Multilevel Converter Research Articles

Computationally efficient data‐driven model predictive control for modular multilevel converters

AbstractThe application of model predictive control (MPC) for the control of modular multilevel converters (MMCs) is widely explored because it offers flexibility in integrating multiobjective control and delivers superior dynamic response. Nonetheless, the increase in computational complexity due to the rise in the number of submodules (SMs) is one of the major drawbacks of this technique. This paper presents a finite control set model predictive control (FCS‐MPC) that significantly reduces the computational complexity by employing sparse identification of non‐linear systems (SINDy) to obtain a simplified linear model for the MMC. The SINDy model reduces the complexity of performing the prediction step by integrating input terms into the dynamics of load current and circulating current. This simplifies the implementation compared to the conventional FCS‐MPC approaches by eliminating the need to evaluate the voltage dynamics. The computational burden is further reduced while maintaining voltage levels at the output by restricting the number of combinations for the inserted SMs to only instead of . A detailed comparison between the proposed technique and the existing strategies demonstrates that the proposed technique offers a more computationally efficient solution for implementing FCS‐MPC on MMCs, while improving the circulating current suppression due to more accurate predictions. Simulation and experimental results are presented to validate the performance of the proposed approach.

A Multiscale Adaptive Fusion Network for Modular Multilevel Converter Fault Diagnosis

Modular Multilevel Converters (MMCs) play a crucial role in new energy grid connection and renewable energy conversion systems due to the significant merits of good modularity, flexible scalability, and lower operating loss. However, reliability is a significant challenge for MMCs, which consist of a large number of Insulated Gate Bipolar Transistors (IGBTs). Failures of the IGBTs in submodules (SMs) are a critical issue that affect the performance and operation of MMCs. The insufficient ability of convolutional neural networks to learn key fault features affects the accuracy of MMC fault diagnosis. To resolve this issue, this paper proposes a novel deep fault diagnosis framework named the Multiscale Adaptive Fusion Network (MSAFN) for MMC fault diagnosis. In the proposed MSAFN, the fault features of the raw current in an MMC are extracted by employing multiscale convolutional neural networks (CNNs) firstly, and then a channel attention mechanism is added to adaptively select the channel containing key features, so as to improve the fault diagnosis ability of the MMC in a noisy environment. Finally, the adaptive size of a one-dimensional CNN is adopted to adjust the weight of the feature channels of different scales, which are adaptively fused for fault diagnosis. Experimental validation is performed on two different MMC datasets. Experimental results confirm that the introduction of an attention mechanism of the multiscale feature adaptive fusion channel improves the recognition accuracy of the model by an average of 15.6%. Moreover, comparative experiments under different signal-to-noise ratios (SNRs) demonstrate that the MSAFN maintains accuracy levels above 96.7%, highlighting its excellent performance, particularly under noisy conditions.

Vector Reconfiguration on a Bidirectional Multilevel LCL-T Resonant Converter

With the development of distributed energy technology, the establishment of the energy internet has become a general trend, and relevant research about the core component, energy router, has also become a hotspot. Therefore, the bidirectional isolated DC–DC converter (BIDC) is widely used in AC–DC–AC energy router systems, because it can flexibly support the DC bus voltage ratio and achieve bidirectional power flow. This paper proposes a novel vector reconfiguration on a bidirectional multilevel LCL-T resonant converter in which an NPC (neutral-point clamped) multilevel structure with a flying capacitor is introduced to form a novel active bridge, and a coupling transformer is specially added into the active bridge to achieve multilevel voltage output under hybrid modulation. In addition, an LCL-T two-port vector analysis is adopted to elaborate bidirectional power flow which can generate some reactive power to realize zero-voltage switching (ZVS) on active bridges to improve the efficiency of the converter. Meanwhile, due to the symmetry of the LCL-T structure, the difficulty of the bidirectional operation analysis of the power flow is reduced. Finally, a simulation study is designed with a rated voltage of 200 V on front and rear input sources which has a rated power of 450 W with an operational efficiency of 93.8%. Then, the feasibility of the proposed converter is verified.

A decoupling strategy for average value control and ripple suppression of capacitor voltages in modular multilevel converters based on notch filters

AbstractModular multilevel converters (MMC) have become an emerging hotspot in the field of medium‐voltage drives. A major challenge is the large voltage ripple of sub‐module capacitors at low rotor speeds with high torque. Therefore, it is necessary to achieve ripple suppression while maintaining the average values of the capacitor voltages at their reference. However, the average value control and ripple suppression of the capacitor voltages have a coupling effect during the circulating current control loop, which reduces the performance. This paper proposes a decoupling strategy based on notch filters (NF). First, the coupling problem existing in the traditional control strategy is analysed by theoretical analysis and simulation. Then, the principle and parameter design method of the improved decoupling strategy are introduced. Finally, the performance of the decoupling strategy is experimentally verified using a small prototype.

Virtual Generator to Replace Backup Diesel GenSets Using Backstepping Controlled NPC Multilevel Converter in Islanded Microgrids with Renewable Energy Sources

This work presents an islanded microgrid energy system that uses backstepping control applied to neutral point clamped (NPC) multilevel converters coupled with batteries to behave as virtual generators, able to absorb surplus renewable energy, therefore increasing the penetration of renewable energy sources. Additionally, on a charged battery the virtual generator allows turning-off the backup diesel generator set (GenSet). Aside from improving energy efficiency, the battery-connected multilevel converter aims to regulate frequency, improves power quality, and keeps the microgrid operational in the event of a GenSet failure. The backstepping controlled NPC multilevel converter emulates a virtual generator injecting power to perform as the primary and secondary microgrid frequency controller. Additionally, AC voltage control is implemented, which enables running the islanded microgrid only with multilevel converters, supplied by the battery while integrating solar and wind energy sources. Energy demand and renewable energy forecasts are used to manage the battery state-of-charge. Simulation results, obtained from switched and phasor models show that energy storage and the backstepping frequency control enables the compensation of power fluctuations from renewable energy sources. Furthermore, in the event of the main GenSet failure, the controlled virtual generator keeps the microgrid running for a few minutes, until another GenSet is ready to supply the microgrid. Therefore, the microgrid integration of the battery-connected multilevel converter results in a significant boost in energy efficiency by allowing the disconnection of the backup GenSet.

An online open circuit faults diagnosis method for converter using the lightweight two-channel deep network

Online diagnostic technology is crucial for ensuring the reliable operation of power converters in industrial applications. However, quickly diagnosing the faults of a power converter using intelligent algorithms is challenging due to the redundancy and noise of the sensor measurement signal. Hence, this paper proposes a lightweight two-channel deep network (LTCDN) to overcome it and achieve rapid fault diagnosis. It consists of a quadratic mean preprocessing layer (QMPL), a two-channel convolutional layer (TCCL), and a bidirectional gated recurrent unit (BGRU). The QMPL is designed to achieve denoising and lightening of output currents. Then, the TCCL is proposed to extract edge features and internal key information for improving diagnostic accuracy. Finally, the BGRU classifier completes the online fault diagnosis with a fast detection speed and high precision. It is evaluated through experiments with real-time open circuit faults for multiple switches of a four-level active neutral point clamped (4L-ANPC) converter, demonstrating superior performance with a false diagnosis rate of less than 1% and a diagnosis time of under 8ms. The method combines a novel data preprocessing layer with an efficient neural network to provide an effective fault detection method for a 4L-ANPC converter, which not only has high accuracy but also has significant computational efficiency. Its scalability for more complex multilevel converters is also verified.

Modeling and Control of Dual Active Bridge‐Modular Multilevel Converter‐Based Solid State Transformer for Grid Integration of SPV and Battery Energy Storage

ABSTRACTThis article deals with the modeling and control of a solid‐state transformer (SST) based on a dual active bridge (DAB) and modular multilevel converter (MMC) for integrating solar photovoltaic (SPV) and battery energy storage (BES) systems into the grid. SST uses DABs for bidirectional DC‐DC conversion and an MMC for DC‐AC conversion. A hybrid control method is developed in this study, which combines proportional‐integral (PI) controllers and model predictive control (MPC) to achieve the multiple objectives of the SST. The DABs' control system uses PI controllers for power extraction from the SPV system and to regulate the charging and discharging of the BES according to power generation and demand fluctuations. MPC is applied to control the active power injection, regulate the DC‐link and sub‐module capacitor voltages of the MMC. Moreover, the developed hybrid control method ensures reliable SST performance even under adverse conditions like grid voltage distortion, unbalance, and frequency variations. An energy management strategy is developed based on total power generation, reference active power injection, and the state of charge of the BES. This strategy ensures accurate reference power injection to the grid despite dynamic changes in operating conditions. The article also presents a detailed mathematical model of the DAB and MMC components, and the stability of the control algorithm is analyzed theoretically. The effectiveness of the SST and the proposed hybrid control scheme is demonstrated through MATLAB/Simulink simulations and hardware‐in‐the‐loop experimental results under various operating conditions.

A Novel Capacitance Estimation Method of Modular Multilevel Converters for Motor Drives Using Recurrent Neural Networks with Long Short-Term Memory

Accurate estimation of submodule capacitance in modular multilevel converters (MMCs) is essential for optimal performance and reliability, particularly in motor drive applications such as permanent magnet synchronous motor (PMSM) drives. This paper presents a novel approach utilizing recurrent neural networks with long short-term memory (RNN–LSTM) to precisely estimate capacitance in MMC-based PMSM drives. By leveraging simulation data from MATLAB, the LSTM neural network is trained to predict capacitance based on voltage, current, and their temporal variations. The proposed LSTM architecture effectively captures the dynamic behavior of MMCs in PMSM drives, providing high-precision capacitance estimates. The results demonstrate significant improvements in estimation accuracy, validated through mean squared error (MSE) metrics and comparative analysis of actual versus estimated capacitance. The method’s robustness is further confirmed under varying operating conditions, highlighting its practical utility for real-time applications in power electronic systems.

A Review on Modular Multi-level Converter Based HVDC Systems

Modular Multilevel Converters (MMCs) have emerged as a promising technology for High Voltage Direct Current (HVDC) transmission systems, offering several advantages such as reduced harmonic distortion, high voltage capability and modularity. This paper presents a comprehensive review of MMC-based HVDC systems, focusing on their applications, control strategies and challenges. The paper begins by discussing the basic principles and structure of MMCs, highlighting their modular design and operation. The paper delves into the control strategies employed in MMC-HVDC systems, emphasizing the importance of coordinated control between the AC and DC sides to ensure stable and efficient operation. Furthermore, the paper addresses the challenges associated with MMC-HVDC systems, such as fault ride-through capability, harmonic interactions and grid integration. It highlights recent advancements in control techniques and technologies that are being developed to address these challenges. The paper provides a valuable overview of MMC-based HVDC systems, highlighting their potential benefits and the ongoing research efforts to overcome their challenges. As the demand for renewable energy sources and long-distance power transmission increases, MMC-HVDC systems are poised to play a crucial role in shaping the future of the power grid

A Novel Enhanced Fire Hawks Optimization Approach for Improving the Efficiency of Converter‐Based Controllers in Switched Reluctance Motors

ABSTRACTSwitched reluctance motors (SRMs) have gained popularity in various industrial applications due to their advantages, including structural simplicity, high reliability, low cost, and operational stability over a wide speed range without relying on rare‐earth permanent magnet materials. However, these motors exhibit drawbacks such as weak torque density, low efficiency, and significant torque ripple, particularly in high‐speed operation. An efficient converter‐based control approach is proposed to manage speed and torque variations in SRM motors, addressing these issues. A multilevel converter (MC) is introduced as a fundamental component. The novel multilevel converter (NMC) accommodates SRMs with varying numbers of phases and exhibits quick demagnetization and excitation behaviors, enabling independent operation of each phase even during conduction overlaps. Subsequently, an effective controller is developed for the SRM motor, combining proportional integral derivative (PID) control with enhanced fire hawks optimization (EFHO). The EFHO optimizes the PID gain values to enhance controller performance. The converter operation minimizes torque ripple and facilitates speed management. The EFHO technique is a fusion of fire hawks optimization (FHO) and the sine cosine algorithm (SCA). This amalgamation improves the updating process of FHO by incorporating SCA. The proposed methodology is implemented in MATLAB and evaluated through various metrics, including SRM motor current, voltage, speed, and torque, under electric vehicle (EV) load conditions. Performance comparisons are conducted with traditional optimization algorithms such as the whale optimization algorithm (WOA) and ant colony optimization (ACO). The results validate the effectiveness of the proposed methodology in achieving improved SRM motor control and performance.

Design and PIL Implementation of Fuzzy Logic-based MPPT Control for Symmetrical Multilevel Boost Converter

This paper aims to introduce a fuzzy logic adaptive MPPT controller to control a symmetrical multilevel converter in a standalone PV system. The system is evaluated under fixed and variable solar radiation with 15 V as the input voltage 60 V as the required output voltage and 50 kHz as the switching frequency. Results prove that by using the controller, the system successfully tracks the MPPT point for constant and variable radiation without oscillation around the maximum power point. In addition, the overshoot and time response is reduced while the voltage ripples are eliminated. The proposed controller is verified through practical implementation in Arduino mega board to test the accuracy of results. The practical finding via a processor in the loop test validates the simulation results.

A lightweight MMC topology with recombined half‐bridge submodules for DC fault ride‐through

AbstractThe lightweight of modular multilevel converter (MMC) and the DC faults ride‐through ability are main challenges for MMC‐high voltage direct current (HVDC) transmission systems. By introducing the concept of time‐division multiplexing, an arm multiplexing MMC (AM‐MMC) topology with high utilization of submodules is presented to reduce the weight and volume of MMC. In order to block the DC side fault current, this paper proposes a novel submodule in AM‐MMC, instead of using full‐bridge submodules. The proposed recombined half‐bridge submodules of AM‐MMC (RHAM‐MMC) contains four half‐bridge submodules and an IGBT with reverse parallel diodes. The topology and operating principle of RHAM‐MMC are introduced in detail. The time‐division multiplexing of middle arms between upper and lower arms is achieved by introducing arm selection switches. Thus, a new type of arm switch and switching method is designed based on the switch state. The DC faults ride‐through strategy is carried out based on its DC fault characteristic analysis. In addition, the economy analysis is conducted on the switching loss and operating loss of RHAM‐MMC. Compared with the fault ride‐through capability of other sub‐modules (SMs), RHAM‐MMC performs better in terms of investment cost and device losses. The simulation results based on MATLAB/Simulink reveal that RHAM‐MMC can achieve the DC side fault ride‐through and show effectiveness of the DC fault ride‐through control strategy.

Research on a New Topology and Reactive Power Compensation Application of Reinjection Multilevel Voltage Source Converter

Based on the principles of reinjection converter technology and submodule operation, a novel topology for a reinjection multilevel voltage source converter (RMVSC) is proposed. In this topology, submodules are dynamically connected in series as the reinjection circuit. This new topology retains all the functions of the RMVSC while offering flexible control of the reinjection circuit and ease of modularization, making it highly suitable for high-voltage, high-power applications. A circulating drive pulse sequence was developed for the 7-level serial submodule RMVSC, ensuring dynamic stability of the submodule voltage and maintaining low harmonic distortion when interfaced with the grid. Building on this, a double-loop control strategy—comprising an outer power loop and an inner current loop—was proposed for the static synchronous compensator (STATCOM) of RMVSC. A simulation model was constructed in PSCAD/EMTDC, and the simulation results confirm the excellent performance of the proposed topology and the effectiveness of both the modulation strategy and the double-loop control strategy. The RMVSC-STATCOM demonstrates continuous and bidirectional reactive power regulation, with high control accuracy and superior compensation current quality.

Thyristor Branch Loop-Based Hybrid Modular Multilevel Converters for DC Short-Circuit Faults

Thyristor Branch Loop-Based Hybrid Modular Multilevel Converters for DC Short-Circuit Faults

Research on Sub-Module Fluctuating Power Decoupling Strategy for Modular Multilevel Converter-Based Medium-Voltage Motor Drive System with Wide Speed Range

There is a problem of excessively large sub-module capacitance in modular multilevel converter (MMC) applications for medium-voltage motor drive systems, which is particularly noticeable during the low-speed operation of the motor. This paper proposes a low-capacitance MMC (LC-MMC) motor drive system based on lateral sub-module interconnection, achieving capacitance lightweighting across the wide speed range of the motor. The LC-MMC is based on the three-phase symmetrical fluctuating current input of the sub-modules in the interconnection channel, achieving their mutual cancellation, thus significantly reducing the sub-module capacitance size. This paper starts from the traditional MMC motor drive system and analyzes its specific requirements for sub-module capacitance. Then, it provides a detailed description of the LC-MMC scheme for achieving capacitance lightweighting across the wide speed range of the motor, and the two MMC motor drive systems are compared and evaluated. The evaluation results show that the volume of the LC-MMC is reduced by nearly 70% compared to a traditional MMC. Finally, the LC-MMC scheme is simulated and experimentally verified.

Comparative analysis of submodules and design of seventeen-level modular multilevel converter using a five-level submodule block

Abstract Multilevel inverters and various modulation techniques have been proven to be the best solutions to overcome all the limitations of conventional two- or three-level voltage source inverters. In recent years, among all topologies, modular multilevel converter (MMC) has advantages like low total harmonic distortion (THD), reduced filter requirement, fault-tolerant operation, scalability, modularity, transformerless operation, etc. The main application of MMC is found in high-voltage DC transmission (HVDC). This study describes and analyses the performance of two distinct MMC submodule (SM) topologies: the Half Bridge submodule (HBSM) and the Full Bridge submodule (FBSM). Switching pattern is simpler in HBSM topology but it has the disadvantage that it does not have DC fault current blocking capability. Whereas FBSM not only inherently can block the DC fault current but also has advantages like reduced volume of MMC and better performance. Further, having the capability to produce three voltage levels, it can be operated in boost mode. Also, by using a proper switching pattern, MMC can be designed to generate a various number of output levels by using the same five-level submodule block. Out of which 17 level MMC gives the best output. The MATLAB-Simulink model is used to simulate the circuit, and the findings are confirmed for a 17-level output voltage.

Design and Implementation of Modular Multi-Level Converter Based HVDC System for Grid Connection

This paper examines Modular Multilevel Converters (MMC) for harnessing power from offshore wind farms. MMCs use many simple Voltage Source Converter (VSC) submodules, enabling high-voltage and high-power applications. They offer faster response times and lower harmonic distortion than traditional two-level VSCs. The paper addresses modelling challenges due to numerous switching devices and discusses the development of Cascaded Two-Level (CTL) converters, which improve output voltage quality. Overall, the study highlights advancements in MMC technology that enhance HVDC transmission capabilities.

Advanced Venturini control for PMSM with modular multilevel matrix converter

This paper provides a comprehensive analysis of control strategies for modular multilevel matrix converters (MMMC) utilizing advanced second-order sliding mode control (ASOSMC) within the context of permanent magnet synchronous motor (PMSM) applications. The research introduces a novel control framework based on the Venturini method, which, when integrated with ASOSMC, achieves a unity input power factor while generating sinusoidal phase current waveforms with markedly reduced harmonic distortion. These advancements not only enhance overall system performance but also significantly improve power quality, addressing critical requirements in contemporary electrical engineering. Additionally, the study conducts a rigorous comparative analysis between classical Proportional Integral (PI) control and ASOSMC, elucidating the substantial limitations of PI control in nonlinear environments where dynamic adaptability is paramount. In contrast, ASOSMC demonstrates superior capability in managing disturbances and nonlinearities, thereby offering enhanced reliability and efficiency for MMMC systems. The findings illustrate that ASOSMC not only addresses the challenges posed by traditional control techniques but also contributes to the development of more robust control methodologies within power electronics. By establishing a clear superiority of ASOSMC over conventional methods, this research paves the way for future innovations in control strategies specifically tailored for high-performance applications that require resilience under varying operational conditions. Ultimately, this work underscores the necessity of integrating advanced control techniques to optimize the operational capabilities of modular multilevel converters, facilitating the creation of sophisticated solutions that meet the evolving demands of electrical systems and power quality enhancement in diverse applications. The implications of these findings are significant, offering foundational insights for both theoretical exploration and practical implementation in the field.

PV Based Single Stage Cascaded Seven Level Modular Multilevel Converter with ZSV Control for Grid Interfaced System

Objectives: Climatic perturbation and environmental factors affect solar power generation. When these solar panels are connected to the grid it causes power quality issues such as voltage harmonics, voltage distortion, etc. These problems are addressed in this paper using a distributed MPPT algorithm. Methods: Multilevel inverters have made remarkable contributions to renewable energy, high voltage, and other high-power applications. Hence, a single-stage Cascaded Seven-Level Modular Multilevel Converter (CSLMMC) is used to address the issues. Zero Sequence Voltage (ZSV) control is proposed for producing balanced power during varying irradiance conditions. The proposed method is simulated using MATLAB SIMULINK software. Partial shading is conquered by using distributed MPPT. Findings: The simulation of the proposed system is performed for a three-phase system. The three-phase Cascaded Modular Multilevel Converter is connected to the grid through two loads which are controlled by a Zero Sequence Voltage Controller. Power quality parameters such as current, harmonics, and power are analyzed for the proposed system. Novelty: THD analysis for a five-level cascaded H bridge converter and the proposed systems are compared and presented. Keywords: Photo voltaic, Cascaded seven-level modular multilevel converter, Zero sequence control, Maximum power point tracking, Voltage Source Converter

A voltage-balancing algorithm based on the gating signal rotation and Separated Circulating Current Controller applied on a Modular Multilevel Converter

The Modular Multilevel Converter (MMC) is being used for many medium/high-power energy conversion applications due to its superior advantages such as modularity, scalability, and low harmonic generation. However, the MMC control can be challenging. If the submodule (SM) capacitors are not properly balanced, a circulating current is induced due to the voltage mismatch between the capacitor submodules. This circulating current adds to the arm current, which increases its RMS and peak value, and thus increases system losses. Therefore, controlling the submodule capacitor voltage and the circulating current is an important step in any MMC control. In this paper, a Gating Pattern Rotation algorithm is used for SM capacitor voltage balancing, and an independent circulating current controller in the double reference frame is used to eliminate the circulating current. Furthermore, a voltage-oriented control is employed to eliminate harmonics and regulate the grid power factor. MATLAB Simulink simulates the control technique, and various simulation results are presented. With results showing their effectiveness in managing and improving MMC behavior.