Three-level Neutral Point Clamped Inverter Research Articles

Maximizing solar energy efficiency with efficient interleaved boost converter with Three-Level neutral point clamped inverter for Grid-Connected photovoltaic using hybrid approach

The efficient interleaved boost converter (IBC) combined with the 3-level neutral point clamped (NPC) inverter for grid-connected photovoltaic systems (GCPVS) maximizes solar energy efficiency are presented. The proposed hybrid technique implies the combination of Double Attention Convolutional Neural Network (DACNN) and Starling Murmuration Optimization (SMO) algorithm and is usually referred as DACNN-SMO technique. Enhancing power quality at the Point of Common Coupling (PCC) while utilizing the rated capacity of the inverter into consideration is the main goal of the proposed approach. The grid-connected photovoltaic system additionally includes an efficient three-level NPC inverter and interleaved boost converter to decrease DC link voltage oscillation. In addition to preventing overheating, the inverter current controls reactive power adjustment, active power injection, and current harmonic filtering. Utilizing the SMO technique, By employing the SMO technique, the system effectively regulates output voltage, ensuring that the inverter output voltage. The DACNN enhances the system’s ability to monitor and diagnose faults. Using MATLAB, the proposed topology is implemented, and the results are contrasted with those of other existing techniques. The existing methods such as Heap Based Optimizer (HBO), Circle Search Algorithm (CSA) and Sparrow Search Algorithm (SSA) attains a higher THD of 3.7%, 4.7% and 5.3% respectively. The proposed method DACNN-SMO attains a THD of 2.5%. The proposed technique displays the efficiency is 99.86%. When compared to existing strategies, the proposed technique displays lower THD and high efficiency.

CONTRÔLE DIRECT DU COUPLE AVEC MODULATION VECTORIELLE SPATIALE UTILISANT DES RÉGULATEURS À LOGIQUE FLUUSE DE TYPE 2 À INTERVALLE D'UNE MACHINE À INDUCTION À DOUBLE ÉTOILE ALIMENTÉE PAR DEUX ONDULEURS À POINT NEUTRE À TROIS NIVEAUX SERRÉS

This paper introduces a direct torque control (DTC) method with space vector modulation (SVM) using interval type-2 fuzzy logic regulators for a dual-star induction machine fed by two three-level neutral point clamped inverters. The conventional DTC drive utilizes a pair of hysteresis comparators, which can lead to issues such as high torque ripple and variable switching frequency. As a result, we introduce several alternative methods, including DTC-SVM. We replace the hysteresis comparators with two Proportional-Integral (PI) regulators to enhance DTC performance, which generates the direct and quadrature voltage components in the d-q frame. The intricacy of the control system can make adjusting the PI regulator parameters difficult. To address this challenge, we propose using an interval type-2 fuzzy logic regulator for PI parameter adjustment in this paper. Our simulation results demonstrate the robustness and efficiency of the IT2FLC regulator.

A reduced vector model predictive controller for a three-level neutral point clamped inverter with common-mode voltage suppression

This paper presents a novel, state-of-the-art predictive control architecture that addresses the computational complexity and limitations of conventional predictive control methodologies while enhancing the performance efficacy of predictive control techniques applied to three-level voltage source converters (NPC inverters). This framework's main goal is to decrease the number of filtered voltage lifespan vectors in each sector, which will increase the overall efficiency of the control system and allow for common mode voltage reduction in three-level voltage source converters. Two particular tactics are described in order to accomplish this. First, a statistical approach is presented for the proactive detection of potential voltage vectors, with an emphasis on selecting and including the vectors that are most frequently used. This method lowers the computational load by limiting the search space needed to find the best voltage vectors. Then, using statistical analysis, a plan is presented to split the sectors into two separate parts, so greatly limiting the number of voltage vectors. The goal of this improved predictive control methodology is to reduce computing demands and mitigate common mode voltage. The suggested strategy's resilience is confirmed in a range of operational scenarios using simulations and empirical evaluation. The findings indicate a pronounced enhancement in computational efficiency and a notable diminution in common mode voltage, thereby underscoring the efficacy of the proposed methodology. This increases their ability to incorporate renewable energy sources into the electrical grid.

Nonlinear control of three level NPC inverter used in PV/grid system: comparison of topologies and control methods

With the passage of time, the importance of using renewable energy systems to overcome energy consumption and improve the quality of the grid has emerged through the use of nonlinear control techniques and reliance on advanced types of inverters such as multi-level inverters. This research is focused on comparing two grid-connected converter topologies in a photovoltaic (PV) generation system connected to a three-phase grid that serves a non-linear load. Additionally, the study explores two different control techniques applied to this converter, evaluating their effects on the total harmonic distortion coefficient. A comparison has been made between the traditional inverter and the three-level inverter type neutral point clamped (NPC) inverter, with the use of integral backstepping (IBS) technique which was also compared with the proportional integral (PI) controller. The simulation results in MATLAB/Simulink are presented illustrating the performances and the strong effectiveness of the three-level NPC inverter controlled by the proposed technique (IBS).

Switch fault identification scheme based on machine learning algorithms for PV-Fed three-phase neutral point clamped inverter

Any faults in power electronic switches must be detected and located promptly to certify the unchanging operation and reliability of multilevel inverter (MLI) systems. Machine learning (ML) techniques are increasingly being utilized to diagnose faults in MLIs due to their advantages, such as high precision, less calculation time, and reduced complexity. A faulty switch identification and phase identification method based on different ML classifiers is presented in this paper, explicitly targeting open-circuit faults in switches in a PV-fed 3-phase three-level Neutral Point Clamped (NPC) inverter. The NPC MLI output voltage and current signals are input signals to classify faults. The information or essential feature from the raw voltage and current data is extracted using a recursive discrete Fourier (RDF) followed by a discrete wavelet transform (DWT). Finally, the standard deviations of the approximate and detailed coefficients are used as input for ML algorithms. To do the comparative analysis, a variety of ML techniques are then applied to these features, including logistic regression (LR), random forest (RF), quadratic discriminate analysis (QDA), K-nearest neighbour (K-NN), and support vector machines (SVM). The experiment results indicate that the RF algorithms achieve the highest classification accuracy of 99.59 % for various switch fault conditions.

A Hybrid PWM Strategy for Switching Loss Reduction in Three-Level Inverters

The advanced bus-clamping PWM (ABCPWM) sequences are well known to reduce line current THD in a three-level neutral point-clamped inverter. This paper deals with ABCPWM sequences employed optimally to achieve minimum switching loss throughout the linear operating region in a three-level inverter. The work extensively analyzes the performance of these sequences in terms of inverter switching loss and compares them with centered space vector modulation PWM (CSVPWM). Based on the analysis, a hybrid PWM scheme termed as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">switching loss reduction</i> is proposed by optimally employing ABCPWM sequences in conjunction with variation in power factors. At a given average switching frequency, the proposed hybrid scheme reduces inverter switching loss compared to CSVPWM and the recently proposed discontinuous PWM-based optimization strategy at all power factors and modulation indices. With this scheme, switching loss reduces to 22% to 36% compared to CSVPWM and a maximum of 12% reduction than the existing optimization strategy. Furthermore, the scheme gives lower harmonic distortion compared to these two existing PWM schemes near high modulation indices and near unity power factor load. The theoretical, simulated, and real-time simulation results are presented with experimental results using TMS320F28335 DSP controller for validating the proposed work.

An Algorithm for a Space-Vector Pulse Width Modulation with a Hybrid Switching Sequence for a Three-Level Neutral Point Clamped Voltage Source Inverter

This paper proposes a new algorithm for a space-vector pulse width modulation (SVPWM) with a hybrid switching sequence (SS) designed to control a three-level (3L) neutral point clamped (NPC) voltage source inverter (VSI). Based on the advantages of five-stage and seven-stage SS, we designed a hybrid SS to improve four key parameters in the system: inverter output current quality, neutral point (NP) and common-mode (CM) voltage levels, and switching losses of power switches. The proposed algorithm flexibly regulates meeting the four criteria depending on the system operating conditions by changing the regulation coefficient. The paper obtained an approximate dependence to determine the optimal regulation coefficient for any values of the inverter modulation coefficient when operating jointly with an active-inductive load. The effectiveness of the proposed algorithm is confirmed by computer simulation in the MatLab+Simulink environment, as well as the results of experimental studies. The paper presents the experimental dependences of static state spaces, including the distortion coefficient of higher current harmonics at the inverter output, the maximum error of the NP voltage, the number of switching pairs of power switches, and the pulse duty factor of CM voltage, depending on the inverter modulation coefficient and the regulation coefficient of the hybrid SS. The results showed that in the algorithm for a SVPWM with a hybrid SS, the number of switchings of power switches is reduced by an average of 13.5 % while maintaining the NP voltage balance and the quality of the curve at the inverter output at an acceptable level, close to a seven-stage SS (the deviations do not exceed 0.5 % and 0.2 %, respectively). The average CM voltage coefficient decreased by no more than 4.5 %. The indicators improve the energy saving, the weight-size parameters, and the operational reliability of the 3L NPC VSI. The application area of the algorithm is much wider and includes the control of power switches of active front ends, grid converters for electricity storage systems, active power filters, and power conditioners. DOI: https://doi.org/10.52783/pst.237

Model Predictive Control Strategy Based on Loss Equalization for Three-Level ANPC Inverters

Targeting the issue of high losses of individual switching tubes in Neutral-Point Clamped (NPC) three-level inverters, an Active Neutral-Point Clamped (ANPC) three-level inverter is used, and a model predictive control strategy using the loss equalization of the inverter is proposed. This method organizes and analyzes multiple zero-state current pathway commutation modes and adds mode three under the original two commonly used zero-state commutation modes. On this basis, the three modes are flexibly switched by model predictive control, and the output is optimized according to the value function for the space vector in each operation, while the midpoint voltage control is added to the value function. The simulation results suggest that the recommended strategy in this study may effectively realize the loss equalization control and midpoint voltage control of the ANPC inverter, which improves the operation efficiency of the electromechanical actuator.

An Open-Circuit Fault Diagnosis Method for Three-Level Neutral Point Clamped Inverters Based on Multi-Scale Shuffled Convolutional Neural Network.

This study constructs a power switching device open-circuit fault diagnosis model for a three-level neutral point clamped inverter based on the multi-scale shuffled convolutional neural network (MSSCNN) and extracts and classifies the fault information contained in the output current of inverters. The model employs depthwise separable convolution and channel shuffle techniques to improve diagnostic accuracy and reduce model complexity. The experimental results show that the new model has lower model complexity, better noise resistance and higher average diagnostic accuracy compared with fault diagnosis models based on CNN, ResNet, ShuffleNet V2 and Mobilenet V3 networks.

Improved virtual space vector modulation for neutral point voltage oscillation and common-mode voltage reduction in neutral point clamped three-level inverter

Improved virtual space vector modulation for neutral point voltage oscillation and common-mode voltage reduction in neutral point clamped three-level inverter

Sensorless integral backstepping control of a single-stage photovoltaic system connected to the single-phase grid using a multi-level NPC inverter with an LCL filter

In this paper, the control problem of a single-phase, grid-tied photovoltaic (PV) system consisting of a three-level neutral point clamped (3L-NPC) inverter and an LCL filter is considered. The proposed controller aims at achieving threefold control objectives: (i) guaranteeing the PF correction (PFC) objective by enforcing the current of the grid to track a sinusoidal reference signal in phase with the grid voltage; (ii) controlling the DC bus capacitor voltages to follow a reference value provided by the maximum power point tracking (MPPT) algorithm to achieve the maximum available PV power; (iii) ensuring a balanced power exchange through the regulation of the two input capacitor voltages to the same values. To achieve these aims, a multi-loop nonlinear controller is synthesized, including three control loops, specifically the inner PFC requirement loop designed through the integral backstepping approach, the outer voltage control loop formulated using a filtered proportional integral (PI) regulator, and the power balance loop built up using a PI regulator. The control problem under consideration entails several difficulties as the existence of numerous state variables that are inaccessible to measurements. This challenge is addressed by adding a high-gain observer to estimate the current of the solar panels. The performance of the proposed controller against climate changes is demonstrated via numerical simulations using the MATLAB/Simulink platform.

Design of 3-Level T-type NPC Inverter for EV Applications

In recent years, there has been a significant demand for lightweight converters that provide exceptional control performance while generating minimal acoustic noise. This has resulted in higher switching signals for hard- switched 2-level low voltage 3-phase inverters. However, the increased switching frequencies have a negative impact on the inverters’ efficiency, requiring the use of expensive switch technology to maintain high efficiency. This paper aims to tackle these challenges by introducing the design and implementation of a extremely effective 3-Level T-Type Neutral Point Clamped (NPC) inverter designed for Electric Vehicle (EV) applications. 3-Level T-Type NPC inverter associates the strengths of both NPC and T-Type inverters. Similar towards the NPC, it offers a lower breakdown voltage for the switching devices, thereby reducing switching losses. Additionally, it shares the characteristics of the T-Type inverter, resulting in fewer conduction losses. To validate the feasibility of the converter, simulation is performed using MATLAB software, followed by the development and testing of a lab-scale prototype. The proposed three-level T-type NPC inverter have several merits over traditional 2-level inverters, including reduced distortion, switching losses, and improved efficiency. These benefits contribute to enhanced motor drive performance, reduced electromagnetic interference (EMI), and extended battery life in EVs.

Torque Increase Strategy for Induction Motor in the Field-Weakening Region Based on Model Predictive Control

In the field-weakening region, the traditional field-weakening method for induction motor drives based on model predictive control (MPC) is to take a no-load operation as the premise and adjust the flux reference in the cost function proportional to the inverse of the rotor speed, which leads to poor torque output. This paper presents a novel field-weakening method for IM drives based on MPC. Considering the induction motor field-weakening limiting conditions and according to the speed adaptive field-weakening strategy with a voltage closed-loop, the speed adaptive field-weakening controllers were designed to optimize the references of the excitation current and torque current. In the rotor field-orientation d–q coordinate system, the stator flux amplitude and torque reference values were optimized by the optimal distribution current. Then, according to the dead-beat control principle, they were converted into an equivalent stator flux vector reference. Moreover, the stator voltage vector reference can be obtained. For an induction motor fed by a three-level neutral point clamped (3L-NPC) inverter, the cost function was constructed by combining all the constraints, including the voltage vector, the neutral potential balance, and the switching frequency. In this way, the high-performance field-weakening operation for the induction motor based on a model predictive control can be realized. The simulation and experiment results show that the proposed method can increase the torque output by 22% in the field-weakening region; at the same time, the steady characteristics and the dynamic response performance can be maintained well.

Influence of switching sequences on the neutral point voltage balance in a three-level voltage source invertor

BACKGROUND:Ensuring the voltage balance of the neutral point of the DC link within acceptable limits is one of the mandatory requirements during the operation of a three-level autonomous neutral point clamped voltage source inverter. It is known that neutral point voltage imbalance can adversely affect the operation of the inverter and the load at all, lead to the failure of both power switches and capacitors in the DC link. Neutral point voltage imbalance mostly often occurs due to the asymmetry of the nominal values of DC capacitors, inconsistent properties of switching devices, asymmetric three-phase load, and also due to the imperfection of the converter control algorithm.&#x0D; AIMS:Selection of the optimal switching sequence that ensures the smallest deviation of the neutral point voltage and the number of switching of power switches in a three-level voltage source inverter.&#x0D; METHODS:For an objective comparison of the considered switching sequences and their influence on the neutral point voltage balance, a simulation model of a three-level neutral point clamped voltage source inverter was developed in theMATLAB/Simulinksoftware. To control this inverter, a space vector modulation method was used with three different switching sequences: five-segment, seven-segment and standard.&#x0D; RESULTS:The topology of a three-level neutral point clamped voltage source inverter is presented. The experimental dependencies of the neutral point voltage deviation error was taken with a change in the modulation coefficient, the frequency of the fundamental harmonic at the inverter output, and load characteristics for three different switching sequences.&#x0D; CONCLUSIONS:In this paper, the influence of the basic vectors and the influence of switching sequences on the neutral point voltage balance are studied. Combinations of states of large and zero basic vectors do not affect the neutral point voltage. For the medium basic vectors, the neutral point voltage can increase or decrease depending on the operating conditions of the inverter. The small basic vectors significantly affect the neutral point voltage. Considering the abovementioned, the seven-segment sequence that ensures both the optimal balance of the neutral point voltage and the level of switching losses should be considered as the best switching sequence for a three-level inverter.

Grid-Connected Solar PV System with Maximum Power Point Tracking and Battery Energy Storage Integrated with Sophisticated Three-Level NPC Inverter

In this research, a solar photovoltaic system with maximum power point tracking (MPPT) and battery storage is integrated into a grid-connected system using an improved three-level neutral-point-clamped (NPC) inverter. An NPC inverter with adjustable neutral-point clamping may achieve this result. To achieve this result, a modernized NPC inverter is used. Using the three-level vector modulation approach, the correct AC voltage may be generated when DC voltage conditions are present in an unbalanced situation involving an NPC inverter. A higher degree of precision is made possible by this. In-depth information on the many possible NPC inverter designs and modulation strategies was provided. By incorporating the necessary sophisticated algorithms into the NPC inverter, the necessary solar PV-MPPT functionality is made available, allowing for the regulation of power transfer among the solar PV system, the battery, and the grid. Modified INC method is proposed which has a tracking efficiency of 99.5% for varying irradiance. The use of sufficiently sophisticated algorithms makes this a reality. Using simulation with MATLAB/Simulink, we were able to examine an NPC inverter’s performance in several setups. Several amounts of solar irradiation were used to test the battery’s charging and discharging capabilities. The probe turned out to be fruitful. Laboratory testing ensures that the proposed method works by simulating real-world conditions.

Duty-Cycle Correction-Based Model Predictive Current Control for PMSM Drives Fed by a Three-Level Inverter With Low Switching Frequency

In this paper, a duty-cycle correction-based model predictive current control (DC-MPCC) is proposed for permanent magnet synchronous motor (PMSM) supplied by a neutral-point clamped three-level voltage source inverter (NPC-3LVSI). Unlike the conventional MPCC, which evaluates the impact of basic voltage vectors on the concerned state variables, the proposed DC-MPCC modifies the output voltage levels with optimized duty-cycle corrections. Firstly, the last three-phase voltage levels are assumed to be kept during the next control period. Then, the current tracking error and neutral-point potential are predicted. After that, the voltage levels are modified with zero, one, or two state changes, which formulate seven candidate solutions. Subsequently, the duty-cycle corrections of the modified voltage levels are computed based on the principle of minimizing current tracking error and neutral-point voltage drift. Finally, the optimal switch sequence is generated by evaluating and sorting a cost function with a penalty on switch actions. The proposed DC-MPCC features variable switching instants, relatively lower sampling frequency, and satisfactory performance under low switching frequency. Experimental tests carried out on a NPC-3LVSI fed PMSM drive, with 100 Hz fundamental frequency and 400 Hz switching frequency, accompanied by a video demonstration, validate the effectiveness of the proposed method.

Compensation-Voltage-Injection-Based Neutral-Point Voltage Fluctuation Suppression Method for NPC Converters

Three-level neutral-point clamped (NPC) inverters are widely used in the new energy power generation, motor drive, and many other occasions. However, the neutral-point voltage imbalance of an NPC inverter will affect the output of the inverter system, and the control of the neutral point voltage has become a popular research topic. In this paper, a compensation-voltage-injection-based neutral-point voltage balancing method is proposed. During the switching cycle, the average value model of the neutral-point current under different voltage vectors is applied to calculate the value of the compensation voltage that needs to be injected. The self-balance of the neutral-point voltage based on a switching cycle is realized, and the influence of modulation ratio and power factor on equalization ability is discussed. A MATLAB/Simulink simulation model and a small power prototype are established to verify the effectiveness of the method, and the simulation and experimental results show that the proposed method can effectively suppress the neutral-point voltage fluctuation in a wide range of modulation ratios and power factors.

Analysis and Reduction of Current and Voltage Ripple in DC Link for Three-Level NPC Inverter-Fed Dual Three-Phase Motor Drives

In this article, switching strategies for dc-link current and voltage ripple reduction have been studied. The considered topology is a neutral-point clamped three-level (NPC-3L) inverter feeding a dual three-phase permanent-magnet synchronous motor (PMSM). The mechanisms of dc-link current and voltage ripple generation in an NPC-3L inverter-fed PMSM drive are analyzed in detail. Then, a two-step collaborative switching strategy is proposed, where the optimum switching sequences, including opposite small vectors, are applied in the two inverters collaboratively. Furthermore, the switching vectors of two inverters are rearranged in the sequence of their corresponding dc-link capacitor currents so that the overlapping of their peaks is avoided. Consequently, both the voltage ripple and current ripple in the dc-link capacitors are mitigated with the proposed two-step collaborative switching strategy. For the midpoint voltage of the NPC-3L inverter, the amplitude of fluctuation is reduced under low modulation index operation, while the high-frequency harmonic components are mitigated under high modulation index operation. The experimental results are given to verify the validity of the theoretical analysis and the proposed switching strategy.

Multi-objective predictive control for three-phase three-level neutral-point clamped inverter

Multi-objective predictive control for three-phase three-level neutral-point clamped inverter

Long-Horizon Robust Direct Model Predictive Control for Medium-Voltage Induction Motor Drives With Reduced Computational Complexity

This paper proposes a long-horizon direct model predictive control (MPC) with reference tracking for medium-voltage (MV) drives that achieves favorable steady-state and transient behavior. However, as MPC is a model-based method, it is susceptible to parameter mismatches and variations of the machine. Moreover, even though a long prediction horizon significantly improves the steady-state behavior of the drive, it significantly increases the computational complexity of the direct MPC problem, rendering its real-time implementation a challenging—if not impossible—task. Motivated by these shortcomings of long-horizon direct MPC, this paper also aims to address them by enhancing the robustness of the developed control strategy, while keeping its computational complexity modest. To achieve the former, a prediction model suitable for MV drive systems is adopted that facilitates the effective estimation of the total leakage inductance of the machine. For the latter, the objective function of the MPC problem is formulated such that, even though the drive behavior is computed over a long prediction interval, only a few changes in the candidate switch positions are considered. The effectiveness of the proposed modeling, control, and estimation approaches is validated with hardware-in-the-loop (HIL) tests for an MV drive consisting of a three-level neutral point clamped (NPC) inverter and an induction machine (IM).