Fault anti-interference operation control method for modular multilevel converter

Abstract

The invention discloses a fault anti-interference operation control method for a modular multi-level converter, and the method comprises the steps: collecting a bridge arm current signal of the modular multi-level converter and a sub-module capacitor voltage signal; estimating the number of fault sub-modules according to the collected data; the method comprises the following steps: constructing a prediction model of circulating current iac and alternating current iao of the modular multilevel converter in a (k + 1) th period, and obtaining a unique nappp (k + 1) and nano (k + 1) combination which enables a cost function to be minimum through traversal optimization; and arranging capacitor voltages of the bridge arm sub-modules according to a sequence from small to large or from large to small, and selecting nappp (k + 1) upper bridge arm sub-modules and nappp (k + 1) lower bridge arm sub-modules for input according to the polarity direction of the bridge arm current. According to the control method, the fault positioning process under the open-circuit fault of the modular multi-level converter can be controlled and optimized, so that the open-circuit fault anti-interference operation of the modular multi-level converter is realized, and the reliability of the converter is prevented from being threatened by over-current of a bridge arm and over-voltage of a sub-module capacitor.

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-resistant operation control method of a modular multi-level converter. Background Art

[0002] The modular multilevel converter system is huge and contains many submodules, each of which contains several power switching devices. The power switching device is one of the most vulnerable components in the modular multilevel converter. Its fault types mainly include short-circuit fault and open-circuit fault. The short-circuit fault of the power switching device can be quickly protected and located in a very short time by integrating the desaturation unit in the drive circuit, while the open-circuit fault of the power switching device is not easy to cause significant fault characteristics at the submodule level in a short time, making it difficult to quickly identify and bypass the faulty submodule. The fault location process takes a certain amount of time, which may cause the failure of the circulating current control of the modular multilevel converter, overcurrent of the bridge arm, overvoltage of the healthy submodule, and damage to the power quality, thereby triggering a series of chain reactions. In severe cases, it may even cause secondary faults, threatening the reliable operation of the modular multilevel converter and causing significant losses to the system.

[0003] Therefore, open-circuit faults of power switching devices threaten the reliable operation of modular multilevel converters. Exploring the fault-resistant operation strategy of modular multilevel converters under open-circuit faults of power switching devices to ensure the safe operation of flexible DC transmission and distribution systems is a major issue that needs to be studied urgently. Summary of the invention

[0004] The purpose of the present invention is to provide a fault-resistant 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 realizing the fault-resistant operation of the modular multilevel converter and avoiding the threats to the converter reliability caused by overcurrent of the bridge arm and overvoltage of the submodule capacitor.

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

[0006] A fault-resistant operation control method for a modular multilevel 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, N is the number of sub-modules of 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 of modular multilevel converter ac , AC current i ao In the prediction model of the k+1th period, by traversing and optimizing, the unique n that minimizes the cost function is obtained 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 submodules put into use in the k+1th cycle;

[0010] Step 4: Arrange the bridge arm submodule capacitor voltages in order from small to large or from 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 operation.

[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 period of model predictive control, k represents the kth control period 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 number of submodules invested n ap ε (k) and n anε (k) is expressed as,

[0018]

[0019] Among them, U C is the rated voltage of the capacitor of the modular multilevel converter submodule.

[0020] Among them, the difference between the actual number of submodules put into use and the predicted number of submodules put into use is the estimated number of faulty submodules, including:

[0021]

[0022] Among them, 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 submodules in the kth control cycle; n ap ε (k) and n an ε (k) represents the actual number of submodules, 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 circulation i of the modular multilevel converter ac , AC current i ao The prediction model in the k+1th period is as follows:

[0024]

[0025] Among them, v ap p (k+1) and v an p (k+1) represents the predicted voltage of the upper bridge arm and the lower bridge arm in the k+1th control cycle, as follows:

[0026]

[0027] Among them, ΔN ap (k+1) and ΔN an (k+1) is the correction factor of the time-varying model predictive control, and its value is the estimated number of fault submodules;

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

[0029]

[0030] Where m is the modulation index 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;

[0031] Determine the cost function of the prediction model:

[0032]

[0033] Among them, w o With w c are the weight coefficients of AC and circulating flow control in the cost function respectively; based on the prediction model and the control target value, 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 sub-modules put into use in the (k+1)th period.

[0034] In step 4 above, select n 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 operation. The principle of selecting submodules is that submodules with low capacitor voltage are charged first, and submodules with high capacitor voltage are discharged first, so as to keep the capacitor voltage balance of the submodules in each bridge arm near the rated value.

[0035] After adopting the above scheme, the present invention studies and analyzes the prior art. At present, the most extensive research on the open-circuit fault of the modular multilevel converter is the open-circuit fault location and the fault-tolerant control operation after the fault location, ignoring the fault suppression and anti-disturbance operation of the modular multilevel converter during the open-circuit fault location process. The time required for the open-circuit fault location of the modular multilevel converter is at least one fundamental frequency cycle. During this process, the lack of control of the modular multilevel converter will lead to fault phenomena and disturbances such as bridge arm overcurrent, submodule overvoltage, AC power quality reduction, and DC bus current pulsation. The present invention combines feedback control with model predictive control to adjust the correction factor of the modular multilevel converter prediction model in real time, establish an accurate prediction model of the modular multilevel converter under fault, and ensure that the number of bridge arm submodules output by the model predictive control under the open-circuit fault can meet the compensation demand of the bridge arm voltage output based on the appropriate cost function and weight coefficient, thereby avoiding the fault disturbance of the bridge arm and above caused by the open-circuit fault. The present invention effectively ensures that the bridge arm current, submodule voltage, AC power quality, DC bus current, etc. under the open circuit fault of the submodule power device are consistent with the normal operation of the modular multilevel converter, thereby improving the operational reliability of the modular multilevel converter system under the open circuit fault of the submodule. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0037] Among them, (a) is the overall topology diagram, and (b) is the structural diagram of each module;

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

[0039] Among them, (a) is an open circuit fault of the upper tube of the half-bridge submodule, and (b) is an open circuit fault of the lower tube of the half-bridge submodule;

[0040] Figure 3 It is a fault-resistant operation control block diagram of a modular multilevel converter in the present invention;

[0041] Figure 4 It is a modular multilevel converter fault status diagnosis flow chart;

[0042] Figure 5 It is the simulation result of the fault-resistant operation of the modular multilevel converter in the present invention;

[0043] Among them, (a) is the fault operation waveform of the modular multilevel converter under traditional control, and (b) is the fault anti-disturbance operation waveform of the modular multilevel converter under the control of the present invention. DETAILED DESCRIPTION

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

[0045] Figure 1 It is a three-phase topology structure of a classic modular multi-level converter, and the upper and lower bridge arms in each phase include N half-bridge sub-modules. The relevant principles and specific solutions of the present invention are explained by taking phase a as an example.

[0046] Figure 2 The figure shows the bridge arm current when the upper and lower tubes of the half-bridge submodule are open circuit faults (upper bridge arm current i ap , the lower bridge arm current i an )path. Figure 2 In (a), an open circuit fault occurs on the upper tube of the half-bridge submodule. When the bridge arm current is negative, the voltage output and current flow path of the half-bridge submodule are not affected, and the actual output voltage of the half-bridge submodule is consistent with the reference output voltage; when the bridge arm current is negative, when the output voltage reference signal of the half-bridge submodule is 1, the upper tube IGBT is difficult to turn on, and the bridge arm current can only flow through the anti-parallel diode of the lower tube. The voltage output is 0, which is inconsistent with the reference signal, resulting in the bridge arm voltage v ap With v an The following deviations are generated (where superscript r represents the reference value, f represents the actual value under fault conditions, and U C Indicates the rated voltage of the submodule capacitor, ΔN ap f and ΔN an f Respectively represent the number of faulty submodules of the upper bridge arm and the lower bridge arm)

[0047]

[0048] Figure 2 In (b), an open circuit fault occurs in the lower tube of the half-bridge submodule. When the bridge arm current is negative, the voltage output and current flow path of the half-bridge submodule are not affected, and the actual output voltage of the half-bridge submodule is consistent with the reference output voltage; when the bridge arm current is positive, the output voltage reference signal of the half-bridge submodule is 0, the lower tube IGBT is difficult to turn on, and the bridge arm current can only flow through the anti-parallel 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 phase a as an example, the open-circuit fault anti-disturbance operation control method of a modular multi-level converter described in the present invention is as follows:

[0051] Figure 3The figure shows a fault-resistant operation control strategy for a modular multi-level converter according to the present invention, 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 specific implementation scheme of the time-varying model predictive control method is as follows:

[0053] Step 1: 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 , lower bridge arm current i an And the submodule 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.

[0054] Step 2: Determine the correction factor calculation and adaptive adjustment method of the prediction model in the variable model prediction control of the present invention. First, the circulation i of the previous cycle is ac With the alternating 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):

[0055]

[0056] Among them, T c is the control cycle of the model predictive control, k represents the kth control cycle of the 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.

[0057] Secondly, the number of faulty submodules of the upper and lower bridge arms can be estimated based on the difference between the actual value of the bridge arm voltage and the reference value. At the same time, the number of submodules is also the adaptive correction factor of the prediction model in the variable model predictive control. ap ε (k) and n an ε (k) is expressed as:

[0058]

[0059] Among them, U C is the rated voltage of the capacitor of the modular multilevel converter submodule.

[0060] Substituting formula (4) into formula (3), we can get the actual value of the number of submodules put into operation. According to the difference between the actual value and the predicted value of the number of submodules put into operation, we can estimate the number of faulty submodules in the upper and lower bridge arms, as follows:

[0061]

[0062] Among them, 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 use in the kth control cycle.

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

[0064]

[0065] In summary, the formula for estimating the number of faulty submodules in the upper and lower bridge arms is as follows:

[0066]

[0067] Step 3: Establish the circulating current i of modular multilevel converter ac , AC current i ao The prediction model in the (k+1)th period is as follows:

[0068]

[0069] Among them, T c is the control cycle of the model predictive control, k represents the kth control cycle of the model predictive control, the superscript p represents the predicted value of the corresponding variable, and L f With L s They represent the AC equivalent inductance and bridge arm inductance of the modular multilevel converter respectively.

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

[0071]

[0072] This calculation method does not take into account the impact of the faulty submodule on the bridge arm voltage output, making it difficult to achieve fault-resistant operation.

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

[0074]

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

[0076] Step 4: Determine the control target value of the variable model predictive control in the present invention, that is, the AC current target value and the circulating current target value i ao * (k+1) and i ac * (k+1) are:

[0077]

[0078] Where m is the modulation index 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 5: Determine the cost function and weight coefficient of the variable model predictive control in the present invention:

[0080]

[0081] Among them, w o With w c are the weight coefficients of AC and circulating current control in the cost function respectively. Substituting equations (8), (10) and (11) into equation (12), we can obtain the n that minimizes the cost function by traversing and optimizing. ap p (k+1) and n an p The (k+1) combination is the predicted value of the number of sub-modules put into use in the (k+1)th period.

[0082] Step 6: Arrange the sampled bridge arm submodule capacitor voltages in order from small to large or from 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 operation. The principle of selecting submodules is that submodules with low capacitor voltage are charged first, and submodules with high capacitor voltage are discharged first, so as to keep the capacitor voltage balance of the submodules in each bridge arm near the rated value.

[0083] Based on the above steps, a switching signal of each submodule of the bridge arm is obtained.

[0084] Figure 4 It is a fault diagnosis flow chart of modular multilevel converter. When a submodule fault occurs in the bridge arm, the fault status flag F is 1. When the bridge arm operates normally, the fault status flag F is 0. When F=1, the model predictive control correction factor realizes the correction of the modular multilevel converter prediction model under the submodule fault. When F=0, the prediction model is not affected by the fault correction factor. The above fault diagnosis basis is as follows:

[0085]

[0086] Among them, θ 1 With θ 2 They represent the error thresholds of the output current and the circulating current respectively, and need to be set according to the actual operating parameters of the modular multilevel converter.

[0087] Figure 5 Based on the implementation effect of the fault-resistant operation of the modular multilevel converter described in the present invention, Figure 5 (a) is the simulation result of the traditional modular multi-level converter model predictive control. During the fault location process, bridge arm overcurrent, submodule overvoltage, output current distortion, etc. occurred in phase a. Figure 5 (b) is a simulation result of the time-varying model predictive control according to the present invention. During the fault location process and before the fault bypass, the operating state of the modular multilevel converter is not affected by the fault, showing fault-resistant operating characteristics.

[0088] The beneficial effect of the fault-resistant operation of the modular multilevel converter of the present invention is that when a sub-module fault occurs in the modular multilevel converter, the fault-resistant operation method of the present invention can avoid fault overcurrent, sub-module capacitor overvoltage, output current distortion, etc., reduce the harm of the sub-module fault to the modular multilevel converter, avoid further expansion of the fault range, reduce the harm of internal module-level faults to the system, and improve the reliability of the modular multilevel converter and the system during the fault transient process.

[0089] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0090] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0091] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0092] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0093] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0094] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A fault-resistant operation control method for a modular multilevel converter, characterized in that: include, 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, N is the number of sub-modules of a single bridge arm of the modular multilevel converter; Step 2: Estimate the number of faulty submodules based on the collected data; Step 3: Build the circulation of modular multilevel converter ac , AC current i ao In the prediction model of the k+1th period, by traversing and optimizing, the unique n that minimizes the cost function is obtained 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 submodules put into use in the k+1th cycle; Step 4: Arrange the bridge arm submodule capacitor voltages in order from small to large or from 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.

2. The method according to claim 1, characterized in that: The specific content of 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.

3. The method according to claim 2, characterized in that: According to the collected data, the actual voltage of the bridge arm is estimated, including: 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): Among them, T c is the control period of model predictive control, k represents the kth control period 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.

4. The method according to claim 3, characterized in that: According to the actual value of the bridge arm voltage, the actual number of sub-modules put into use is estimated, including: Actual value of number of submodules invested n ap ε (k) and n an ε (k) is expressed as, Among them, U C is the rated voltage of the capacitor of the modular multilevel converter submodule.

5. The method according to claim 2, characterized in that: The difference between the actual number of submodules put into use and the predicted number of submodules put into use is the estimated number of faulty submodules, including: Among them, 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 submodules in the kth control cycle; n ap ε (k) and n an ε (k) represents the actual number of submodules, n apf (k) and n anf (k) represents the estimated number of faulty sub-modules.

6. The method according to claim 1, characterized in that: The specific content of step 3 is to establish a circulating current i of the modular multi-level converter. ac , AC current i ao The prediction model in the k+1th period is as follows: Among them, v ap p (k+1) and v an p (k+1) represents the predicted voltage of the upper bridge arm and the lower bridge arm in the k+1th control cycle, as follows: Among them, ΔN ap (k+1) and ΔN an (k+1) is the correction factor of the time-varying model predictive control, and its value is the estimated number of fault submodules; Determine the control target value of the prediction model, that is, the AC current target value and the circulating current target value i ao * (k+1) and i ac * (k+1) are: Where m is the modulation index 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; Determine the cost function of the prediction model: Among them, w o With w c are the weight coefficients of AC and circulating flow control in the cost function respectively; based on the prediction model and the control target value, 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 sub-modules put into use in the (k+1)th period.

7. The method according to claim 1, characterized in that: In step 4, select n 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 operation. The principle of selecting submodules is that submodules with low capacitor voltage are charged first, and submodules with high capacitor voltage are discharged first, so as to keep the capacitor voltage balance of the submodules in each bridge arm near the rated value.

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