Multilevel converter specific harmonic elimination modulation method and system

Abstract

The present invention provides a multi-level converter specific harmonic elimination modulation method and system, belonging to the field of converter control technology, collecting modular multi-level converter output phase voltage; based on the modular multi-level converter output phase voltage, calculating the actual harmonic spectrum; combining the actual harmonic spectrum and the error of the voltage vector generated based on the fundamental modulation ratio, calculating the disturbance compensation angle; adding the calculated disturbance compensation angle to the corresponding switch angle under different fundamental modulation ratios obtained by offline calculation, to obtain the actual switch angle, which is used to directly drive the modular multi-level converter. The present invention realizes the real-time update of the switch angle following the error change, reduces the low-order harmonic content, and improves the output waveform accuracy of the modular multi-level converter; it can be applied to different converter models without obtaining the precise model parameters of the converter in advance and adjusting the control parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of converter control, and in particular to an online adaptive modular multi-level converter specific harmonic elimination modulation method and system. Background Art

[0002] The application of specific harmonic elimination pulse width modulation (SHE-PWM) technology in actual industrial conditions needs to consider the following issues: 1) There are fluctuations in DC voltage. If the switching angle still uses the solution under ideal conditions, it will cause considerable low-order harmonics in the output voltage waveform; 2) The modular multi-level converter is composed of multiple units with small differences. Dead time and transmission delay will cause the switching angle to shift, which is called the lead-lag displacement (LLP) error, which will also cause low-order harmonic errors in the output waveform.

[0003] Specific harmonic elimination pulse width modulation (SHE-PWM) can accurately eliminate each low-order harmonic. Compared with traditional carrier pulse width modulation, it has higher waveform quality at the same switching frequency. It is a modulation strategy that is very suitable for high-power and high-voltage industrial applications. The key to realizing SHE-PWM technology lies in the generation of switching angles. The most commonly used methods are: 1) determining dozens of optimal solutions in discrete form through offline analytical, numerical or heuristic search algorithms; 2) storing these solutions in a lookup table; 3) calculating the approximate solution of any given modulation ratio online through linear interpolation. However, the above SHE-PWM solutions are usually based on two premises: 1) the DC voltage of the converter is uniform and constant, that is, an ideal DC power supply; 2) ignoring the offset error of the switching angle. But these assumptions may not be met in actual industrial applications, especially for high-power modular multi-level converters.

[0004] First, in the case of non-ideal DC sources (NIDs), that is, DC voltage fluctuations, if the switching angle still uses the ideal solution, it will cause considerable low-order harmonics in the output voltage waveform. To address this problem, existing methods use artificial neural networks to train the switching angles using fluctuating DC voltage data sets. In these methods, all DC voltages must be used as inputs to the neural network. However, this neural network-based method requires detailed DC voltage data to be obtained in advance to train the neural network offline. Therefore, the performance is heavily dependent on the training set, and the training is highly correlated with the converter model parameters. This offline preset method cannot guarantee the accuracy of the output switching angle based on limited training data. Another solution is to speed up the solution to deal with the errors caused by NID.

[0005] Secondly, the bias error of the multilevel converter will also affect the power quality of the output waveform. This is because the multilevel converter is usually composed of many individual units with small differences. Non-ideal factors of the switching angle, such as dead time and transmission delay, will produce low-order harmonic errors, which will have a negative impact on SHE-PWM. An existing SHE phase jitter method is used to compensate for background disturbances. This method needs to be designed based on the model parameters of the converter. However, in practice, the pulsation position is difficult to measure. In other words, the error caused by LLP is a black box error, so there is not much available information about the model parameters and it cannot be used in industrial practice.

[0006] In addition, existing technologies mostly use dSPACE control systems as algorithm execution platforms, but the high-performance control systems in laboratories do not meet the low-cost requirements of actual industrial application scenarios. Summary of the invention

[0007] The object of the present invention is to provide an online adaptive modular multi-level converter specific harmonic elimination modulation method and system with high control accuracy, fast calculation speed, no need to adjust control parameters, and high universality, so as to solve at least one technical problem existing in the above-mentioned background technology.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions:

[0009] In one aspect, the present invention provides a multi-level converter specific harmonic elimination modulation method, comprising:

[0010] Collect the output phase voltage of modular multilevel converter;

[0011] Calculate the actual harmonic spectrum based on the output phase voltage of the modular multilevel converter;

[0012] The disturbance compensation angle is calculated by combining the actual harmonic spectrum and the error of the voltage vector generated based on the fundamental wave modulation ratio;

[0013] The calculated disturbance compensation angle is added to the corresponding off-line calculated switching angle under different fundamental modulation ratios to obtain an actual switching angle for directly driving the modular multi-level converter.

[0014] Preferably, the switch angles under different fundamental modulation ratios obtained by offline calculation include: using a radial basis function neural network, a back propagation neural network or a classic lookup table to offline solve the solutions of the switch angles corresponding to different fundamental modulation ratios.

[0015] Preferably, the output phase voltage of the modular multi-level converter is collected in real time, and a fast Fourier transform is performed to obtain an actual harmonic spectrum.

[0016] Preferably, the error between the actual harmonic spectrum and the reference value is fed into a multi-objective optimization cost function, and solved using a particle swarm optimization algorithm. When the particle swarm optimization algorithm link converges, disturbance compensation is obtained.

[0017] In a second aspect, the present invention provides a multi-level converter specific harmonic elimination modulation system, comprising:

[0018] A collection module, used for collecting output phase voltages of modular multi-level converters;

[0019] A first calculation module is used to calculate an actual harmonic spectrum based on an output phase voltage of the modular multilevel converter;

[0020] A second calculation module is used to calculate a disturbance compensation angle by combining an actual harmonic spectrum and an error of a voltage vector generated based on a fundamental wave modulation ratio;

[0021] The third calculation module is used to add the calculated disturbance compensation angle to the corresponding switching angle under different fundamental modulation ratios calculated offline to obtain an actual switching angle for directly driving the modular multi-level converter.

[0022] In a third aspect, the present invention provides a non-transitory computer-readable storage medium, which is used to store computer instructions. When the computer instructions are executed by a processor, the multi-level converter specific harmonic elimination modulation method as described above is implemented.

[0023] In a fourth aspect, the present invention provides a computer program product, comprising a computer program, wherein when the computer program is executed on one or more processors, the computer program is used to implement the multi-level converter specific harmonic elimination modulation method as described above.

[0024] In a fifth aspect, the present invention provides an electronic device, comprising: a processor, a memory and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory so that the electronic device executes instructions for implementing the multi-level converter specific harmonic elimination modulation method as described above.

[0025] Explanation of terms: specific harmonic elimination (SHE), pulse width modulation (PWM), online adaptive specific harmonic elimination modulation algorithm (OA-SHE), non-ideal DC source (NID), lead-lag shift (LLP), cascaded H-bridge multilevel converter (CHBC), fast Fourier transform (FFT), particle swarm optimization algorithm (PSO), field programmable gate array (FPGA), digital signal processor (DSP).

[0026] The beneficial effects of the present invention are as follows: error feedback of the output voltage is introduced before the switching angle is generated, and the compensation angle is optimized by a particle swarm algorithm to achieve real-time update of the switching angle following the error change, and the error caused by the non-uniform DC source and the offset of the switching angle is compensated online and adaptively, which can reduce the low-order harmonic content and improve the output waveform accuracy of the modular multi-level converter; there is no need to obtain the precise model parameters of the converter in advance, and there is no need to adjust the control parameters to apply to different converter models; an online adaptive modular multi-level converter specific harmonic elimination modulation algorithm is implemented to meet actual industrial needs.

[0027] Additional advantages of the present invention will be more clearly given in the following description or learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0029] Figure 1 This is a structural diagram of a three-phase cascaded H-bridge multi-level converter according to an embodiment of the present invention.

[0030] Figure 2 This is a flow chart of a specific harmonic elimination modulation algorithm for a multi-level converter according to an embodiment of the present invention.

[0031] Figure 3 This is a functional principle block diagram of a multi-core embedded control system composed of FPGA and DSP according to an embodiment of the present invention.

[0032] Figure 4 This is a program design diagram for a multi-core embedded control system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below by the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0034] It should be understood by those skilled in the art that unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art to which this invention belongs.

[0035] It should also be understood that terms, such as those defined in commonly used dictionaries, should be understood to have a meaning consistent with that in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless as defined herein.

[0036] Those skilled in the art will appreciate that, unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements and / or groups thereof.

[0037] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0038] To facilitate understanding of the present invention, the present invention is further explained below with reference to specific embodiments in conjunction with the accompanying drawings, and the specific embodiments do not constitute a limitation on the embodiments of the present invention.

[0039] Those skilled in the art should understand that the drawings are merely schematic diagrams of embodiments, and the components in the drawings are not necessarily necessary for implementing the present invention.

[0040] Example 1

[0041] This embodiment 1 provides a multi-level converter specific harmonic elimination modulation system, including:

[0042] A collection module, used for collecting output phase voltages of modular multi-level converters;

[0043] A first calculation module is used to calculate an actual harmonic spectrum based on an output phase voltage of the modular multilevel converter;

[0044] A second calculation module is used to calculate a disturbance compensation angle by combining an actual harmonic spectrum and an error of a voltage vector generated based on a fundamental wave modulation ratio;

[0045] The third calculation module is used to add the calculated disturbance compensation angle to the corresponding switching angle under different fundamental modulation ratios calculated offline to obtain an actual switching angle for directly driving the modular multi-level converter.

[0046] like Figure 2 As shown, in the above system described in this embodiment 1, the output switch angle of the offline data module Calculated from the fundamental modulation ratio M1 and used to directly drive the converter. Total disturbances Superimposed on The actual switching angle α is generated i It should be pointed out that represents the combined effect of the NID source and the LLP. It is very variable for each converter and difficult to calculate in advance, so the total error Design the compensation object of the cost algorithm.

[0047] First, the fast Fourier transform (FFT) module (i.e., the first calculation module) calculates the output phase voltage v of the modular multilevel converter. ao Perform fast Fourier transform to obtain the actual harmonic spectrum; in the second calculation module, the voltage vector generated based on the fundamental modulation ratio M1 is used as a reference value Compare the FFT output with The error is sent to the multi-objective optimization (MOO) cost function and solved using the particle swarm optimization algorithm (PSO). When the convergence result of the PSO link is The disturbance can be almost compensated when Figure 2 Then find the switch angle in the table. Updated to alpha i .

[0048] In this embodiment 1, a multi-level converter specific harmonic elimination modulation method is implemented by using the above system, including:

[0049] Collect the output phase voltage of modular multilevel converter;

[0050] Calculate the actual harmonic spectrum based on the output phase voltage of the modular multilevel converter;

[0051] The disturbance compensation angle is calculated by combining the actual harmonic spectrum and the error of the voltage vector generated based on the fundamental wave modulation ratio;

[0052] The calculated disturbance compensation angle is added to the corresponding off-line calculated switching angle under different fundamental modulation ratios to obtain an actual switching angle for directly driving the modular multi-level converter.

[0053] The switch angles under different fundamental modulation ratios are obtained by offline calculation, including: using a radial basis neural network, a back propagation neural network or a classic lookup table to offline solve the solutions of the switch angles corresponding to different fundamental modulation ratios.

[0054] The output phase voltage of the modular multilevel converter is collected in real time and subjected to fast Fourier transform to obtain the actual harmonic spectrum.

[0055] The error between the actual harmonic spectrum and the reference value is fed into the multi-objective optimization cost function and solved using the particle swarm optimization algorithm. When the particle swarm optimization algorithm link converges, disturbance compensation is obtained.

[0056] Example 2

[0057] In this embodiment 2, an online adaptive modular multi-level converter specific harmonic elimination modulation algorithm is provided for example Figure 1 The three-phase cascaded H-bridge multilevel converter (CHBC) shown in FIG. 1 implements specific harmonic elimination (SHE) pulse width modulation in an online adaptive manner. The three-phase CHBC consists of 3N units; V dci is the DC side voltage of the i-th module, where i = 1, 2, 3, ..., N; v ai is the output voltage of the single H-bridge converter; v ao 、v bo and v co is the phase voltage. Taking single-phase as an example, the algorithm introduces the phase voltage v before the switching angle is generated. ao As error feedback, the output phase voltage error caused by the non-uniform DC source and the offset of the switching angle is compensated online and adaptively, which can reduce the low-order harmonic content and improve the output waveform accuracy of the modular multilevel converter.

[0058] like Figure 2 As shown, an online adaptive modular multilevel converter specific harmonic elimination modulation algorithm includes the following steps:

[0059] Step 1: Use radial basis function neural network to solve the switching angle corresponding to different fundamental modulation ratios M1 offline.

[0060] In step 1, offline calculations need to be performed in advance, but the calculation process can be greatly simplified and the accuracy requirements can be relaxed because the errors can be adaptively compensated by other loops of the present invention. Therefore, the cost of optimizing calculations and training a well-designed neural network is reduced.

[0061] In step 1, a radial basis neural network is used for offline calculation, as Figure 2As shown in the Offline Data module of , back-propagation neural network is also effective here, and the classic lookup table is another option.

[0062] Step 2: Real-time acquisition of the output phase voltage v of the modular multilevel converter ao , and perform fast Fourier transform to obtain the actual harmonic spectrum.

[0063] Step 3: Generate a voltage vector based on the fundamental modulation ratio M1 and use it as a reference value

[0064] Step 4: Compare the FFT output with The error is fed into the multi-objective optimization (MMO) cost function.

[0065] In step 4, different cost functions can be applied in the present invention according to different emphases.

[0066] Step 5: Use the particle swarm optimization algorithm to solve. When the convergence result of the PSO link is The disturbance can be almost compensated.

[0067] In step 5, in order to quickly solve the problem to meet the requirements of industrial applications, a particle swarm optimization algorithm is used, which is simple and has high search efficiency.

[0068] In step 5, the optimization goal is to maximize the cost function, and the optimization object is N compensation angles.

[0069] Step 6: Add the N compensation angles to the N switch angles corresponding to the offline calculation results to obtain N actual switch angles.

[0070] In step 6, the compensation angle is added to the switch angle to compensate Figure 2 The total error in The obtained N actual switching angles are used to directly drive the converter.

[0071] Step 7, repeat steps 2-6 online, add the compensation angle to the switch angle at the previous moment, and obtain the current switch angle.

[0072] In step 7, by repeating steps 2-6, the switch angle α in the lookup table is i * Updated to alpha i , to achieve online adaptive compensation of output waveform errors.

[0073] In summary, the multi-level converter specific harmonic elimination modulation method described in this embodiment 2 introduces error feedback of the output voltage before the switching angle is generated, and adopts the particle swarm algorithm to optimize the compensation angle, so as to realize the real-time calculation and update of the switching angle following the error change, so as to achieve the purpose of online adjustment of the switching angle, compensate the output waveform error, and improve the output waveform accuracy of the modular multi-level converter; by measuring the error in real time and calculating the corresponding compensation angle, the error can be adaptively eliminated without obtaining the precise model parameters of the converter in advance, and the control parameters can be applied to different converter models without adjusting them; based on the multi-core embedded control system composed of FPGA and DSP, an online adaptive modular multi-level converter specific harmonic elimination modulation algorithm is realized, which can meet the actual industrial needs.

[0074] Example 3

[0075] like Figure 3 As shown, in this embodiment 3, a multi-core embedded control system architecture is obtained by combining software and hardware. The multi-core embedded control system based on field programmable gate array (FPGA) and digital signal processor (DSP) can realize high-frequency control. The control system includes two FPGA chips, the main chip (Main FPGA) processes sampling and protection, and the slave chip (Slave FPGA) generates conversion pulses (GCP) through optical fiber; two floating-point DSP chips, the main processor (Main DSP) undertakes the main control functions, such as dq decoupling control and voltage balance control, and the slave processor (Slave DSP) calculates the switching angle based on the online adaptive modular multi-level converter specific harmonic elimination modulation (OA-SHE) algorithm.

[0076] The program design described in this embodiment is as follows Figure 4 As shown in the figure, DFT stands for Discrete Fourier Transform, PSO stands for Particle Swarm Optimization, ADC stands for Sampling Process, and GCP stands for Generating Transformation Pulses. Par is the abbreviation of "Particle" in PSO, and Tsam is the sampling period of ADC.

[0077] The program execution steps are:

[0078] 0: Enable interrupt from MFPGA and start interrupt counter num=0, iteration number ger=0.

[0079] 1: Initialize Ma, POP, DIM, GER, seed_a[POP][DIM], seed_b[POP][DIM], fx[POP], x_pop[POP][DIM], v_pop[POP][DIM], fx[POP][GER], xm[DIM].

[0080] 2: Randomly generate particle position x_pop[num][:] and particle velocity v_pop[num][:] based on seed_a[num][:] and seed_b[num][:].

[0081] 3: Execute {

[0082] (1): Generate the actual angle a=a*+x_pop[num][:] and send them to SFPGA.

[0083] (2): Update the random seeds seed_a[num][:] and seed_b[num][:].

[0084] (3): Read DFT results Vh from MFPGA, h = 0, 1, 5, 7, 11, 13.

[0085] (4): Calculate the cost function value fx[num].

[0086] (5): Set num = num + 1.}

[0087] 4: If num≤POP, go to step 3; otherwise set num=1 and go to step 5.

[0088] 5: If fx[:]>fxm[:], update the local optimal value of fxm[:]=fx[:].

[0089] 6: Set the optimal value of the overall population fym = Max(fxm[:]) and save the corresponding local position xm[:].

[0090] 7: Set ger=ger+1.

[0091] 8: Update x_pop[num][:] and v_pop[num][:] according to the iterative formula of the particle swarm algorithm.

[0092] 9: If ger≤GER, go to step 3; otherwise save the final switching angle a=a*+xm[dim] to MDSP and exit.

[0093] Among them, POP is the population size, DIM is the dimension of a single particle, GER is the maximum number of iterations, seed_a and seed_b are seed tables used to generate random numbers, fx is the cost function value of all particles, x_pop and v_pop are all local positions and velocities, and fxm is the maximum cost function value of all iterations of each local.

[0094] At the top level of the time series, an iterative process contains x basic cycles. Each basic cycle corresponds to the running time of a particle. In the second level time series, the sampling frequency of the control system is set to 24kHz, that is, 480 sampling points can be generated within a base frequency cycle of 20ms. In the third level time series, a sampling cycle includes 2 or 4 time slices, which are ADC, DFT, PSO and GCP. In the first Tsam of a basic cycle, 4 time slices are required, and in other time periods, only ADC and GCP are required. The ADC and DFT functions are executed in the slave FPGA to obtain good real-time performance.

[0095] Example 4

[0096] Embodiment 4 of the present invention provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, a multi-level converter specific harmonic elimination modulation method is implemented. The method includes:

[0097] Collect the output phase voltage of modular multilevel converter;

[0098] Calculate the actual harmonic spectrum based on the output phase voltage of the modular multilevel converter;

[0099] The disturbance compensation angle is calculated by combining the actual harmonic spectrum and the error of the voltage vector generated based on the fundamental wave modulation ratio;

[0100] The calculated disturbance compensation angle is added to the corresponding off-line calculated switching angle under different fundamental modulation ratios to obtain an actual switching angle for directly driving the modular multi-level converter.

[0101] Example 5

[0102] Embodiment 5 of the present invention provides a computer program (product), including a computer program, wherein when the computer program is executed on one or more processors, the computer program is used to implement a multi-level converter specific harmonic elimination modulation method, the method comprising:

[0103] Collect the output phase voltage of modular multilevel converter;

[0104] Calculate the actual harmonic spectrum based on the output phase voltage of the modular multilevel converter;

[0105] The disturbance compensation angle is calculated by combining the actual harmonic spectrum and the error of the voltage vector generated based on the fundamental wave modulation ratio;

[0106] The calculated disturbance compensation angle is added to the corresponding off-line calculated switching angle under different fundamental modulation ratios to obtain an actual switching angle for directly driving the modular multi-level converter.

[0107] Example 6

[0108] Embodiment 6 of the present invention provides an electronic device, including: a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory, so that the electronic device executes instructions for implementing a multi-level converter specific harmonic elimination modulation method, the method comprising:

[0109] Collect the output phase voltage of modular multilevel converter;

[0110] Calculate the actual harmonic spectrum based on the output phase voltage of the modular multilevel converter;

[0111] The disturbance compensation angle is calculated by combining the actual harmonic spectrum and the error of the voltage vector generated based on the fundamental wave modulation ratio;

[0112] The calculated disturbance compensation angle is added to the corresponding off-line calculated switching angle under different fundamental modulation ratios to obtain an actual switching angle for directly driving the modular multi-level converter.

[0113] In summary, the prior art uses an offline and pre-calculated method to address the error problems caused by non-ideal DC sources (NID) and lead-lag displacement (LLP), stores the calculated switch angle in a lookup table, and obtains an approximate solution through a linear interpolation method, but cannot perform online calculation and adjustment of the switch angle according to the error change. The multi-level converter specific harmonic elimination modulation method described in the embodiment of the present invention introduces error feedback of the output voltage before the switch angle is generated, and uses a particle swarm algorithm to optimize the compensation angle, so as to realize real-time calculation and update of the switch angle following the error change, so as to achieve the purpose of online adjustment of the switch angle, compensate for the output waveform error, and improve the output waveform accuracy of the modular multi-level converter.

[0114] Most of the existing technologies rely on converter model parameters for design, and since the NID and LLP errors cannot be calculated in advance, and the errors caused in different systems are different, the existing technologies cannot be applied to different converter models. The multi-level converter specific harmonic elimination modulation method described in the embodiment of the present invention can adaptively eliminate the error by measuring the error in real time and calculating the corresponding compensation angle, without the need to obtain the precise model parameters of the converter in advance, and can be applied to different converter models without adjusting the control parameters.

[0115] The existing technology mostly uses dSPACE control system as the algorithm execution platform, but the high-performance control system in the laboratory does not meet the low-cost requirements of actual industrial application scenarios. The multi-level converter specific harmonic elimination modulation method described in the embodiment of the present invention is based on a multi-core embedded control system composed of FPGA and DSP to realize an online adaptive modular multi-level converter specific harmonic elimination modulation algorithm, which can meet actual industrial needs.

[0116] Those skilled in the art will appreciate 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 code.

[0117] 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.

[0118] 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.

[0119] These computer program instructions can also be loaded onto a computer or other programmable data processing device, and a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0120] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative work on the basis of the technical solution disclosed in the present invention should be included in the scope of protection of the present invention.

Claims

1. A multilevel converter specific harmonic elimination modulation method for a single-phase cascaded H-bridge multilevel converter, It is characterized in that include: The switch angles under different fundamental modulation ratios obtained by offline calculation include: using a radial basis neural network, a back propagation neural network or a classic lookup table to offline solve the switch angles corresponding to different fundamental modulation ratios; Collect the output phase voltage of the modular multilevel converter and perform fast Fourier transform to obtain the actual harmonic spectrum; The error between the actual harmonic spectrum and the voltage vector generated based on the fundamental modulation ratio is fed into the multi-objective optimization cost function and solved using the particle swarm optimization algorithm. When the particle swarm optimization algorithm link converges, the disturbance compensation angle is obtained. The calculated disturbance compensation angle is added to the corresponding off-line calculated switching angle under different fundamental modulation ratios to obtain an actual switching angle for directly driving the modular multi-level converter.

2. A multi-level converter specific harmonic elimination modulation system, It is characterized in that include: An offline calculation module, used for offline calculation of the switch angles under different fundamental modulation ratios, including: using a radial basis neural network, a back propagation neural network or a classic lookup table to offline solve the switch angles corresponding to different fundamental modulation ratios; An acquisition module is used to acquire the output phase voltage of the modular multi-level converter and perform fast Fourier transform to obtain the actual harmonic spectrum; The first calculation module is used to input the actual harmonic spectrum and the error of the voltage vector generated based on the fundamental modulation ratio into the multi-objective optimization cost function, and solve it using the particle swarm optimization algorithm. When the particle swarm optimization algorithm link converges, the disturbance compensation angle is obtained; The second calculation module is used to add the calculated disturbance compensation angle to the corresponding off-line calculated switching angle under different fundamental modulation ratios to obtain an actual switching angle for directly driving the modular multi-level converter.

3. A non-transitory computer-readable storage medium, It is characterized in that The non-transitory computer-readable storage medium is used to store computer instructions, and when the computer instructions are executed by a processor, the multi-level converter specific harmonic elimination modulation method according to claim 1 is implemented.

4. A computer program product, It is characterized in that The invention comprises a computer program, which is used to implement the multi-level converter specific harmonic elimination modulation method as claimed in claim 1 when the computer program is run on one or more processors.

5. An electronic device, It is characterized in that include: A processor, a memory and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to execute instructions for implementing the multi-level converter specific harmonic elimination modulation method as claimed in claim 1.

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