Direct Optimization Model Predictive Control Method and System for MMC-STATCOM Systems

Abstract

This invention belongs to the field of power electronic converter technology, specifically disclosing a direct optimization model predictive control method and system for an MMC-STATCOM system. The method includes: calculating the differential-mode voltage and common-mode voltage between the upper and lower arms of each phase; injecting third harmonic voltage into the upper and lower arms of each phase to obtain the upper and lower arm voltages of the newly added third voltage component for each phase; based on the obtained upper and lower arm voltages of the newly added third voltage component, determining the number of sub-modules to be engaged in each phase's upper and lower arms using a nearest-level approximation modulation strategy; sorting the sub-modules according to the capacitor voltage of each sub-module in the arm; and determining the engaged sub-modules for each arm according to the current direction. This invention, while maintaining the discrete control structure, achieves direct injection of third harmonic voltage under the MPC framework, exhibiting higher real-time performance and scalability.

Description

Technical Field

[0001] This invention relates to the field of power electronic converter technology, and in particular to a direct optimization model predictive control method and system for an MMC-STATCOM system. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] With the large-scale integration of new energy sources such as wind and solar power into the power grid, voltage and reactive power fluctuations occur frequently. Traditional synchronous generators are insufficient to support these fluctuations, necessitating high-performance reactive power compensation equipment to ensure grid voltage stability. Static synchronous var compensators (STATCOMs) are widely used in power transmission systems due to their fast response speed and strong compensation capabilities. Among them, the STATCOM with a modular multilevel converter (MMC) structure (i.e., MMC-STATCOM) is used in large-capacity reactive power compensation applications due to its advantages such as high voltage rating, high modularity, multiple voltage levels, and excellent output waveform quality.

[0004] In terms of control strategies, traditional linear control methods such as proportional-integral (PI) and proportional-resonant (PR) control are inherently limited in bandwidth and cumbersome in parameter tuning, making it difficult to meet the high dynamic performance and robustness requirements of MMC-STATCOM. In contrast, model predictive control (MPC), with its advantages of rolling optimization and multivariable coordinated control, can achieve rapid dynamic response and adapt to complex operating environments. Finite control set model predictive control (FCS-MPC) further simplifies the control process, avoids the use of modulators, and is particularly suitable for multi-level structures.

[0005] To mitigate the combinatorial explosion problem caused by the large number of submodules in FCS-MPC within MMC-STATCOM, existing research has proposed schemes such as optimal level prediction control, neighborhood solution search control, and adaptive optimization strategies. These aim to reduce the number of enumerated combinations, thereby improving real-time performance and computational efficiency. Meanwhile, to address the issue of capacitor voltage fluctuations in MMC submodules, research has also employed control methods such as circulating current suppression, second-harmonic circulating current injection, and third-harmonic voltage injection, or topology improvements such as sharing intermediate submodules, isolating bidirectional converters, and using high-frequency crossover capacitors to improve capacitor voltage balancing characteristics.

[0006] Although the above control strategies alleviate the computational burden and capacitor voltage fluctuation problem of MPC to some extent, the following main shortcomings still exist:

[0007] When the number of submodules is large, traditional finite set model predictive control algorithms employ an traversal approach, resulting in an extremely heavy computational burden. Even with methods such as neighborhood search or adaptive optimization, the controller still requires multiple cycles to converge to the optimal submodule combination during the transient phase, impacting dynamic performance.

[0008] Current third-harmonic voltage injection relies heavily on the superposition of external modulation waveforms, making it difficult to integrate closely with the FCS-MPC control framework. This results in a disconnect between the control strategy and harmonic injection, making it impossible to achieve the harmonic control objective without compromising the controller structure.

[0009] Existing methods, such as circulating current suppression or topology improvement, have negative impacts on system efficiency or hardware complexity, do not fundamentally solve the capacitor voltage fluctuation problem, and lack flexibility and adaptability. Summary of the Invention

[0010] To address the aforementioned issues, this invention proposes a direct optimization model predictive control method and system for MMC-STATCOM systems. This method achieves rapid updates of control switch combinations through a low-complexity algorithm based on direct optimization, and suppresses fluctuations in submodule capacitor voltages by injecting a third harmonic component into the control reference.

[0011] In some implementations, the following technical solutions are adopted:

[0012] A direct optimization model predictive control method for MMC-STATCOM systems includes:

[0013] Calculate the differential-mode voltage and common-mode voltage between the upper and lower bridge arms of each phase respectively;

[0014] The third harmonic voltage is injected into the upper and lower arms of each phase to obtain the upper and lower arm voltages of the newly added third voltage component of each phase.

[0015] Based on the newly obtained upper and lower bridge arm voltages of the three voltage components, the number of sub-modules to be engaged in each phase upper and lower bridge arm is determined by the nearest level approximation modulation strategy. The sub-modules are sorted according to the capacitor voltage of each sub-module in the bridge arm, and the sub-modules to be engaged in each bridge arm are determined according to the current direction.

[0016] As a further step, the differential-mode voltage between the upper and lower arms of each phase is calculated, specifically:

[0017] Based on the active power reference value, reactive power reference value and grid voltage, the output current reference value is calculated.

[0018] Based on the output current reference value, grid current and grid voltage, and combined with the differential mode voltage calculation formula, the differential mode voltage is calculated.

[0019] As a further solution, the differential mode voltage calculation formula is as follows:

[0020] ;

[0021] in, This refers to the differential mode voltage between the upper and lower bridge arms. This represents the reference value of the grid current in phase x during the (k+1)th period. This represents the grid current in phase x of the k-th period. , , For the equivalent inductance on the AC output side, The resistor of the RL filter. Indicates the control cycle.

[0022] As a further step, the common-mode voltage between the upper and lower arms of each phase is calculated, specifically:

[0023] The reference value of the circulating current is obtained based on the reference values ​​of the AC component and the DC component.

[0024] Based on the reference and actual values ​​of the circulating current, and combined with the common-mode voltage calculation formula, the common-mode voltage is calculated.

[0025] As a further solution, the common-mode voltage calculation formula is as follows:

[0026] ;

[0027] in, This refers to the common-mode voltage between the upper and lower bridge arms. Indicates DC voltage. This represents the circulation reference value for phase x in the (k+1)th period. This represents the circulation of phase x in the k-th period. , Indicates the bridge arm inductance. Indicates the control cycle.

[0028] As a further solution, third harmonic voltages are injected into the upper and lower arms of each phase, specifically:

[0029] ;

[0030] in, , The fundamental voltage amplitude of the upper or lower bridge arm. This represents the phase angle corresponding to the fundamental voltage.

[0031] As a further approach, the upper and lower bridge arm voltages of the newly added third voltage component for each phase are obtained, specifically:

[0032] ;

[0033] in, , These are the voltages output by the upper and lower bridge arms, respectively. This refers to the differential mode voltage between the upper and lower bridge arms. This is the common-mode voltage between the upper and lower bridge arms.

[0034] As a further solution, based on the obtained upper and lower bridge arm voltages of the newly added third voltage components, a modulation strategy of closest level approximation is used to determine the number of submodules to be engaged in each phase upper and lower bridge arm, specifically:

[0035] Divide the voltage of each phase upper arm by the average capacitor voltage of each sub-module of the upper arm to obtain the number of sub-modules in operation for the upper arm.

[0036] The number of submodules in the lower bridge arm is obtained by dividing the voltage of each lower bridge arm by the average capacitor voltage of each submodule in the lower bridge arm.

[0037] In other embodiments, the following technical solutions are adopted:

[0038] A direct optimization model predictive control system for MMC-STATCOM systems, comprising:

[0039] The voltage calculation module is configured to calculate the differential-mode voltage and common-mode voltage between the upper and lower bridge arms of each phase, respectively.

[0040] The harmonic injection module is configured to inject third harmonic voltage into the upper and lower arms of each phase respectively, so as to obtain the upper and lower arm voltages of the newly added third voltage component of each phase.

[0041] The predictive control module is configured to determine the number of submodules to be engaged in each phase upper and lower bridge arm based on the obtained new third voltage components and the upper and lower bridge arm voltages using a modulation strategy of nearest level approximation. The submodules are sorted according to the capacitor voltage of each submodule in the bridge arm and the submodules to be engaged in each bridge arm are determined according to the current direction.

[0042] In other embodiments, the following technical solutions are adopted:

[0043] A terminal device includes a processor and a memory, the processor being used to implement instructions; the memory being used to store multiple instructions adapted to be loaded and executed by the processor using the above-described MMC-STATCOM system direct optimization model predictive control method.

[0044] Compared with the prior art, the beneficial effects of the present invention are:

[0045] (1) Traditional model predictive control directly obtains the number of upper and lower bridge arm sub-modules through the control algorithm, but cannot superimpose the third harmonic voltage on the number of modules. To successfully inject the third harmonic voltage, the discrete predictive control architecture needs to be changed to a continuous set predictive control architecture. The required voltage vector is obtained through the control algorithm, and finally the modulation stage and capacitor voltage sorting algorithm are used to obtain the final number of the sub-modules. Although the required voltage vector can be obtained through continuous set model predictive control, a continuous optimization problem needs to be solved in each sampling period. The computational complexity increases significantly with the system dimension, which is difficult to meet the real-time control requirements of MMC high sub-module number scenarios.

[0046] This invention calculates the differential-mode voltage and common-mode voltage separately, and derives an explicit expression for the bridge arm voltage. With the explicit expression for the bridge arm voltage, the third harmonic voltage can be directly injected into the predictive control reference, thereby reducing the voltage fluctuation of the submodule capacitor. The method of this invention realizes the direct injection of the third harmonic voltage under the MPC framework while maintaining the discrete control structure, and has higher real-time performance and scalability.

[0047] Meanwhile, based on the voltages of the upper and lower bridge arms with the addition of three voltage components, the number of submodules can be obtained by the nearest level approximation modulation. The control switch combination can be updated quickly through a low-complexity algorithm of direct optimization, which greatly reduces the computational complexity and has good real-time performance.

[0048] (2) This invention directly introduces the third voltage harmonic into the predictive control reference, realizing the third harmonic voltage injection under the MPC framework. Compared with the capacitor voltage fluctuation suppression scheme that only injects the second harmonic circulating current, this invention directly introduces the third voltage harmonic into the predictive control reference, which can achieve a better suppression effect.

[0049] (3) Traditional neighborhood optimization or adaptive search strategies rely on the historical cost function trend for optimization. Their implicit premise is that the system is in a steady-state condition, where the objective function changes slowly over time, making historical trends the only valid reference. Once a transient state occurs, these methods typically require multiple control cycles to achieve optimal control. The method of this invention, based on the grid-connected current and circulating current reference values ​​generated by the voltage outer loop and circulating current control, utilizes the deadbeat control concept to inversely calculate the common-mode voltage and differential-mode voltage reference values ​​from the cost function in one step, thus completing the optimization update within the first sampling cycle after the disturbance. Since the optimization process does not rely on statistical characteristics or asymptotic convergence mechanisms within the fundamental cycle, it maintains a fast and stable control response even under transient conditions. Compared to neighborhood optimization or adaptive search strategies, which are only applicable to steady-state conditions, the method of this invention still possesses rapid response capabilities under transient disturbances, completing the optimization update without waiting for multiple cycles.

[0050] Compared with topology improvement techniques such as adding shared submodules or isolating bidirectional converters, this invention achieves performance improvement only through control algorithm optimization, avoiding the problems of increased equipment costs and system structure complexity, and has higher engineering practicality and economy.

[0051] Other features 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

[0052] Figure 1 This is a system topology diagram of MMC-STATCOM in an embodiment of the present invention;

[0053] Figure 2 This is a block diagram of the predictive control of the classic MMC model in an embodiment of the present invention;

[0054] Figure 3 This is a schematic diagram of the direct optimization model predictive control method for the MMC-STATCOM system in an embodiment of the present invention;

[0055] Figure 4 This is a schematic diagram illustrating the dynamic performance under the control method of this invention.

[0056] Figure 5 A schematic diagram illustrating the dynamic performance under the traversal optimization control strategy;

[0057] Figure 6 To simplify the dynamic performance diagram under the optimization control strategy;

[0058] Figure 7 To suppress capacitor voltage fluctuations before third-harmonic voltage injection;

[0059] Figure 8 This describes the effect of suppressing capacitor voltage fluctuations after a third-harmonic voltage injection. Detailed Implementation

[0060] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0061] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0062] Example 1

[0063] In one or more embodiments, a direct optimization model predictive control method for an MMC-STATCOM system is disclosed, specifically including the following process:

[0064] S101: Calculate the differential-mode voltage and common-mode voltage between the upper and lower bridge arms of each phase respectively;

[0065] S102: Inject the third harmonic voltage into the upper and lower arms of each phase respectively to obtain the upper and lower arm voltages of the newly added third voltage component of each phase.

[0066] S103: Based on the obtained upper and lower bridge arm voltages of the newly added third voltage components, the number of sub-modules to be put into operation for each phase upper and lower bridge arm is determined by the modulation strategy of the closest level approximation. The sub-modules are sorted according to the capacitor voltage of each sub-module of the bridge arm and the sub-modules to be put into operation for each bridge arm are determined according to the current direction.

[0067] As a specific implementation method, firstly, combined with Figure 1 The topology of MMC-STATCOM is described, and each phase... It includes two bridge arms (the upper bridge arm and the lower bridge arm are respectively marked with subscripts). , (This is indicated by the diagram). Each phase arm consists of N half-bridge submodules SM and one arm reactor. Each half-bridge submodule SM consists of two IGBTs and a reactor with a voltage of... Capacitor components.

[0068] Assuming the capacitor voltages of each half of the bridge submodule SM in each bridge arm are balanced, the output voltages of the upper and lower bridge arms in each phase are as follows: and ,in, , These are the output voltages of the upper and lower bridge arms, respectively. , These represent the number of upper and lower bridge arm half-bridge sub-modules (SM) deployed, respectively. This indicates the rated capacitor voltage of the submodule SM; it can be seen that the output voltage of each phase upper and lower bridge arm is completely determined by the number of half-bridge submodules SM that are engaged.

[0069] The AC output side of the MMC-STATCOM is connected to the AC power grid via an RL filter. and These are the inductor and resistor of the RL filter, respectively. and These represent AC grid current and voltage, respectively.

[0070] The dynamic equations for the AC and DC equivalent circuits are as follows:

[0071] (1)

[0072] (2)

[0073] in, For the equivalent inductance on the AC output side, ; For bridge arm inductance, It is the circulating current flowing in phase x. , , They represent DC voltage and DC current, respectively; This represents the exchange component in the circulation. , These represent the current in the upper and lower bridge arms, respectively.

[0074] Assuming the capacitor voltage of SM is balanced, the relationship between grid current and circulating current and the number of SM modules in operation can be seen from equations (1) and (2) as follows:

[0075] ;

[0076] ;

[0077] Where k represents the kth sampling period, , These are the AC grid currents in the kth and (k+1)th sampling periods, respectively. The AC grid voltage during the kth sampling period is... , These are the circulating currents in the kth and k+1th sampling periods, respectively. , , , and These represent the average capacitor voltages of the x-phase submodules.

[0078] Define differential voltage: ;

[0079] Define common-mode voltage: ;

[0080] The output voltages of the upper and lower bridge arms can then be expressed as: ;

[0081] in, This refers to the differential mode voltage between the upper and lower bridge arms. This represents the reference value of the grid current in phase x during the (k+1)th period. This represents the grid current in phase x of the k-th period. , , For the equivalent inductance on the AC output side, The resistor of the RL filter. Indicates the control cycle. This refers to the common-mode voltage between the upper and lower bridge arms. Indicates DC voltage. This represents the circulation reference value for phase x in the (k+1)th period. This represents the circulation of phase x in the k-th period. , Indicates the bridge arm inductance. Indicates the control cycle.

[0082] Combination Figure 2 The control process of the classical model predictive control (MPC) algorithm is as follows:

[0083] Multiple cost functions are used sequentially, with each cost function containing only one control objective. The number of upper and lower bridge arm submodules for each phase is obtained by minimizing the cost function.

[0084] The cost functions for current tracking and circulating current tracking are as follows:

[0085] ;

[0086] ;

[0087] , They represent Reference values ​​for grid current and circulating current at any given time.

[0088] Grid-connected current reference Obtained from the DC voltage or power outer loop, the capacitor voltage reference is set to its rated value. Since the circulating current contains both DC and AC components, the DC component must be present, while the AC component needs to be suppressed. Therefore, a circulating current reference can be established. DC component , This is a reference value for active power.

[0089] The reference values ​​of the above system variables at time k+2 can be obtained by the following recursive algorithm:

[0090] ;

[0091] ;

[0092] Here x refers to or .

[0093] (1) Predictive control algorithm for traversal optimization model:

[0094] The traversal optimization control strategy iterates through all candidate submodule input arrays in each cycle, merging them to minimize the cost function and selecting the submodule input number that optimizes the control variables. Then, a submodule capacitor voltage sorting algorithm is used to achieve capacitor voltage equalization, and the switching state of each submodule is output. For an MMC with N submodules per arm, this method requires traversing N+1 possible combinations of submodule inputs per phase. The computational load increases linearly with the number of submodules. In HVDC applications with hundreds of modules, this method has a significant computational burden.

[0095] (2) Simplified predictive control algorithm for the optimization model:

[0096] To reduce computational load, the simplified optimization control strategy, based on the traversal optimization control strategy, selects only the best input number from the previous cycle and the two nearest input numbers as candidate combinations for prediction in the current and circulating current cost function prediction stage. This greatly reduces the computational burden. However, the drawback is that when the power reference changes, the simplified optimization algorithm needs to go through several cycles to select the optimal input number, resulting in poor dynamic performance.

[0097] Based on this, this embodiment proposes a direct optimization model predictive control method for MMC-STATCOM systems, combined with... Figure 3 The specific process is as follows:

[0098] First, measure the outer loop DC voltage V. dc Compared with the true value By comparison, a reference active power is obtained. Through active power reference Reactive power reference Grid voltage The output current reference value is calculated. Then, based on the aforementioned differential mode voltage calculation formula, the differential mode voltage is calculated.

[0099] Given the reference value of the circulating AC component It is 0, plus its DC component. To obtain the reference value of the final circulation. Then, using the aforementioned common-mode voltage calculation formula, the common-mode voltage is calculated.

[0100] By injecting third harmonic voltage into the upper and lower bridge arms, energy distribution is optimized and capacitor voltage fluctuations are suppressed.

[0101] Injected third harmonic voltage Afterwards, the voltages of the upper and lower bridge arms become:

[0102] ;

[0103] in, , The fundamental amplitude of the bridge arm voltage is [value missing]. m is the modulation ratio. The phase angle is the fundamental voltage.

[0104] After obtaining the upper and lower bridge arm voltages of the newly added three voltage components, a modulation strategy of closest level approximation and a capacitor voltage sorting algorithm are used to achieve precise control of submodule switching and balanced control of capacitor voltage.

[0105] The modulation strategy for closest level approximation is as follows: the voltage of each upper bridge arm is divided by the average capacitor voltage of each sub-module of the upper bridge arm to obtain the number of sub-modules in operation of the upper bridge arm; the voltage of each lower bridge arm is divided by the average capacitor voltage of each sub-module of the lower bridge arm to obtain the number of sub-modules in operation of the lower bridge arm.

[0106] The capacitor voltage sorting algorithm is as follows: After obtaining the number of sub-modules put into operation for each phase upper and lower bridge arm, sort all the capacitor voltages of the sub-modules of that bridge arm in ascending or descending order. Combined with the number of sub-modules put into operation, select the sub-modules that are earlier or later in the sorting according to the current direction to put them into operation first, so that the sub-modules with high capacitor voltages are discharged first and the sub-modules with low voltages are charged first, thereby achieving voltage balance.

[0107] To verify the dynamic performance of the method proposed in this embodiment, Figures 4-6 Dynamic performance diagrams are provided for the proposed control method, the traversal optimization control strategy, and the simplified optimization control strategy in this embodiment. It can be seen that the simplified optimization algorithm exhibits poor dynamic performance when the power reference changes, requiring a longer time to reach a steady state. In contrast, the proposed method in this embodiment demonstrates the same dynamic performance as the traversal optimization method, while avoiding the heavy computational burden of the traversal optimization method.

[0108] To verify the advantages of the method proposed in this embodiment in suppressing capacitor voltage fluctuations, the suppression effect of capacitor voltage fluctuations before and after the injection of third harmonic voltage (third harmonic voltage) was compared. Figure 7 and Figure 8 It can be seen that after injecting a third-harmonic voltage, the capacitor voltage fluctuation decreases significantly, and the circulating current also decreases.

[0109] Therefore, the method in this embodiment reduces the computational burden to the extreme without affecting the control performance; it avoids the exhaustive search of all submodule switch combinations in the traditional FCS-MPC, and only requires one calculation to obtain the reference voltage vector, thus having good real-time performance.

[0110] The method in this embodiment can directly perform third harmonic injection within the MPC framework, effectively suppressing capacitor voltage fluctuations in individual sub-modules.

[0111] Example 2

[0112] In one or more embodiments, a direct optimization model predictive control system for an MMC-STATCOM system is disclosed, comprising:

[0113] The voltage calculation module is configured to calculate the differential-mode voltage and common-mode voltage between the upper and lower bridge arms of each phase, respectively.

[0114] The harmonic injection module is configured to inject third harmonic voltage into the upper and lower arms of each phase respectively, so as to obtain the upper and lower arm voltages of the newly added third voltage component of each phase.

[0115] The predictive control module is configured to determine the number of submodules to be engaged in each phase upper and lower bridge arm based on the obtained new third voltage components and the upper and lower bridge arm voltages using a modulation strategy of nearest level approximation. The submodules are sorted according to the capacitor voltage of each submodule in the bridge arm and the submodules to be engaged in each bridge arm are determined according to the current direction.

[0116] It should be noted that the specific implementation methods of the above modules are exactly the same as those in Example 1, and will not be described in detail again.

[0117] Example 3

[0118] In one or more embodiments, a terminal device is disclosed, comprising a processor and a memory, wherein the processor is used to implement instructions; and the memory is used to store multiple instructions adapted to be loaded by the processor and executed by the processor using the direct optimization model predictive control method for the MMC-STATCOM system described in Embodiment 1.

[0119] It should be understood that in this embodiment, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0120] Memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of memory may also include non-volatile random access memory. For example, memory may also store information about the device type.

[0121] In the implementation process, each step of the above method can be completed by the integrated logic circuits in the processor hardware or by software instructions.

[0122] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A direct optimization model predictive control method for an MMC-STATCOM system, characterized in that, include: Calculate the differential-mode voltage and common-mode voltage between the upper and lower bridge arms of each phase respectively; The third harmonic voltage is injected into the upper and lower arms of each phase to obtain the upper and lower arm voltages of the newly added third voltage component of each phase. Third harmonic voltages are injected into the upper and lower arms of each phase, specifically as follows: ； in, , The fundamental voltage amplitude of the upper or lower bridge arm. This represents the phase angle corresponding to the fundamental voltage; The upper and lower bridge arm voltages of the newly added third voltage component for each phase are obtained as follows: ； in, , These are the voltages output by the upper and lower bridge arms, respectively. This refers to the differential mode voltage between the upper and lower bridge arms. This refers to the common-mode voltage between the upper and lower bridge arms. Based on the newly obtained upper and lower bridge arm voltages of the three voltage components, the number of sub-modules to be engaged in each phase upper and lower bridge arm is determined by the nearest level approximation modulation strategy. The sub-modules are sorted according to the capacitor voltage of each sub-module in the bridge arm, and the sub-modules to be engaged in each bridge arm are determined according to the current direction.

2. The direct optimization model predictive control method for an MMC-STATCOM system as described in claim 1, characterized in that, Calculate the differential-mode voltage between the upper and lower arms of each phase, specifically as follows: Based on the active power reference value, reactive power reference value and grid voltage, the output current reference value is calculated. Based on the output current reference value, grid current and grid voltage, and combined with the differential mode voltage calculation formula, the differential mode voltage is calculated.

3. The direct optimization model predictive control method for an MMC-STATCOM system as described in claim 2, characterized in that, The specific formula for calculating the differential voltage is as follows: ； in, This refers to the differential mode voltage between the upper and lower bridge arms. This represents the reference value of the grid current in phase x during the (k+1)th period. This represents the grid current in phase x of the k-th period. , , For the equivalent inductance on the AC output side, The resistor of the RL filter, Indicates the control cycle. Let x be the AC grid voltage of phase x in the kth sampling period.

4. The direct optimization model predictive control method for an MMC-STATCOM system as described in claim 1, characterized in that, Calculate the common-mode voltage between the upper and lower arms of each phase, specifically as follows: The reference value of the circulating current is obtained based on the reference values ​​of the AC component and the DC component. Based on the reference and actual values ​​of the circulating current, and combined with the common-mode voltage calculation formula, the common-mode voltage is calculated.

5. The direct optimization model predictive control method for an MMC-STATCOM system as described in claim 4, characterized in that, The specific formula for calculating the common-mode voltage is as follows: ； in, This refers to the common-mode voltage between the upper and lower bridge arms. Indicates DC voltage. This represents the circulation reference value for phase x in the (k+1)th period. This represents the circulation of phase x in the k-th period. , Indicates the bridge arm inductance. Indicates the control cycle.

6. The direct optimization model predictive control method for an MMC-STATCOM system as described in claim 1, characterized in that, Based on the newly obtained upper and lower bridge arm voltages of the three voltage components, the number of sub-modules to be engaged in each phase upper and lower bridge arm is determined using a modulation strategy that approximates the nearest level. Specifically: Divide the voltage of each phase upper arm by the average capacitor voltage of each sub-module of the upper arm to obtain the number of sub-modules in operation for the upper arm. The number of submodules in the lower bridge arm is obtained by dividing the voltage of each lower bridge arm by the average capacitor voltage of each submodule in the lower bridge arm.

7. A direct optimization model predictive control system for an MMC-STATCOM system, characterized in that, include: The voltage calculation module is configured to calculate the differential-mode voltage and common-mode voltage between the upper and lower bridge arms of each phase, respectively. The harmonic injection module is configured to inject third harmonic voltage into the upper and lower arms of each phase respectively, so as to obtain the upper and lower arm voltages of the newly added third voltage component of each phase. Third harmonic voltages are injected into the upper and lower arms of each phase, specifically as follows: ； in, , The fundamental voltage amplitude of the upper or lower bridge arm. This represents the phase angle corresponding to the fundamental voltage; The upper and lower bridge arm voltages of the newly added third voltage component for each phase are obtained as follows: ； in, , These are the voltages output by the upper and lower bridge arms, respectively. This refers to the differential mode voltage between the upper and lower bridge arms. This refers to the common-mode voltage between the upper and lower bridge arms. The predictive control module is configured to determine the number of submodules to be engaged in each phase upper and lower bridge arm based on the obtained new third voltage components and the upper and lower bridge arm voltages using a modulation strategy of nearest level approximation. The submodules are sorted according to the capacitor voltage of each submodule in the bridge arm and the submodules to be engaged in each bridge arm are determined according to the current direction.

8. A terminal device comprising a processor and a memory, the processor for implementing instructions; the memory for storing multiple instructions, characterized in that, The instructions are adapted to be loaded by a processor and executed by the direct optimization model predictive control method for the MMC-STATCOM system according to any one of claims 1-6.

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