are determined, and for each operating mode, the state equation of the submodule in one cycle is written. The operating mode is the conduction state of different switching transistors of the submodule under preset conditions.

[0008] By using a periodic averaging operator to perform state averaging and unified modeling on multiple state equations, a state-space average circuit simulation model of the sub-module is obtained. The state-space average circuit simulation model is a model obtained by decoupling the circuit of the sub-module.

[0009] By processing the state-space average circuit simulation model using the discrete difference method, a state-space average discrete analytical recursive model of the sub-module is obtained.

[0010] Optionally,

[0011] The submodule includes a first switching transistor. Second switching transistor Polarized capacitor, third switching transistor Fourth switching transistor An inductor and a battery, wherein the first switching transistor... The second switching transistor The third switching transistor and the fourth switching transistor They are all composed of anti-parallel IGBTs and diodes;

[0012] The positive terminal of the polarized capacitor is connected to the third switching transistor. The cathode of the diode and the negative terminal of the polarized capacitor are connected to the fourth switching transistor. The anode of the diode; the third switching transistor The anode of the diode is connected to the fourth switching transistor. The cathode of the diode; the third switching transistor and the fourth switching transistor The midpoint is connected to the positive terminal of the battery via an inductor, and the negative terminal of the battery is connected to the negative terminal of the polarized capacitor.

[0013] Optionally, the method further includes:

[0014] Obtain the battery voltage, inductor voltage, and capacitor voltage of the polarized capacitor. Subtract the inductor voltage from the battery voltage to obtain the voltage difference.

[0015] The operating modes include a first operating mode to a sixth operating mode, wherein the first operating mode is: when the first switching transistor... With the third switching transistor When in the ON state, the second switch transistor With the fourth switching transistor It is in a closed state;

[0016] The second operating mode is: when the second switching transistor... With the third switching transistor When in the ON state, the first switching transistor With the fourth switching transistor It is in a closed state;

[0017] The third operating mode is: when the voltage difference is less than the capacitor voltage, the first switching transistor... With the fourth switching transistor When in the ON state, the second switch transistor With the third switching transistor It is in a closed state;

[0018] The fourth operating mode is: when the voltage difference is less than the capacitor voltage, the second switching transistor... With the fourth switching transistor When in the ON state, the first switching transistor With the third switching transistor It is in a closed state;

[0019] The fifth operating mode is: when the voltage difference is greater than the capacitor voltage, the first switching transistor... With the fourth switching transistor When in the ON state, the second switch transistor With the third switching transistor It is in a closed state;

[0020] The sixth operating mode is: when the voltage difference is greater than the capacitor voltage, the second switching transistor... With the fourth switching transistor When in the ON state, the first switching transistor With the third switching transistor It is in a closed state.

[0021] Optionally, for each operating mode, writing the state equations of the submodule over one cycle includes:

[0022] When the operating mode is the first operating mode, the state equation is expressed by the following formula:

[0023] ;

[0024] ;

[0025] When the operating mode is the second operating mode, the state equation is expressed by the following calculation formula:

[0026] ;

[0027] ;

[0028] When the operating mode is the third operating mode, the state equation is expressed by the following calculation formula:

[0029] ;

[0030] ;

[0031] When the operating mode is the fourth operating mode, the state equation is expressed by the following formula:

[0032] ;

[0033] ;

[0034] When the operating mode is the fifth operating mode, the state equation is expressed by the following calculation formula:

[0035] ;

[0036] ;

[0037] When the operating mode is the sixth operating mode, the state equation is expressed by the following calculation formula:

[0038] ;

[0039] ;

[0040] ;

[0041] in, This refers to the capacitance value of the submodule. This refers to the inductance value of the submodule. These are the state variables for capacitor voltage and inductor current. This is the resistance value when the switch is on. For the first The voltage of the polarized capacitor at any given time. For the first The current in the inductor at all times, For the first The battery voltage at all times. For the first The current constantly flowing into the submodule, This represents the output voltage at the submodule port. The input quantities are the current flowing into the submodule and the battery voltage. For the first The port voltage of the time submodule, , , , and All are matrix variables.

[0042] Optionally, the state-space average circuit simulation model of the submodule is expressed by the following calculation formula:

[0043] ;

[0044] ;

[0045] in, The duty cycle of the first working mode. The duty cycle of the second working mode. The duty cycle for the third working mode. The duty cycle for the fourth working mode. The duty cycle for the fifth working mode. The duty cycle for the sixth working mode. , , and All are intermediate variables used in the calculation of the unified state equation, which is represented by the duty cycle correlation coefficient.

[0046] Optionally, the state-space average discrete analytical recursive model is expressed by the following calculation formula:

[0047] ;

[0048] ;

[0049] ;

[0050] in, , and All of these are intermediate variables in the calculation. The discrete equivalent resistance of the capacitor. Let be the inductor current at step k. The current flowing into the submodule, The inductor current at step k+1. The capacitor voltage at step k+1. For simulating step size, The discrete equivalent resistance of the inductor. The capacitor voltage at step k is... This represents the k-th step of the simulation. This refers to the battery voltage.

[0051] Through the above technical solution, when performing electromagnetic transient simulation of a modular multilevel converter battery energy storage system, a state-space average discrete analytical recursive model is constructed for each submodule. This model is obtained by processing the state-space average circuit simulation model using the discrete difference method. The state-space average circuit simulation model is obtained by writing the state equations of the submodule within one cycle under different operating modes, and then averaging multiple state equations. Furthermore, it decouples the circuits of the submodules. Compared to related technologies that use the Thevenin equivalent model for simulation, this method does not require a large number of submodules. Simultaneously, during electromagnetic transient simulation, it can reflect the high-frequency dynamic characteristics affected by the switching process and simulate the unbalanced operating states of the submodules, thereby improving the simulation speed.

[0052] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0053] Figure 1 This is a schematic diagram illustrating an efficient modeling method for electromagnetic transient simulation of battery energy storage in a modular multilevel converter according to an exemplary embodiment of the present invention.

[0054] Figure 2 This is a schematic diagram illustrating the structure of a modular multilevel converter battery energy storage system according to an exemplary embodiment of the present invention.

[0055] Figure 3 This is a circuit structure diagram of a submodule according to an exemplary embodiment of the present invention.

[0056] Figure 4 This is a schematic diagram illustrating the current flow path of a submodule under different operating conditions according to an exemplary embodiment of the present invention.

[0057] Figure 5 This is a circuit structure diagram corresponding to the state-space average circuit simulation model according to an exemplary embodiment of the present invention.

[0058] Figure 6 This is a schematic diagram illustrating the MMC-BESS single-ended test system according to an exemplary embodiment of the present invention.

[0059] Figure 7This is a waveform comparison diagram of a switch model and a state-space model according to an exemplary embodiment of the present invention. Detailed Implementation

[0060] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, so as to provide a better understanding of the concept of the present invention, the technical problem solved, the technical features constituting the technical solution, and the technical effects brought about.

[0061] like Figure 1 As shown, Figure 1 This is a schematic diagram illustrating an efficient modeling method for electromagnetic transient simulation of modular multilevel converter battery energy storage according to an exemplary embodiment of the present invention. (Refer to...) Figure 1 The method includes;

[0062] S101: For a submodule in a modular multilevel converter battery energy storage system, determine multiple operating modes of the submodule, and for each operating mode, write the state equation of the submodule in one cycle, wherein the operating mode is the conduction state of different switching transistors of the submodule under preset conditions.

[0063] S102: The state space average circuit simulation model of the sub-module is obtained by uniformly modeling multiple state equations through the periodic averaging operator. The state space average circuit simulation model is a model obtained by decoupling the circuit of the sub-module.

[0064] S103: The state-space average circuit simulation model is processed by the discrete difference method to obtain the state-space average discrete analytical recursive model of the sub-module.

[0065] Through the above technical solution, when performing electromagnetic transient simulation of a modular multilevel converter battery energy storage system, a state-space average discrete analytical recursive model is constructed for each submodule. This model is obtained by processing the state-space average circuit simulation model using the discrete difference method. The state-space average circuit simulation model is obtained by writing the state equations of the submodule within one cycle under different operating modes, and then averaging multiple state equations. Furthermore, it decouples the circuits of the submodules. Compared to related technologies that use the Thevenin equivalent model for simulation, this method does not require a large number of submodules. Simultaneously, during electromagnetic transient simulation, it can reflect the high-frequency dynamic characteristics affected by the switching process and simulate the unbalanced operating states of the submodules, thereby improving the simulation speed.

[0066] To enable those skilled in the art to better understand the efficient modeling method for electromagnetic transient simulation of modular multilevel converter battery energy storage provided by the present invention, the above steps are illustrated in detail below.

[0067] For example, electromagnetic transient simulation can be described as the process of performing real-time and accurate numerical simulation calculations of rapidly changing electromagnetic processes in circuits / power grids in the field of power systems / power electronics. Modular multilevel converter battery energy storage systems are novel power energy storage devices that combine a modular multilevel converter (MBC) with an embedded battery energy storage system (BESS). Their core is the use of a modular power electronic conversion topology to achieve bidirectional and efficient interaction between battery energy and grid energy, making them key equipment for new energy grid integration, grid frequency and voltage regulation, and peak shaving and valley filling. In this embodiment of the invention, the structural diagram of the modular multilevel converter battery energy storage system is as follows: Figure 2 As shown, the modular multilevel converter battery energy storage system has a three-phase six-arm structure, with each arm consisting of an arm reactor. It is formed by cascading with at least one submodule. This is the DC bus voltage. Figure 2 In It can be divided into different sub-modules, and the circuit structure diagram of each sub-module is as follows: Figure 3 As shown, it includes the HBSM (Half Bridge SubModule) and the third switch. Fourth switching transistor The HBSM includes an inductor and a battery, and includes a first switching transistor. Second switching transistor and polarized capacitors. Wherein, the first switching transistor... The second switching transistor The third switching transistor and the fourth switching transistor All are composed of anti-parallel IGBTs (Insulated Gate Bipolar Transistors) and diodes; the positive terminal of the polarized capacitor is connected to the third switching transistor. The cathode of the diode and the negative terminal of the polarized capacitor are connected to the fourth switching transistor. The anode of the diode; the third switching transistor The anode of the diode is connected to the fourth switching transistor. The cathode of the diode; the third switching transistor and the fourth switching transistor The midpoint is connected to the positive terminal of the battery via an inductor, and the negative terminal of the battery is connected to the negative terminal of the polarized capacitor. Figure 3 middle, The current flowing into the submodule, This refers to the port voltage of the submodule. This is the capacitor voltage.

[0068] Each submodule corresponds to a different operating mode, and for each operating mode, the state equation of that submodule can be written over one cycle. Furthermore, each operating mode can be determined based on the battery voltage, inductor voltage, capacitor voltage, and the conduction state of each switch.

[0069] In some possible ways, the method further includes:

[0070] Obtain the battery voltage, inductor voltage, and capacitor voltage of the polarized capacitor. Subtract the inductor voltage from the battery voltage to obtain the voltage difference.

[0071] The operating modes include a first operating mode to a sixth operating mode, wherein the first operating mode is: when the first switching transistor... With the third switching transistor When in the ON state, the second switch transistor With the fourth switching transistor It is in a closed state;

[0072] The second operating mode is: when the second switching transistor... With the third switching transistor When in the ON state, the first switching transistor With the fourth switching transistor It is in a closed state;

[0073] The third operating mode is: when the voltage difference is less than the capacitor voltage, the first switching transistor... With the fourth switching transistor When in the ON state, the second switch transistor With the third switching transistor It is in a closed state;

[0074] The fourth operating mode is: when the voltage difference is less than the capacitor voltage, the second switching transistor... With the fourth switching transistor When in the ON state, the first switching transistor With the third switching transistor It is in a closed state;

[0075] The fifth operating mode is: when the voltage difference is greater than the capacitor voltage, the first switching transistor... With the fourth switching transistor When in the ON state, the second switch transistor With the third switching transistor It is in a closed state;

[0076] The sixth operating mode is: when the voltage difference is greater than the capacitor voltage, the second switching transistor... With the fourth switching transistor When in the ON state, the first switching transistor With the third switching transistor It is in a closed state.

[0077] It should be understood that the differential voltage can be expressed by the following formula:

[0078] ;

[0079] in, It is a differential voltage. This is the inductor voltage. The specific operating modes are shown in Table 1, where... The voltage is the capacitor voltage. The first and second operating modes do not limit the magnitude of the difference voltage and the capacitor voltage. The value "1" can represent the on state and the value "0" can represent the off state.

[0080] Table 1. Submodule Working Modes .

[0081] Taking the submodule in the first operating mode as an example, in the first operating mode, the submodule has various current flow paths under different operating conditions, as detailed below. Figure 4 As shown. According to Kirchhoff's voltage and current laws, the circuit equation is as follows:

[0082] ;

[0083] in, This refers to the capacitance value of the submodule. The inductance value of the submodule. This is the resistance value when the switch is on. For the first Polarity capacitor C SM voltage, For the first Inductance L SM The current, For the first The battery voltage at all times. For the first The current constantly flowing into the submodule, For the first The port voltage of the time submodule.

[0084] Define the submodule port voltage as the output quantity. The current flowing into the submodule and the battery voltage are used as input quantities. The capacitor voltage and inductor current of the submodule are used as state variables. :

[0085] ;

[0086] Then, based on this formula, state equations are written for each operating mode within one cycle, and then organized into a state-space equation expression form:

[0087] ;

[0088] definition:

[0089] ;

[0090] When the operating mode is the first operating mode, the state equation is expressed by the following formula:

[0091] ;

[0092] ;

[0093] When the operating mode is the second operating mode, the state equation is expressed by the following calculation formula:

[0094] ;

[0095] ;

[0096] When the operating mode is the third operating mode, the state equation is expressed by the following calculation formula:

[0097] ;

[0098] ;

[0099] When the operating mode is the fourth operating mode, the state equation is expressed by the following formula:

[0100] ;

[0101] ;

[0102] When the operating mode is the fifth operating mode, the state equation is expressed by the following calculation formula:

[0103] ;

[0104] ;

[0105] When the operating mode is the sixth operating mode, the state equation is expressed by the following calculation formula:

[0106] ;

[0107] ;

[0108] ;

[0109] in, , , , and All are matrix variables.

[0110] For example, a periodic averaging operator can be a mathematical tool or method for averaging signals such as voltage, current, and state variables that vary periodically in a power electronic system over a complete cycle. Specifically, the periodic averaging operator can be defined by the following formula:

[0111] ;

[0112] in, Representation function In length The average over the time interval, For a certain variable to be averaged in the state, For one cycle time, Let be a dummy variable in the integral, representing time, in the interval [t, t+T]. s The changes occur within the [condition]. Then, substituting the state equations corresponding to different operating modes into the periodic averaging operator, we obtain the following calculation formula:

[0113] ;

[0114] in, The duty cycle of the first working mode. The duty cycle of the second working mode. The duty cycle for the third working mode. The duty cycle for the fourth working mode. The duty cycle for the fifth working mode. This represents the duty cycle of the sixth working mode.

[0115] Then, by combining the above calculations, we can obtain the expression for the state-space average circuit simulation model of the target submodule:

[0116] ;

[0117] ;

[0118] in, , , and All are intermediate variables used in the calculation of the unified state equation, which is represented by the duty cycle correlation coefficient.

[0119] Therefore, based on the state-space average circuit simulation model, the state-space average circuit simulation model of a single sub-module can be obtained, such as... Figure 5 As shown, Figure 5 In The battery voltage is represented by the inductor. This model decouples the capacitor, inductor, and sub-modules from the external parts through a controlled source, greatly reducing the amount of simulation calculations. It can also simulate all electrical information inside the sub-modules. In actual simulation, it is only necessary to cascade the external equivalent parts of all sub-modules in the bridge arm while keeping the internal parts unchanged to obtain the bridge arm simulation model.

[0120] For example, the discrete difference method can be a method that uses the discrete difference quotient to approximate the continuous derivative, transforming the differential equation into a difference equation for numerical solution. In this embodiment of the invention, after obtaining the state-space average circuit simulation model, the discrete difference method can be used to process the state-space average circuit simulation model to obtain the state-space average discrete analytical recursive model of the sub-module.

[0121] Specifically, once the submodule has stabilized, the fifth and sixth operating modes will not appear during the stable operation. Therefore, based on the conditions of the first to fourth operating modes, the state-space average circuit simulation model can be transformed into the following calculation formula:

[0122] ;

[0123] By using the trapezoidal integral method to diffuse the above formula, we obtain the following formula:

[0124] ;

[0125] Assumption: Therefore, based on this formula and the previous formula, we can obtain:

[0126] ;

[0127] when Then:

[0128] ;

[0129] in, , and All of these are intermediate variables in the calculation. The discrete equivalent resistance of the capacitor. Let be the inductor current at step k. The current flowing into the submodule, The inductor current at step k+1. The capacitor voltage at step k+1. For simulating step size, The discrete equivalent resistance of the inductor. The capacitor voltage at step k is... This represents the k-th step of the simulation.

[0130] This yields a state-space average discrete analytical recursive model, whose external equivalent method in electromagnetic transient simulation is similar to... Figure 5 Since the internal circuit model is not present, the following solution method is adopted: assuming the preset simulation step size is... Now, at simulation time t, we first read the relevant parameters of the external circuit obtained by the system solver at time t, namely the bridge arm current and the switching states of the control signals of the four switching transistors in each submodule of the bridge arm, and determine their respective modes. After one switching cycle, we calculate the duty cycle of each mode. Then, according to the above calculation formula, we can calculate the parameters of the components corresponding to each submodule in the modular multilevel converter battery energy storage system. By repeating the above simulation operation for each submodule, we can realize the electromagnetic transient simulation of the modular multilevel converter battery energy storage system.

[0131] In the specific implementation process, such as Figure 6 The image shows the MMC-BESS single-ended test system. Figure 6 middle The impedance of the DC line. The AC line impedance is given, and the specific system parameters are shown in Table 2.

[0132] Table 2 System Parameters .

[0133] In this embodiment, the detailed switching model and state-space simulation model of MMC-BESS are compared and analyzed.

[0134] Under power reference variation conditions in the MMC-BESS single-ended test system Figure 7 The figures show the AC active power of the Detailed Switching Model (DSM) and the State Space Model, respectively. P AC waveform, AC reactive power Q AC waveform, DC active power P DC waveform and battery active power P bat The waveform comparison chart shows that... Figure 7 In the diagram, SSA represents the relevant waveforms of the state-space model. It can be seen that the waveforms have a good degree of agreement. Here, Time represents time.

[0135] Therefore, as can be seen from the above embodiments and accompanying drawings, high-precision simulation can be achieved. Under the Microsoft Windows 11 operating system, on a PC with a 2.80 GHz Intel Core i9-10900F processor and 64GB of RAM... Figure 6 The test system in the test performs a 6-second simulation.

[0136] In the simulation, different numbers of submodules per bridge arm were used to conduct tests with varying degrees of complexity. Table 3 shows a comparison of the simulation time of the proposed simulation method and the detailed model at different levels of complexity.

[0137] Table 3 Comparison of Time Consumption .

[0138] Therefore, the simulation method proposed in this invention has a good simulation acceleration effect, and the acceleration effect is better as the number of sub-modules increases. In summary, the simulation modeling method provided by this invention, for MMC-BESS, can accurately simulate the internal and external characteristics under various operating conditions and control strategies while ensuring accelerated simulation. Furthermore, this modeling method is applicable to various control and modulation methods, demonstrating strong adaptability. Moreover, the technical solution provided by this invention enables a more comprehensive and efficient simulation of MMC-BESS electromagnetic transient modeling, balancing high precision and high speed.

[0139] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An efficient modeling method for electromagnetic transient simulation of modular multilevel converter battery energy storage, characterized in that, include: For a submodule in a modular multilevel converter battery energy storage system, multiple operating modes of the submodule are determined, and for each operating mode, the state equation of the submodule in one cycle is written. The operating mode is the conduction state of different switching transistors of the submodule under preset conditions. By using a periodic averaging operator to perform state averaging and unified modeling on multiple state equations, a state-space average circuit simulation model of the sub-module is obtained. The state-space average circuit simulation model is a model obtained by decoupling the circuit of the sub-module. By processing the state-space average circuit simulation model using the discrete difference method, a state-space average discrete analytical recursive model of the sub-module is obtained.

2. The efficient modeling method for electromagnetic transient simulation of modular multilevel converter battery energy storage according to claim 1, characterized in that, The submodule includes a first switching transistor. Second switching transistor Polarized capacitor, third switching transistor Fourth switching transistor An inductor and a battery, wherein the first switching transistor... The second switching transistor The third switching transistor and the fourth switching transistor They are all composed of anti-parallel IGBTs and diodes; The positive terminal of the polarized capacitor is connected to the third switching transistor. The cathode of the diode and the negative terminal of the polarized capacitor are connected to the fourth switching transistor. The anode of the diode; the third switching transistor The anode of the diode is connected to the fourth switching transistor. The cathode of the diode; the third switching transistor and the fourth switching transistor The midpoint is connected to the positive terminal of the battery via an inductor, and the negative terminal of the battery is connected to the negative terminal of the polarized capacitor.

3. The efficient modeling method for electromagnetic transient simulation of modular multilevel converter battery energy storage according to claim 2, characterized in that, The method further includes: Obtain the battery voltage, inductor voltage, and capacitor voltage of the polarized capacitor. Subtract the inductor voltage from the battery voltage to obtain the voltage difference. The operating modes include a first operating mode to a sixth operating mode, wherein the first operating mode is: when the first switching transistor... With the third switching transistor When in the ON state, the second switch transistor With the fourth switching transistor It is in a closed state; The second operating mode is: when the second switching transistor... With the third switching transistor When in the ON state, the first switching transistor With the fourth switching transistor It is in a closed state; The third operating mode is: when the voltage difference is less than the capacitor voltage, the first switching transistor... With the fourth switching transistor When in the ON state, the second switch transistor With the third switching transistor It is in a closed state; The fourth operating mode is: when the voltage difference is less than the capacitor voltage, the second switching transistor... With the fourth switching transistor When in the ON state, the first switching transistor With the third switching transistor It is in a closed state; The fifth operating mode is: when the voltage difference is greater than the capacitor voltage, the first switching transistor... With the fourth switching transistor When in the ON state, the second switch transistor With the third switching transistor It is in a closed state; The sixth operating mode is: when the voltage difference is greater than the capacitor voltage, the second switching transistor... With the fourth switching transistor When in the ON state, the first switching transistor With the third switching transistor It is in a closed state.

4. The efficient modeling method for electromagnetic transient simulation of modular multilevel converter battery energy storage according to claim 3, characterized in that, For each working mode, the state equations of the submodule are written over one cycle, including: When the operating mode is the first operating mode, the state equation is expressed by the following formula: ； ； When the operating mode is the second operating mode, the state equation is expressed by the following calculation formula: ； ； When the operating mode is the third operating mode, the state equation is expressed by the following calculation formula: ； ； When the operating mode is the fourth operating mode, the state equation is expressed by the following formula: ； ； When the operating mode is the fifth operating mode, the state equation is expressed by the following calculation formula: ； ； When the operating mode is the sixth operating mode, the state equation is expressed by the following calculation formula: ； ； ； in, This refers to the capacitance value of the submodule. This refers to the inductance value of the submodule. These are the state variables for capacitor voltage and inductor current. This is the resistance value when the switch is on. For the first The voltage of the polarized capacitor at any given time. For the first The current in the inductor at all times, For the first The battery voltage at all times. For the first The current constantly flowing into the submodule, This represents the output voltage at the submodule port. The input quantities are the current flowing into the submodule and the battery voltage. For the first The port voltage of the time submodule, , , , and All are matrix variables.

5. The efficient modeling method for electromagnetic transient simulation of modular multilevel converter battery energy storage according to claim 4, characterized in that, The state-space average circuit simulation model of the submodule is expressed by the following formula: ； ； in, The duty cycle of the first working mode. The duty cycle of the second working mode. The duty cycle for the third working mode. The duty cycle for the fourth working mode. The duty cycle for the fifth working mode. The duty cycle for the sixth working mode. , , and All are intermediate variables used in the calculation of the unified state equation, which is represented by the duty cycle correlation coefficient.

6. The efficient modeling method for electromagnetic transient simulation of modular multilevel converter battery energy storage according to claim 5, characterized in that, The state-space average discrete analytical recursive model is expressed by the following formula: ； ； ； in, , and All of these are intermediate variables in the calculation. The discrete equivalent resistance of the capacitor. Let be the inductor current at step k. The current flowing into the submodule, The inductor current at step k+1. The capacitor voltage at step k+1. For simulating step size, The discrete equivalent resistance of the inductor. The capacitor voltage at step k is... This represents the k-th step of the simulation. This refers to the battery voltage.

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