CN112600452B - MMC finite set model prediction control method and system based on bridge arm current control - Google Patents

MMC finite set model prediction control method and system based on bridge arm current control Download PDF

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CN112600452B
CN112600452B CN202011445746.5A CN202011445746A CN112600452B CN 112600452 B CN112600452 B CN 112600452B CN 202011445746 A CN202011445746 A CN 202011445746A CN 112600452 B CN112600452 B CN 112600452B
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bridge arm
current
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axis
voltage
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CN112600452A (en
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王霄鹤
周才全
傅春翔
施朝晖
谢瑞
杨文斌
马润泽
徐鸥洋
徐晗
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PowerChina Huadong Engineering Corp Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M7/00—Conversion of ac power input into dc power output; Conversion of dc power input into ac power output
    • H02M7/42—Conversion of dc power input into ac power output without possibility of reversal
    • H02M7/44—Conversion of dc power input into ac power output without possibility of reversal by static converters
    • H02M7/48—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode
    • H02M7/483—Converters with outputs that each can have more than two voltages levels
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/18—Arrangements for adjusting, eliminating or compensating reactive power in networks
    • H02J3/1821—Arrangements for adjusting, eliminating or compensating reactive power in networks using shunt compensators
    • H02J3/1835—Arrangements for adjusting, eliminating or compensating reactive power in networks using shunt compensators with stepless control
    • H02J3/1842—Arrangements for adjusting, eliminating or compensating reactive power in networks using shunt compensators with stepless control wherein at least one reactive element is actively controlled by a bridge converter, e.g. active filters
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M1/00—Details of apparatus for conversion
    • H02M1/08—Circuits specially adapted for the generation of control voltages for semiconductor devices incorporated in static converters
    • H02M1/088—Circuits specially adapted for the generation of control voltages for semiconductor devices incorporated in static converters for the simultaneous control of series or parallel connected semiconductor devices
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/30—Reactive power compensation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/60—Arrangements for transfer of electric power between AC networks or generators via a high voltage DC link [HVCD]

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Abstract

The invention discloses a bridge arm current control-based MMC finite set model prediction control method and system. The method establishes prediction models of the currents of the upper bridge arm and the lower bridge arm of the MMC, constructs corresponding target functions, and selects an optimal sub-module input mode through the target functions. The method utilizes bridge arm current control to replace two control links of output current and internal circulation in the traditional model predictive control strategy, thereby simplifying the calculation process of a target function; in addition, compared with the existing control strategy based on bridge arm current, the method adopts a finite set model predictive control method, does not need a reference voltage calculation module and a modulation module, realizes effective control under a two-phase static alpha-beta coordinate system, and simplifies the complexity of a control system. The MMC finite set model prediction control method based on bridge arm current control is simple in structure, excellent in performance and high in engineering practical value.

Description

MMC (modular multilevel converter) finite set model prediction control method and system based on bridge arm current control
Technical Field
The invention belongs to the technical field of power electronics, and particularly relates to a prediction control method of an MMC finite set model based on bridge arm current control.
Background
The flexible direct-current power transmission technology based on Modular Multilevel Converter (MMC) topology adopts a submodule cascading mode to replace direct series connection of switching devices, has the advantages of low manufacturing difficulty, low switching loss, high waveform quality and the like, and has very good application prospect in the collection and transmission process of large-scale renewable energy sources.
Model predictive control has recently gained much attention in the power electronics field as an advanced control theory, and a finite set model predictive control strategy is applied to MMC as one of the research directions in the field of flexible dc power transmission. The MMC finite set model prediction control strategy based on the submodule investment mode traversal method is developed, the control idea is simple, and the optimal submodule investment mode is determined by comparing the target functions of all submodule investment modes in the sampling period, so that the MMC is controlled. However, for a high-power flexible direct-current power transmission system, the number of sub-modules is large, and the calculation amount by adopting the traversal method is too large to be applied in engineering practice. On the basis, a scholars provides an improved MMC finite set model prediction control strategy, the input priorities of different sub-modules of an upper bridge arm and a lower bridge arm are sequenced according to capacitance and voltage of the sub-modules, and when the number of the sub-modules needing to be input is determined, the specific input method of the sub-modules can also be determined to be one, so that only the target functions of the upper bridge arm and the lower bridge arm adopting different input numbers of the sub-modules need to be compared. The method optimizes the calculation efficiency of the MMC finite set model prediction control strategy, however, the method needs to respectively construct an output current, internal circulation and bridge arm energy target function, and selects a proper weight factor to obtain a final target function, and the control structure and the selection method of the weight factor are still complex. In addition, the method realizes the control of the system in a three-phase coordinate system, and the calculation amount in the control process is still large.
Disclosure of Invention
In order to overcome the defect that the selection method of the control structure and the weight factor in the prior art is complex, the invention provides a prediction control method of an MMC finite set model based on bridge arm current control, which is characterized in that a prediction model of the currents of an upper bridge arm and a lower bridge arm of the MMC is established, corresponding objective functions are established, an optimal sub-module input mode is selected through the objective functions, and the complexity of a control system is simplified; the method utilizes bridge arm current control to replace two control links of output current and internal circulation in the traditional model predictive control method, thereby simplifying the calculation process of a target function; compared with the existing control strategy based on bridge arm current, the method does not need a reference voltage calculation module and a modulation module, realizes effective control under a two-phase static alpha-beta coordinate system, has a simple control structure, and meets the actual engineering requirements on dynamic response speed and control precision.
In order to achieve the above purpose, the invention further adopts the following technical scheme:
the utility model provides a finite set model predictive control system of MMC based on bridge arm current control which characterized in that: the system comprises a sampling module, a phase-locked loop module, a coordinate transformation module, a power calculation module, a direct current bus voltage and reactive power control module, a bridge arm current reference value calculation module, a bridge arm current prediction and target function calculation module and a target function comparison and control instruction output module;
the sampling module comprises:
voltage sampling module for three-phase voltage U on AC network side of MMC convertersabcDC bus voltage UdcVoltage U of upper and lower bridge arm submodules of three phasespabc(i) And Unabc(i) (i is 1 to N) sampling;
a current sampling module for sampling three-phase current I on the power grid sidesabcThree-phase current I at valve side of converter transformervabcMMC upper and lower bridge arm current IpabcAnd InabcSampling is carried out;
the phase-locked loop module is used for detecting the phase theta of the power grid voltagev；
The coordinate transformation module comprises:
clark conversion module for three-phase voltage U on the AC network side of MMCsabcValve side three-phase current IvabcUpper and lower bridge arm current IpabcAnd InabcClark transformation is carried out to obtain a corresponding voltage vector U under an alpha-beta coordinate systemsαβCurrent vector IvαβUpper and lower bridge arm current IpαβAnd Inαβ；
A Park inverse transformation module for converting the current reference value I output by the grid voltage controllervdqrefTransforming the synchronous rotation d-q coordinate system into a static alpha-beta coordinate system to obtain a current reference value I in the static coordinate systemvαβrefThe angle adopted by Park inverse transformation is the phase theta of the alternating current power gridv；
The power calculation module is used for calculating the three-phase voltage U according to the power gridsabcCurrent I ofsabcCalculating to obtain AC side power PsAnd Qs；
The direct current bus voltage and reactive power control module adopts a PI controller to control the direct current bus voltage UdcAnd reactive power QsControl is performed so as to respectively follow a given reference value UdcrefAnd QsrefThe outputs of the two PI controllers are respectively used as reference values I of d-axis current and q-axis currentvdqref(ii) a Wherein the reference value UdcrefReference value Q for rated DC bus voltage of systemsrefAccording to the system instruction, the unit power factor is set to be 0 when in operation, and the corresponding reactive compensation can be carried out on the power grid according to the reactive requirement of the power grid;
the bridge arm current reference value calculating module is used for calculating the reference value according to the power P at the alternating current sidesDC bus voltage UdcOutput a current reference value IvαβrefCalculating to obtain upper and lower bridge arm current reference values IpαβrefAnd InαβrefFurther, the calculation method may employ the following formula:
Figure BDA0002824535160000031
wherein, IpαrefAnd IpβrefAre respectively electricityFlow vector IpαβrefAlpha axis, beta axis component of (I)nαrefAnd InβrefAre respectively a current vector InαβrefAlpha axis, beta axis component, IvαrefAnd IvβrefAre respectively a current vector Ivαβrefα -axis, β -axis component of (a);
the bridge arm current prediction and objective function calculation module comprises:
a bridge arm current prediction module for obtaining the power grid voltage U according to the sampling periodsαβUpper and lower bridge arm current IpαβAnd InαβRespectively calculating the current I of the upper and lower bridge arms in the next sampling period when the upper and lower bridge arms in the sampling period adopt different submodule investment methodspαβ(next)And Inαβ(next)Wherein, the sampling period has N +1 seed module investment methods in total, and I needs to be calculated for N +1 times in totalpαβ(next)And Inαβ(next)To obtain Ipαβ(next)(m) and Inαβ(next)(m),(m＝1,2,...N+1)；
An objective function calculation module for calculating the predicted value I of the upper and lower bridge arm currentpαβ(next)(m)、Inαβ(next)(m), and reference value I thereofpαβref、InαβrefCalculating an objective function J1m,(m＝1,2,...N+1)；
The current I of the upper and lower bridge arms of the next sampling periodpαβ(next)And Inαβ(next)The specific calculation method is as follows:
Figure BDA0002824535160000032
Figure BDA0002824535160000033
wherein L is equivalent inductance containing converter transformer and bridge arm reactor, and T is equivalent inductancesFor a sampling period, UsαAnd UsβAre respectively a voltage vector UsαβAlpha axis, beta axis component, IpαAnd IpβAre respectively a current vector IpαβAlpha axis, beta axis component, Ipα(next)(m) and Ipβ(next)(m) are each a current vector Ipαβ(next)Alpha-axis, beta-axis component of (m), InαAnd InβAre respectively a current vector InαβAlpha axis, beta axis component, Inα(next)(m) and Inβ(next)(m) are each a current vector Inαβ(next)An α -axis, β -axis component of (m); u shapepα(m),Upβ(m) are respectively the alpha-axis and beta-axis components of the upper bridge arm voltage by adopting the mth seed module input method, and the calculation method is as follows:
Figure BDA0002824535160000041
wherein lpa、lpbAnd lpcThe number of the submodules which are put into corresponding upper bridge arms;
Unα(m),Unβ(m) respectively representing the alpha-axis and beta-axis components of the lower bridge arm voltage by adopting the mth seed module input method, wherein the calculation method is the same as that of the corresponding components of the upper bridge arm;
the objective function JmThe specific calculation method is as follows:
Jm＝|Ipαref-Ipα(next)(m)|+|Ipβref-Ipβ(next)(m)|+|Inαref-Inα(next)(m)|+|Inβref-Inβ(next)(m)|
wherein, JmIs an objective function using the mth seed module input method.
The target function comparison and control instruction output module compares the final target function J by adopting an N +1 seed module input methodmAnd (m-1, 2.. N +1), selecting a submodule investment method with the minimum objective function as a control instruction of the sampling period, and realizing the control of the MMC converter.
Drawings
Fig. 1 is a diagram of a specific example of a MMC converter station.
Fig. 2 is a system schematic diagram of a specific example of the control method of the present invention.
FIG. 3 is a schematic diagram of a method for inputting an N +1 seed module according to the present invention.
FIG. 4 is a diagram of a bridge arm current prediction module and an objective function calculation module.
Detailed Description
In order to more specifically describe the present invention, the following detailed description is provided for the technical solution of the present invention with reference to the accompanying drawings and the specific embodiments.
The system implementation of the MMC finite set model prediction control method based on bridge arm current control is shown in figure 2, and comprises a voltage sensor 1, a current sensor 2, a phase-locked loop module 3, a Clark conversion module 4, a power calculation module 5, a direct current bus voltage and reactive power controller 6, a Park inverse conversion module 7, a bridge arm current reference value calculation module 8, a bridge arm current prediction module 9, a bridge arm current target function calculation module 10 and a target function comparison and control instruction output module 11.
As shown in fig. 2, the method for predicting and controlling the MMC finite set model based on bridge arm current control in the present invention includes the following steps:
three-phase voltage U on alternating current network side of MMC current converter at sending end of flexible direct current transmission systemsabcAnd three-phase current IsabcCollecting; three-phase current I on valve side of converter transformervabcMMC upper and lower bridge arm current IpabcAnd InabcAnd a DC bus voltage UdcCollecting; for three-phase upper and lower bridge arm N sub-module voltage Upabc(i) And Unabc(i) (i is 1 to N) and the phase θ of the grid voltage is obtained by the phase-locked loop module 3v；
Three-phase voltage U on MMC alternating current network side by adopting Clark conversion module 4sabcValve side three-phase current IvabcUpper and lower bridge arm current IpabcAnd InabcClark transformation is carried out to obtain a corresponding voltage vector U under an alpha-beta coordinate systemsαβCurrent vector IvαβUpper and lower bridge arm current IpαβAnd Inαβ；
Utilizing a power calculation module 5 to calculate the three-phase voltage U according to the power gridsabcCurrent I ofsabcCalculating to obtain AC side power PsAnd Qs(ii) a DC bus voltage U is controlled by DC bus voltage and reactive power controller 6dcAnd reactive power QsControl is performed so as to respectively follow a given reference value UdcrefAnd QsrefThe output of the controller is respectively used as the reference value I of the d-axis current and the q-axis currentvdqref(ii) a Wherein the reference value UdcrefReference value Q for rated DC bus voltage of systemsrefAccording to the system instruction, the unit power factor is set to be 0 when in operation, and the corresponding reactive compensation can be carried out on the power grid according to the reactive requirement of the power grid. The direct current bus voltage and reactive power controller is realized in the following mode:
Figure BDA0002824535160000051
Figure BDA0002824535160000052
wherein: fPI(s) is the transfer function of the PI controller, kpIs a proportionality coefficient, kiWhen the control variables are different, the proportional and integral coefficients are adjusted according to the actual conditions, Ivdref,IvqrefCorresponding to a current vector IvdqrefD-axis, q-axis component.
Adopting a Park inverse transformation module 7 to convert the reference value I of the currentvdqrefTransforming the synchronous rotation d-q coordinate system into a stationary alpha-beta coordinate system to obtain an output current reference value IvαβrefThe angle adopted by Park inverse transformation is the phase theta of the alternating current power gridv(ii) a A bridge arm current reference value calculation module 8 is adopted to calculate the power P according to the alternating current sidesDC bus voltage UdcOutput a current reference value IvαβrefCalculating to obtain upper and lower bridge arm current reference values IpαβrefAnd Inαβref；
Upper and lower bridge arm current reference value IpαβrefAnd InαβrefThe calculation method of (2) is as follows:
Figure BDA0002824535160000061
wherein, IpαrefAnd IpβrefAre respectively a current vector IpαβrefAlpha axis, beta axis component, InαrefAnd InβrefAre respectively a current vector InαβrefAlpha axis, beta axis component, IvαrefAnd IvβrefAre respectively a current vector IvαβrefThe α axis, the β axis component.
The bridge arm current prediction module 9 is utilized to obtain the power grid voltage U according to the sampling periodsαβUpper and lower bridge arm current IpαβAnd InαβRespectively calculating the current I of the upper and lower bridge arms in the next sampling period when the upper and lower bridge arms in the sampling period adopt different submodule investment methodspαβ(next)And Inαβ(next)Wherein, the sampling period has N +1 seed module input methods, the specific input method is shown in figure 3, I needs to be calculated for N +1 timespαβ(next)And Inαβ(next)To obtain Ipαβ(next)(m) and Inαβ(next)(m), (m ═ 1, 2.. N + 1); then, the objective function calculation module 10 is utilized to calculate the current reference value I of the upper and lower bridge arms according to the current reference value IpαβrefAnd InαβrefCalculating an objective function Jm,(m＝1,2,...N+1)；
Upper and lower bridge arm current I of next sampling periodpαβ(next)And Inαβ(next)Calculated according to the following way:
Figure BDA0002824535160000062
Figure BDA0002824535160000063
wherein L is equivalent inductance containing converter transformer and bridge arm reactor, and T is equivalent inductancesFor a sampling period, UsαAnd UsβAre respectively a voltage vector UsαβAlpha axis, beta axis component, IpαAnd IpβAre respectively a current vector IpαβAlpha axis, beta axis component, Ipα(next)(m) and Ipβ(next)(m) are each a current vector Ipαβ(next)Alpha-axis, beta-axis component of (m), InαAnd InβAre respectively a current vector InαβAlpha axis, beta axis component of (I)nα(next)(m) and Inβ(next)(m) are each a current vector Inαβ(next)An α -axis, β -axis component of (m); u shapepα(m),Upβ(m) are respectively the alpha-axis and beta-axis components of the upper bridge arm voltage adopting the mth seed module input method, and the calculation method comprises the following steps:
Figure BDA0002824535160000071
wherein lpa、lpbAnd lpcThe number of the submodules which are put into corresponding upper bridge arms.
Unα(m),UnβAnd (m) are respectively the alpha-axis and beta-axis components of the lower bridge arm voltage by adopting the m-th seed module input method, and the calculation method is the same as that of the corresponding components of the upper bridge arm.
Objective function JmThe calculation method of (2) is as follows:
Jm＝|Ipαref-Ipα(next)(m)|+|Ipβref-Ipβ(next)(m)|+|Inαref-Inα(next)(m)|+|Inβref-Inβ(next)(m)|
wherein, JmIs an objective function using the mth seed module input method.
Comparing the target function J adopting the N +1 seed module input method by using the target function comparison and control instruction output module 11mAnd (m-1, 2.. N +1), selecting a submodule investment method with the minimum target function as a control instruction of the sampling period, and realizing the control of the MMC converter.
In conclusion, by adopting the MMC finite set model prediction control method based on bridge arm current control, two control links of output current and internal circulation in the traditional control strategy can be replaced by effective control of upper and lower bridge arm currents, so that the calculation process of a target function is effectively simplified; meanwhile, the invention realizes the effective control of the system under the two-phase static alpha-beta coordinate system, has very simple control structure and stronger practicability.
The embodiments described above are presented to enable a person having ordinary skill in the art to make and use the invention. It will be readily apparent to those skilled in the art that various modifications to the above-described embodiments may be made, and the generic principles defined herein may be applied to other embodiments without the use of inventive faculty. Therefore, the present invention is not limited to the above embodiments, and those skilled in the art should make improvements and modifications to the present invention based on the disclosure of the present invention within the protection scope of the present invention.

Claims (3)

1. The MMC finite set model prediction control system based on bridge arm current control is characterized by comprising a sampling module, a phase-locked loop module, a coordinate transformation module, a power calculation module, a direct current bus voltage and reactive power control module, a bridge arm current reference value calculation module, a bridge arm current prediction and target function calculation module and a target function comparison and control instruction output module;
the sampling module comprises:
voltage sampling module for three-phase voltage U on AC network side of MMC convertersabcDC bus voltage UdcVoltage U of upper and lower bridge arm submodules of three phasespabc(i) And Unabc(i) Sampling, wherein i is 1-N, and N is the number of upper bridge arm sub-modules and the number of lower bridge arm sub-modules;
a current sampling module for sampling three-phase current I on the power grid sidesabcThree-phase current I at valve side of converter transformervabcMMC upper and lower bridge arm current IpabcAnd InabcSampling is carried out;
the phase-locked loop module is used for detecting the voltage phase theta of the alternating current power gridv；
The coordinate transformation module comprises:
clark conversion module for three-phase voltage U on the AC network side of MMCsabcValve side three-phase current IvabcUpper and lower bridge arm current IpabcAnd InabcClark transformation is carried out to obtain a corresponding voltage vector U under an alpha-beta coordinate systemsαβCurrent vector IvαβUpper and lower bridge arm current vector IpαβAnd Inαβ；
A Park inverse transformation module for converting the current reference value I output by the grid voltage controllervdqrefTransforming the synchronous rotation d-q coordinate system into a stationary alpha-beta coordinate system to obtain a current reference value I in the stationary coordinate systemvαβrefThe angle adopted by Park inverse transformation is the voltage phase theta of the alternating current power gridv；
The power calculation module is used for calculating the three-phase voltage U on the side of the alternating current power gridsabcGrid side three-phase current IsabcCalculating to obtain AC side power PsAnd Qs；
The direct current bus voltage and reactive power control module adopts a PI controller to direct current bus voltage UdcAnd reactive power QsControl is performed so as to respectively follow a given reference value UdcrefAnd QsrefThe outputs of the two PI controllers are respectively used as reference values I of d-axis and q-axis currentsvdqref(ii) a Wherein the reference value UdcrefFor rated DC bus voltage of the system, reference value QsrefAccording to the system instruction, the unit power factor is set to be 0 when in operation, and the corresponding reactive compensation can be carried out on the power grid according to the reactive requirement of the power grid;
the bridge arm current reference value calculating module is used for calculating the reference value according to the power P at the alternating current sidesDC bus voltage UdcOutputting the current reference value I in the static coordinate systemvαβrefCalculating to obtain the reference values I of the upper and lower bridge armspαβrefAnd InαβrefThe specific calculation method is as follows:
Figure FDA0003436670930000021
wherein, IpαrefAnd IpβrefRespectively as upper bridge arm current reference value IpαβrefAlpha axis, beta axis component of (I)nαrefAnd InβrefRespectively as the current reference value I of the lower bridge armnαβrefAlpha axis, beta axis component, IvαrefAnd IvβrefRespectively a current reference value I in a stationary coordinate systemvαβrefα -axis, β -axis component of (a);
the bridge arm current prediction and objective function calculation module comprises:
the bridge arm current prediction module obtains a corresponding voltage vector U under an alpha-beta coordinate system according to the sampling periodsαβUpper and lower bridge arm current IpαβAnd InαβRespectively calculating the current I of the upper and lower bridge arms in the next sampling period when the upper and lower bridge arms in the sampling period adopt different submodule investment methodspαβ(next)And Inαβ(next)Wherein, the sampling period has N +1 seed module investment methods in total, and I needs to be calculated for N +1 times in totalpαβ(next)And Inαβ(next)To obtain Ipαβ(next)(m) and Inαβ(next)(m),(m＝1,2,...N+1)；
An objective function calculation module for calculating the predicted value I of the upper and lower bridge arm currentpαβ(next)(m)、Inαβ(next)(m), and reference value I thereofpαβref、InαβrefCalculating an objective function Jm,(m＝1,2,...N+1)；
The target function comparison and control instruction output module compares the final target function J by adopting an N +1 seed module input methodmAnd (m-1, 2.. N +1), selecting a submodule investment method with the minimum target function as a control instruction of the sampling period, and realizing the control of the MMC converter.
2. The system of claim 1, wherein: in the bridge arm current prediction module, the upper and lower bridge arm currents I of the next sampling periodpαβ(next)And Inαβ(next)The specific calculation method is as follows:
Figure FDA0003436670930000022
Figure FDA0003436670930000031
wherein L is equivalent inductance containing converter transformer and bridge arm reactor, and T is equivalent inductancesFor a sampling period, UsαAnd UsβRespectively corresponding voltage vector U under alpha-beta coordinate systemsαβAlpha axis, beta axis component, IpαAnd IpβRespectively as upper arm current vector IpαβAlpha axis, beta axis component, Ipα(next)(m) and Ipβ(next)(m) are respectively upper bridge arm current predicted values Ipαβ(next)α -axis, β -axis component of (m), InαAnd InβRespectively as lower bridge arm current vector InαβAlpha axis, beta axis component, Inα(next)(m) and Inβ(next)(m) are respectively the predicted values I of the lower bridge arm currentnαβ(next)An α -axis, β -axis component of (m); u shapepα(m),Upβ(m) are respectively the alpha-axis and beta-axis components of the upper bridge arm voltage adopting the mth seed module input method, and the calculation method comprises the following steps:
Figure FDA0003436670930000032
wherein lpa、lpbAnd lpcThe number of submodules which are input for corresponding upper bridge arms;
Unα(m),Unβand (m) are respectively the alpha-axis and beta-axis components of the lower bridge arm voltage by adopting the m-th seed module input method, and the calculation method is the same as that of the corresponding components of the upper bridge arm.
3. The system according to claim 1 or 2, characterized in that: in the objective function calculation module, the objective function JmThe specific calculation method is as follows:
Jm＝|Ipαref-Ipα(next)(m)|+|Ipβref-Ipβ(next)(m)|+|Inαref-Inα(next)(m)|+|Inβref-Inβ(next)(m)|
wherein, JmIs an objective function using the mth seed module input method.
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