Power-Compensated Triple-Vector Model Predictive Direct Power Control Strategy for Nonredundant Fault-Tolerant Rectifiers

Model predictive direct power control (MPDPC) has been widely studied for the control of doubly fed induction generator (DFIG) systems because of its conceptual simplicity and multivariable control ability. However, conventional MPDPC suffers from the problems of high power ripples and intensive computational effort. Furthermore, this approach presents highly distorted currents under unbalanced networks. To address the problems mentioned above, this article proposes a universal and low-complexity MPDPC, which can work effectively under both balanced and unbalanced networks. On one hand, the proposed method unifies conventional MPDPC and multiple-vector-based MPDPC under a common framework with lower complexity. The optimal vectors and their respective durations in the proposed MPDPC are obtained in a substantially more efficient manner than conventional enumeration-based MPDPC. On the other hand, a flexible power control method with a universal power compensation expression is proposed. By adding the calculated power compensation value to the prior power reference value, the proposed universal MPDPC method can be applied to unbalanced networks. Three control objects under unbalanced network conditions can be realized. Current distortion and power ripple can vary smoothly among the three objects by regulating the coefficient determining the universal power compensation value. The presented experimental results confirm the effectiveness of the proposed method.

Conventional finite control set model predictive direct power control for grid-connected inverter causes high current harmonics and power fluctuations, during per control cycle, only one voltage vector is used. To address this issue, this paper introduces a hybrid vector model predictive direct power control (HV-MPDPC) strategy. A power prediction model is established in accordance with the instantaneous power theory. Then, eighteen alternative hybrid voltage vector combinations are formed by integrating double-vector and triple-vector combinations. Through cost function-driven selection of the optimal voltage vector combination, the power control performance and power quality are enhanced. The proposed strategy's effectiveness is validated by simulation results.

Model predictive direct power control for modular multilevel converter under unbalanced conditions with power compensation and circulating current reduction

This paper proposes a self-tuning model predictive direct power control (MPDPC) strategy for power flow control and power quality improvement in grid-connected power converters. At each sampling instant, a fuzzy logic controller is used to determine online the best weighting factor values for a given operating point. These values are then used to solve the multi-objective optimal control problem associated to the MPDPC. The optimal solution that minimizes the multi-objective cost function is chosen as the input (power switch state). The proposed method is examined through a case study and verified numerically via MAT LAB SIMULINK. A comparative study is conducted to demonstrate the effective performance of this approach. As a result of the proposed weighting factor online tuning, an improved performance in terms of total harmonic distortion and average switching frequency is attained when compared with fixed weighting factors.

The research object of this paper is single-phase PWM rectifier, the purpose is to reduce the total harmonic distortion (THD) of the grid-side current. A model predictive current control (MPCC) with fixed switching frequency and dead-time compensation is proposed. First, a combination of an effective vector and two zero vectors is used to fix the switching frequency, and a current prediction equation based on the effective vector’s optimal action time is derived. The optimal action time is resolved from the cost function. Furthermore, in order to perfect the established prediction model and suppress the current waveform distortion as a consequence of the dead-time effect, the dead-time’s influence on the switching vector’s action time is analyzed, and the current prediction equation is revised. According to the experimental results, the conclusion is that, firstly, compared with finite-control-set model predictive control, proportional-integral-based instantaneous current control (PI-ICC) scheme and model predictive direct power control (MP-DPC), the proposed MPCC has the lowest current THD. In addition, the proposed MPCC has a shorter execution time than MP-DPC and has fewer adjusted parameters than PI-ICC. In addition, the dead-time compensation scheme successfully suppresses the zero-current clamping effects, and reduce the current THD.

Despite distinctive advantages such as fast dynamic, simple concept and ease of implementation, model predictive direct power control (MPDPC) suffers from some major drawbacks. First, in order to provide sinusoidal currents and low-ripple powers, very high sampling rates are required for MPDPC implementation. Furthermore, this method requires accurate knowledge of system parameters and its performance deteriorates in presence of parameter uncertainties. In this paper, an improved MPDPC is proposed, which features: 1) high current and power quality at low sampling frequencies, 2) less sensitivity to parameter uncertainties, particularly unknown grid inductance, and 3) voltage sensorless operation. The first and second features are achieved by incorporating the concept of switching duty cycles into the conventional MPDPC. In the proposed method, two voltage vectors are applied during a control period and their duty cycles are obtained by a fuzzy logic modulator. The proposed fuzzy logic modulator works based on the real and reactive power errors. Eventually, voltage sensorless operation is accomplished by designing a full-order observer. Thanks to voltage sensorless operation, the system volume and cost can be reduced. Through extensive hardware-in-the-loop tests, the superiority of the proposed MPDPC in comparison with two conventional MPDPCs is demonstrated.

A novel power and rate control system model for wireless communication networks is presented, which includes uncertainties, input constraints, and time-varying delays in both state and control input. A robust delay-dependent model predictive power and rate control method is proposed, and the state feedback control law is obtained by solving an optimization problem that is derived by using linear matrix inequality (LMI) techniques. Simulation results are given to illustrate the effectiveness of the proposed method.

For the power control problem of a bidirectional voltage-source converter, because only one voltage vector is applied at each control period, the traditional model predictive direct power control strategy brings in high harmonic content. In this paper, a hybrid vector-modulation model predictive direct power control scheme is developed to address the high harmonic distortion issue under unbalanced grid conditions. Based on the instantaneous power theory, the expression for the power fluctuation is derived under unbalanced grid voltages. The new reference power under unbalanced grid voltages is represented by the α β components of the grid voltages and their orthogonal signals lagging by 9 0 ∘ . By means of the proposed strategy, neither the phase-locked loops nor the sequence extraction of the grid voltages are required. In addition, the optimal voltage vector is selected from eighteen alternative hybrid voltage vectors to further improve control performance. The effectiveness of the proposed strategy is verified through real-time simulations conducted on an RT-LAB hardware-in-the-loop platform.

This paper presents a novel Model Predictive Direct Power Control (MPDPC) approach for the pulse width modulation (PWM) rectifiers in the Aircraft Alternating Current Variable Frequency (ACVF) power system. The control performance of rectifiers may be largely affected by variations in the AC side impedance, especially for systems with limited power volume system. A novel idea for estimating the impedance variation based on the Bayesian estimation, using an algorithm embedded in MPDPC is presented in this paper. The input filter inductance and its equivalent series resistance (ESR) of PWM rectifiers are estimated in this algorithm by measuring the input current and input voltage in each cycle with the probability Bayesian estimation theory. This novel estimation method can overcome the shortcomings of traditional data based estimation methods such as least square estimation (LSE), which achieves poor estimation results with the small samples data set. In ACVF systems, the effect on the parameters estimation accuracy caused by the number of sampling points in one cycle is also analyzed in detail by simulation. The validity of this method is verified by the digital and Hard-in-loop simulation compared with other estimation methods such as the least square estimation method. The experimental testing results show that the proposed estimation algorithm can improve the robustness and the control performance of the MPDPC under the condition of the uncertainty of the AC side parameters of the three-phase PWM rectifiers in aircraft electrical power system.

Model predictive direct power control (MPDPC) is a suitable method for the highly nonlinear system of a three‐level Vienna rectifier. However, the traditional MPDPC suffers from irregular switching states, which can decrease current tracking accuracy and generate high current ripple and electromagnetic noise. Additionally, the use of sensors can increase system hardware costs and complexity. To enhance operational reliability and reduce the fault impact of AC voltage sensors, a double closed‐loop control strategy based on voltage‐sensorless MPDPC in the inner loop and sliding mode control (SMC) in the outer loop is proposed. First, the virtual flux model of the three‐phase Vienna rectifier is established in the two‐phase static coordinate system, and the second‐order low‐pass filter is used to improve the voltage observer to estimate the grid‐voltage. Meanwhile, an improved grid voltage observer based on the second‐order low‐pass filter is designed to improve the observation effect. Second, to solve the variable switching operation, current fluctuation and wide harmonic spectrum caused by the traditional MPDPC effectively, a double closed‐loop control strategy with constant switching frequency based on voltage‐sensorless MPDPC in the inner loop and SMC control in the outer loop is proposed. Based on the principle of SVPWM modulation, the modulation voltage of SVPWM is calculated directly, in order to verify the correctness of the theoretical analysis, extensive simulation and matching experimental is presented to verify the correctness of the theoretical analysis. © 2023 The Authors. IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

An improved model predictive direct power control (MPDPC) for three-phase grid-connected converters is proposed. In the proposed method, two voltage vectors are applied during a control period and their duty cycles are determined by a fuzzy logic-based modulator. The inputs to the modulator are the active and reactive power errors and the output is the duty cycle of the first (main) voltage vector. The fuzzy rules are developed based on expert knowledge and the fact that small/large power errors can be compensated by applying the main voltage vector for a small/large portion of the switching period. The candidate voltage vector pairs are examined on a control Lyapunov function and the pair that satisfy the closed-loop stability criteria are selected. The voltage vector pairs are then applied following a proposed switching pattern through which reduced average switching frequency is achieved. Comparative simulation and hardware-in-the-loop studies between the proposed method and a most recently introduced duty cycle-based MPDPC confirm that in addition to lower average switching frequency, better quality currents and active and reactive powers can be achieved under the proposed MPDPC.

With the increasing demand for power quality and system efficiency, traditional control strategies have gradually become unable to meet complex application requirements. Traditional control strategies often rely on fixed control algorithms, which may lead to decreased or even unstable system performance under dynamic conditions such as load changes, uncertain system parameters, or external disturbances. Taking the model of a three-phase PWM rectifier as an example, by optimizing the switching sequence, the problems of uneven distribution of the grid side current spectrum and system computational complexity can be solved. Furthermore, the control strategy was validated through simulation experiments. By comparing the results of optimized and unoptimized control strategies, it was found that the development of this strategy can effectively optimize open sequences.

The model predictive control method can be effective for converter control in distributed power generation but requires a large amount of computation, leading to a considerable time delay in the actuation. If the delay is not reflected, the system performance could get worse. This paper presents a two-step (horizon) prediction algorithm of model predictive control technique for grid-tied inverters used in wind turbine systems. The control objectives such as active and reactive power flow and switching loss reduction are reflected in the objective function of the controller. The proposed model predictive control strategy is verified numerically by using MATLAB/Simulink.

Conventional model predictive power control (MPPC) features a simple concept and quick dynamic response. However, it relies heavily on the system model and its parameter accuracy. Furthermore, the steady ripples are still high due to the use of one voltage vector during one control period. Recently, model-free predictive current control (MFPCC) has been proposed in the current control of PWM rectifiers. Despite the strong parameter robustness, the principle of MFPCC cannot be directly applied to power control, because the relationship between power and converter voltage is more complex. This paper first proposes a basic model-free predictive power control (MFPPC), which successfully extends the principle of MFPCC to power control. Subsequently, an improved MFPPC is proposed, which uses an extended finite control set of voltage vectors to improve the steady-state performance. Furthermore, by using the online updated ultralocal model of PWM rectifiers, the problem of stagnant power updating in basic MFPPC is solved. The ideal three-phase grid voltages are symmetrical and sinusoidal, but the actual grids are usually unsymmetrical. In this paper, the proposed method is extended to asymmetrical power grids by adding an appropriate compensated power to the original power references. The proposed basic MFPPC and improved MFPPC are compared to conventional MPPC. The presented experimental results confirm the effectiveness of the proposed methods.

This paper proposes a model predictive direct power control scheme for nonredundant fault tolerant grid-connected bidirectional voltage source converter (BVSC) with balanced dc-link split capacitor voltage and high reliability. Based on the operation analysis of fault-tolerant BVSC with phase leg faults, a power predictive model of three-phase four-switch fault-tolerant topology in αβ coordinates is established, and the space voltage vectors with unbalanced dc-link split capacitor voltage are analyzed. According to the power predictive model and cost function, the optimal space voltage vector is selected to achieve a flexible, smooth transition between inverter and rectifier mode with direct power control. Pulse width modulation and phase locked loop are not required in the proposed method. The constraint of dc-link voltage constraint is designed for the cost function to achieve a central point of dc-link voltage offset suppression, which can reduce the risk of electrolytic capacitor failure for over-voltage operation. With the proposed control method, the converter can work continuously in both inverter mode and rectifier mode, even if phase leg faults occur. The simulation and experimental results show good steady-state and dynamic performance of the proposed control scheme to enhance the reliability of bidirectional power conversion.