A method for fault ride-through control of a modular multilevel converter

Abstract

The present invention discloses a fault-resistant operation control method for a modular multi-level converter, comprising the steps of collecting arm current signals and submodule capacitor voltage signals of the modular multi-level converter; estimating the number of faulty submodules based on the collected data; and constructing a circulating current i ac , AC current i ao In the prediction model of the k+1th period, the unique n that minimizes the cost function is obtained by traversing and optimizing. ap p (k+1) and n an p (k+1) combination; arrange the bridge arm submodule capacitor voltages in the order of small to large or large to small, and select n according to the polarity direction of the bridge arm current. ap p (k+1) upper bridge arm submodules are put into use, and n an p (k+1) lower-arm submodules are put into operation. This control method can optimize the fault location process under open-circuit faults in modular multilevel converters, thereby achieving open-circuit fault-immune operation of the modular multilevel converter and preventing threats to converter reliability from overcurrent in the lower arms and overvoltage in the submodule capacitors.

Description

Technical Field

[0001] The present invention belongs to the technical field of direct current transmission, relates to the reliability of medium and high voltage power electronic converters, and in particular to a fault-immune operation control method for a modular multi-level converter. Background Art

[0002] Modular multilevel converter systems are large, comprising numerous submodules, each of which contains several power switching devices. Power switching devices are among the most vulnerable components in modular multilevel converters. Their fault types primarily include short-circuit and open-circuit faults. Short-circuit faults in power switching devices can be quickly protected and located using desaturation units integrated into the drive circuits. However, open-circuit faults in power switching devices do not readily induce noticeable submodule-level fault signatures, making it difficult to quickly identify and bypass the faulty submodule. The time-consuming fault location process can lead to failure of the modular multilevel converter's circulating current control, overcurrent in bridge arms, overvoltage in healthy submodules, and impaired power quality. This can trigger a series of chain reactions, and in severe cases, even secondary faults, threatening the reliable operation of the modular multilevel converter and causing significant system losses.

[0003] Therefore, open-circuit power switch failures threaten the reliable operation of modular multilevel converters. Exploring fault-tolerant operation strategies for modular multilevel converters under open-circuit power switch failures to ensure the safe operation of flexible DC transmission and distribution systems is a major issue that urgently needs research. Summary of the Invention

[0004] The purpose of the present invention is to provide a fault-immune operation control method for a modular multilevel converter, which can control and optimize the fault location process under an open-circuit fault of the modular multilevel converter, thereby achieving fault-immune operation of the modular multilevel converter and avoiding threats to converter reliability caused by bridge arm overcurrent and submodule capacitor overvoltage.

[0005] In order to achieve the above object, the solution of the present invention is:

[0006] A fault-immune operation control method for a modular multi-level converter, comprising:

[0007] Step 1: Collect the bridge arm current signal i of the modular multilevel converter ap with i an , and the submodule capacitor voltage signal u Ci , i = 1, 2, ..., N, where N is the number of submodules in a single bridge arm of the modular multilevel converter;

[0008] Step 2: Estimate the number of faulty submodules based on the collected data;

[0009] Step 3: Build the circulation circuit of modular multilevel converter ac , AC current i ao In the prediction model of the k+1th period, the unique n that minimizes the cost function is obtained by traversing and optimizing. ap p (k+1) and n an p The (k+1) combination is the predicted value of the number of upper bridge arm and lower bridge arm sub-modules put into use in the k+1 cycle;

[0010] Step 4: Arrange the bridge arm submodule capacitor voltages in the order of small to large or large to small, and select n according to the polarity direction of the bridge arm current. ap p (k+1) upper bridge arm submodules are put into use, and n an p (k+1) lower bridge arm submodules are put into use.

[0011] The specific content of the above step 2 is to estimate the actual voltage of the bridge arm based on the collected data, and estimate the actual number of sub-modules put into operation based on the actual value of the bridge arm voltage. The difference between the actual number of sub-modules put into operation and the predicted number of sub-modules put into operation is the estimated number of faulty sub-modules.

[0012] Among them, based on the collected data, the actual voltage of the bridge arm is estimated, including:

[0013] The circulation i through the kth cycle ac With the output current i ao Estimate the actual voltage v of the upper bridge arm and the lower bridge arm ap ε (k) and v an ε (k):

[0014]

[0015] Among them, T c is the control cycle of model predictive control, k represents the kth control cycle of model predictive control; the superscript ε represents the actual value of the corresponding variable, L f With L s They represent the AC equivalent inductance and bridge arm inductance of the modular multilevel converter respectively; R represents the load resistance, U dc Represents the DC voltage of the modular multilevel converter.

[0016] Among them, the number of submodules actually put into use is estimated based on the actual value of the bridge arm voltage, including:

[0017] Actual value of the number of submodules put into use n ap ε (k) and n anε (k) represents,

[0018]

[0019] wherein, U C is the capacitor voltage rating of the modular multilevel converter sub-module.

[0020] wherein, the difference between the actual value of the number of sub-modules put into operation and the predicted value of the number of sub-modules put into operation is the estimated number of faulty sub-modules, including,

[0021]

[0022] wherein, p represents the predicted value of the corresponding variable, n ap p (k) and n an p (k) represents the predicted value of the number of sub-modules put into operation in the kth control period; n ap ε (k) and n an ε (k) represents the actual value of the number of sub-modules put into operation, n apf (k) and n anf (k) represents the estimated number of faulty sub-modules.

[0023] The specific content of the above step 3 is to establish the circulating current i ac , the alternating current i ao The prediction model in the k+1th period is as follows:

[0024]

[0025] wherein, v ap p (k+1) and v an p (k+1) respectively represent the predicted voltage of the upper bridge arm and the lower bridge arm in the k+1th control period, as follows:

[0026]

[0027] wherein, ΔN ap (k+1) and ΔN an (k+1) are correction factors of the time-varying model predictive control, and the value is the estimated number of faulty sub-modules;

[0028] Determine the control target value of the prediction model, that is, the alternating current target value and the circulating current target value i ao * (k+1) and i ac *(k+1) are respectively:

[0029]

[0030] wherein m is a modulation degree of the modular multilevel converter, I dc is a direct current of the modular multilevel converter, is an operating power factor of the modular multilevel converter;

[0031] determining a cost function of the prediction model:

[0032]

[0033] wherein w o and w c are weight coefficients of AC and circulating current control in the cost function; based on the prediction model and the control target value, a unique n ap p (k+1) and n an p (k+1) combination, that is, the prediction value of the number of sub-modules put into the (k+1) period.

[0034] In the above step 4, n ap p (k+1) upper bridge arm sub-modules are put into, and n an p (k+1) lower bridge arm sub-modules are put into, and the principle of selecting the sub-modules is that the sub-modules with low capacitor voltage are preferentially charged, and the sub-modules with high capacitor voltage are preferentially discharged, so as to keep the capacitor voltage of each bridge arm internal sub-module balanced around the rated value.

[0035] With the above scheme, the present application is studied and analyzed in view of the prior art, and the open-circuit fault positioning and fault positioning fault-tolerant control operation of the modular multilevel converter are widely studied at present, and the fault suppression and disturbance resistance operation of the modular multilevel converter in the open-circuit fault positioning process are ignored. The time required for the open-circuit fault positioning of the modular multilevel converter is at least one fundamental frequency period, and the lack of control of the modular multilevel converter during this process will lead to fault phenomena and disturbances such as bridge arm overcurrent, submodule overvoltage, reduced AC power quality, and DC bus current pulsation. The present application combines feedback control and model predictive control to adjust the correction factor of the prediction model of the modular multilevel converter in real time, establish an accurate prediction model of the modular multilevel converter under fault, and based on a suitable cost function and weight coefficient, ensure that the number of bridge arm submodule inputs output by the model predictive control under open-circuit fault can meet the compensation demand of bridge arm voltage output, thereby avoiding the fault disturbance caused by open-circuit fault to the bridge arm and above. The present application effectively realizes that the bridge arm current, submodule voltage, AC power quality, DC bus current and the like under the open-circuit fault of the submodule power device are consistent with the normal operation of the modular multilevel converter, and improves the operation reliability of the modular multilevel converter system under the open-circuit fault of the submodule. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 is a schematic diagram of the modular multilevel converter topology based on a half-bridge submodule;

[0037] wherein (a) is a whole topology structure diagram, and (b) is a structure schematic diagram of each module;

[0038] Figure 2 is a schematic diagram of the current flow path under the open-circuit fault of the half-bridge submodule;

[0039] wherein (a) is that the upper tube of the half-bridge submodule occurs open-circuit fault, and (b) is that the lower tube of the half-bridge submodule occurs open-circuit fault;

[0040] Figure 3 is a fault disturbance resistance operation control block diagram of the modular multilevel converter in the present application;

[0041] Figure 4 is a fault state diagnosis flowchart of the modular multilevel converter;

[0042] Figure 5 is a fault disturbance resistance operation simulation result of the modular multilevel converter in the present application;

[0043] wherein (a) is the fault operation waveform of the modular multilevel converter under the traditional control, and (b) is the fault disturbance resistance operation waveform of the modular multilevel converter under the control of the present application. DETAILED DESCRIPTION

[0044] The technical solutions and beneficial effects of the present application will be described in detail below with reference to the drawings.

[0045] Figure 1 is a three-phase topology structure of a classic modular multilevel converter, and each phase includes N half-bridge sub-modules in the upper and lower bridge arms.

[0046] Figure 2 The bridge arm current (the upper bridge arm current i ap , and the lower bridge arm current i an ) path when the upper and lower tubes of the half-bridge sub-module respectively occur open circuit faults is shown. Figure 2 In (a), when the upper tube of the half-bridge sub-module occurs an open circuit fault, the voltage output and the current flow path of the half-bridge sub-module are not affected when the bridge arm current is negative, and the actual output voltage of the half-bridge sub-module is consistent with the reference output voltage; when the bridge arm current is negative, the upper tube IGBT is difficult to turn on when the half-bridge sub-module output voltage reference signal is 1, and the bridge arm current can only flow through the antiparallel diode of the lower tube, the voltage output is 0, which is inconsistent with the reference signal, resulting in the following deviation of the bridge arm voltage v ap and v an (wherein, the upper subscript r represents the reference value, f represents the actual value under the fault, U C represents the rated voltage of the sub-module capacitor, ΔN ap f and ΔN an f respectively represent the number of fault sub-modules of the upper bridge arm and the lower bridge arm)

[0047]

[0048] Figure 2 In (b), when the lower tube of the half-bridge sub-module occurs an open circuit fault, the voltage output and the current flow path of the half-bridge sub-module are not affected when the bridge arm current is negative, and the actual output voltage of the half-bridge sub-module is consistent with the reference output voltage; when the bridge arm current is positive, the lower tube IGBT is difficult to turn on when the half-bridge sub-module output voltage reference signal is 0, and the bridge arm current can only flow through the antiparallel diode of the upper tube, the voltage output is 1, which is inconsistent with the reference signal, resulting in the following deviation of the bridge arm voltage:

[0049]

[0050] Taking the a phase as an example, the open circuit fault anti-interference operation control method of the modular multilevel converter described in the present application is as follows:

[0051] Figure 3The modular multilevel converter fault ride-through operation control strategy is shown, which is divided into two parts, the first part is a time-varying model predictive control method, and the second part is a correction factor adaptive adjustment method.

[0052] The time-varying model predictive control method has the following specific embodiments:

[0053] Step one: current / voltage sampling: collect the bridge arm current signal and submodule capacitor voltage signal of the modular multilevel converter, including the upper bridge arm current i ap , the lower bridge arm current i an and the submodule capacitor voltage signal u Ci , i=1, 2, …, N, N is the number of submodules of a single bridge arm of the modular multilevel converter.

[0054] Step two: the correction factor calculation and adaptive adjustment method of the prediction model in the variable model predictive control in the application is determined as follows: first, the actual voltage v ac ao (k) of the upper and lower bridge arms is estimated by the circulating current i ap and the alternating current i ε (k) of the last period: an ε (k):

[0055]

[0056] Where T c is the control period of the model predictive control, k represents the kth control period of the model predictive control. The upper index ε represents the actual value of the corresponding variable, L f and L s represent the alternating current equivalent inductance and bridge arm inductance of the modular multilevel converter respectively. R represents the load resistance, and U dc represents the DC voltage of the modular multilevel converter.

[0057] Secondly, the number of faulty submodules of the upper and lower bridge arms can be estimated according to the difference between the actual value and the reference value of the bridge arm voltage, and this number of submodules is also the adaptive correction factor of the prediction model in the variable model predictive control. In this embodiment, the actual value n ap ε (k) of the number of submodules put into operation and n an ε (k) are represented as:

[0058]

[0059] Where U C is the rated value of the submodule capacitor voltage of the modular multilevel converter.

[0060] The actual value of the number of sub-modules is obtained by substituting formula (4) into formula (3). The number of faulty sub-modules of the upper and lower bridge arms can be estimated according to the difference between the actual value and the predicted value of the number of sub-modules, as follows

[0061]

[0062] where p represents the predicted value of the corresponding variable, n ap p (k) represents the predicted value of the number of sub-modules in the kth control period. an p (k) represents the predicted value of the number of sub-modules in the kth control period.

[0063] Meanwhile, the number of sub-modules is also the adaptive correction factor ΔN ap (k+1) and ΔN an (k+1) of the prediction model in the (k+1)th period in the variable model predictive control, as follows:

[0064]

[0065] In summary, the estimation formula of the number of faulty sub-modules of the upper and lower bridge arms is as follows:

[0066]

[0067] Step three: establish the circulating current i ac , the AC current i ao of the modular multilevel converter

[0068]

[0069] where T c is the control period of the model predictive control, k represents the kth control period of the model predictive control, the upper index p represents the predicted value of the corresponding variable, L f and L s respectively represent the AC equivalent inductance and the bridge arm inductance of the modular multilevel converter.

[0070] where v ap p (k+1) and v an p (k+1) respectively represent the predicted voltage of the upper bridge arm and the lower bridge arm. For the traditional model predictive control, the calculation method of the predicted value of the bridge arm voltage is as follows:

[0071]

[0072] This calculation method does not consider the influence of the faulty sub-modules on the output of the bridge arm voltage, and it is difficult to realize the fault-resistant operation.

[0073] In the time-varying model predictive control, the bridge arm voltage prediction value v ap p (k+1) and v an p The calculation method of v

[0074]

[0075] Where, ΔN ap , ΔN an respectively represent the fault sub-modules of the upper and lower bridge arms, also known as the correction factor of the time-varying model predictive control, which can be adaptively adjusted according to the fault condition of the modular multilevel converter, thereby correcting the model predictive control and realizing the fault-resistant operation of the sub-modules of the modular multilevel converter.

[0076] Step four: determine the control target value of the variable model predictive control in the application, i.e. the AC current target value and the circulating current target value i ao * (k+1) and i ac * (k+1) are respectively:

[0077]

[0078] Where, m is the modulation degree of the modular multilevel converter, I dc is the DC current of the modular multilevel converter, is the operating power factor of the modular multilevel converter.

[0079] Step five: determine the cost function and weight coefficient of the variable model predictive control in the application:

[0080]

[0081] Where, w o and w c are the weight coefficients of the AC and circulating current control in the cost function. By substituting equation (8), equation (10) and equation (11) into equation (12) and traversing the optimization, the n ap p (k+1) and n an p (k+1) combination is the prediction value of the number of sub-modules put into the (k+1) period.

[0082] Step six: arrange the bridge arm sub-module capacitor voltages obtained by sampling in ascending or descending order, and select n ap p(k+1) upper bridge arm sub-modules are put in, and n an p (k+1) lower bridge arm sub-modules are put in, and the principle of selecting the sub-modules is that the sub-modules with low capacitor voltage are preferentially charged, and the sub-modules with high capacitor voltage are preferentially discharged, so as to keep the capacitor voltage of each bridge arm sub-module balanced around the rated value.

[0083] The switching signals of each sub-module of the bridge arm are obtained based on the above steps.

[0084] Figure 4 is a flow chart of fault diagnosis of the modular multilevel converter, when a sub-module fault occurs in the bridge arm, the fault state flag F is 1, and when the bridge arm is normally operated, the fault state flag F is 0. When F=1, the model predictive control correction factor realizes the correction of the predictive model of the modular multilevel converter under the sub-module fault, and when F=0, the predictive model is not affected by the fault correction factor. The above fault diagnosis is as follows:

[0085]

[0086] Wherein, θ1 and θ2 respectively represent error thresholds of output current and circulating current, which need to be set according to actual operation parameters of the modular multilevel converter.

[0087] Figure 5 is the implementation effect of the fault disturbance resistance operation of the modular multilevel converter based on the application, Figure 5 (a) is a simulation result of adopting a traditional modular multilevel converter model predictive control, in the fault positioning process, the bridge arm overcurrent and sub-module overvoltage, output current distortion and the like occur in phase a, Figure 5 (b) is a simulation result of adopting the time-varying model predictive control, in the fault positioning process and before the fault bypass, the operation state of the modular multilevel converter is not affected by the fault, and the fault disturbance resistance operation characteristics are shown.

[0088] The beneficial effects of the fault disturbance resistance operation of the modular multilevel converter are that when a sub-module fault occurs in the modular multilevel converter, the fault disturbance resistance operation method can avoid the fault overcurrent, sub-module capacitor overvoltage, output current distortion and the like, reduce the harm of the sub-module fault to the modular multilevel converter, avoid the further expansion of the fault range, reduce the harm of the internal module level fault to the system, and improve the reliability of the modular multilevel converter and the system in the fault transient process.

[0089] Those skilled in the art will appreciate that embodiments of the present application can be readily used as software, hardware, or a combination of software and hardware. In a software embodiment, the methods can be tangibly embodied in a machine-readable storage medium having stored thereon instructions that can be used to program a computer to perform any of the methods. The software implementation can be initialized by loading and executing a set of instructions arranged to perform one of the methods into the computer's memory. Alternatively, hard-wired circuitry can be used in place of, or in combination with, software instructions. Thus, the

[0090] The present application is described in reference to the flowchart illustrations and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in one or more of the flowchart illustrations and / or block diagrams. Figure 1 means for performing the functions specified in one or more of the flowchart illustrations and / or block diagrams.

[0091] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in one or more of the flowchart illustrations and / or block diagrams. Figure 1 means for performing the functions specified in one or more of the flowchart illustrations and / or block diagrams.

[0092] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in one or more of the flowchart illustrations and / or block diagrams. Figure 1 means for performing the functions specified in one or more of the flowchart illustrations and / or block diagrams.

[0093] While preferred embodiments of the application have been described, modifications and variations can be apparent to those skilled in the art once aware of the general underlying concepts. Accordingly, the appended claims are intended to encompass all modifications and variations as falling within the scope of the application.

[0094] It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application cover modifications and variations of this application provided they come within the scope of the appended claims and their equivalents.

Claims

1. A method for fault ride-through control of a modular multilevel converter, characterized in that: Comprising, Step 1, collecting bridge arm current signal i of modular multilevel converter ap With i an And sub-module capacitor voltage signal u Ci , i = 1, 2, …, N, N is the number of sub-modules of a single bridge arm of the modular multilevel converter; Step 2, estimating the number of faulty sub-modules according to the collected data; Step 3: Build the circulation circuit of modular multilevel converter ac , AC current i ao In the prediction model of the k+1th period, the only one that minimizes the cost function is obtained by traversing and optimizing. and The combination is the predicted value of the number of upper bridge arm and lower bridge arm sub-modules put into use in the k+1th cycle; Step 4, arrange the bridge arm submodule capacitor voltage according to the order from small to large or from large to small, according to the polarity direction of the bridge arm current, select one upper bridge arm submodule to put in, and one lower bridge arm submodule to put in; Wherein, the specific content of step 3 is to establish the circulating current i of the modular multilevel converter ac , the alternating current i ao The prediction model in the k+1 period is as follows: Wherein, T c is the control cycle of model predictive control, k represents the kth control cycle of model predictive control; L f and L s respectively represent the AC equivalent inductance and bridge arm inductance of the modular multilevel converter; R represents the load resistance, U dc represents the DC voltage of the modular multilevel converter; wherein, with respectively represent the predicted voltages of the upper bridge arm and the lower bridge arm in the k+1th control period, as follows: wherein U C is the modular multilevel converter sub-module capacitor voltage rating; wherein ΔN ap (k+1) and ΔN an (k+1) is a correction factor of the time-varying model predictive control, and the value is the estimated number of fault sub-modules. determining a control target value of the prediction model, i.e. an alternating current target value and a circulating current target value i ao * (k+1) and i ac * (k+1) are: wherein m is a modulation degree of the modular multilevel converter, I dc is a direct current of the modular multilevel converter, is an operating power factor of the modular multilevel converter; Determine the cost function of the prediction model: where w o and w c are the weight coefficients of the AC and the circulating current control in the cost function; based on the prediction model and the control target value, the unique and combination, which is the prediction value of the number of sub-modules to be put into the (k+1)th period.

2. The method of claim 1, wherein: The specific content of the step 2 is, according to the collected data, the actual voltage of the bridge arm is estimated, and the actual number of sub-modules is estimated according to the actual value of the bridge arm voltage, the difference between the actual value of the number of sub-modules and the predicted value of the number of sub-modules is the estimated number of faulty sub-modules.

3. The method of claim 2, wherein: According to the collected data, the actual voltage of the bridge arm is estimated, including, By the circulation i of the kth cycle ac With the output current i ao The actual voltage v of the bridge arm of the upper bridge arm and the lower bridge arm is estimated ap ε (k) With v an ε (k): Wherein, T c is the control cycle of model predictive control, k represents the kth control cycle of model predictive control; the upper subscript epsilon represents the actual value of the corresponding variable, L f and L s respectively represent the AC equivalent inductance and the bridge arm inductance of the modular multilevel converter; R represents the load resistance, U dc represents the DC voltage of the modular multilevel converter.

4. The method of claim 3, wherein: According to the actual value of the bridge arm voltage, the actual number of sub-modules is estimated, including, Actual value of number of sub-modules put in n ap ε (k) is represented as an ε (k) is represented as where U C is the modular multilevel converter sub-module capacitor voltage rating.

5. The method of claim 2, wherein: The difference between the actual value of the number of sub-modules and the predicted value of the number of sub-modules is the estimated number of faulty sub-modules, including, wherein p represents the predicted value of the corresponding variable, with n(k) represents the predicted value of the number of sub-modules in the kth control period; ap ε (k) represents the actual value of the number of sub-modules, n an ε (k) represents the actual value of the number of sub-modules, n apf (k) represents the actual value of the number of sub-modules, n anf (k) represents the estimated number of failed sub-modules.

6. The method of claim 1, wherein: In step 4, select The upper arm submodule is put into use, and The principle of selecting sub-modules is that sub-modules with low capacitor voltage are charged first and sub-modules with high capacitor voltage are discharged first, so as to keep the capacitor voltage balance of sub-modules in each bridge arm near the rated value.

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