Predictive Direct Power Control Strategy Research Articles

Neural Network Quadrature Signal Generator-Based Virtual Flux Estimation for Predictive Control of PWM Converters

In this paper, a frequency-adaptive neural network-based virtual flux (FANN-VF) estimator is developed for sensorless control of a pulse-width modulation converter under unbalanced and distorted grid conditions. This method exploits two parallel FANNs configured as quadrature signal generators. The VF fundamental positive and negative sequence components (PNSCs) are inherently separated in the estimator without employing any cascaded filters. A frequency-locked loop is introduced to accurately track the frequency variations. The estimated VF PNSCs are directly exploited to compute the power references in VF-based predictive direct power control scheme. The developed strategy ensures constant active power and sinusoidal current waveforms under nonideal grid conditions. Simulation and experimental tests are performed to verify the effectiveness of the proposed method.

New combined control strategy of on-board bidirectional battery chargers for electric vehicles

This paper aims to develop a bidirectional on-board battery charger for electric vehicles (EVs). The studied battery charger is composed of a bidirectional ac-dc converter as the first stage of conversion and a bidirectional dc-dc converter as the second stage. The first one is controlled by a predictive direct power control strategy based on a space vector modulation technique known as P-SVM-DPC, and the second is used to regulate the battery current and regulate the power direction flow by using a direct current control technique. The choice of its topology has taken into consideration the grid-to-vehicles (G2V) and vehicle-to-grid (V2G) power flow directions. During charging or discharging, the DC/DC converter acts likes a buck or boost converter. Using MATLAB/Simulink software, the performance of the battery charger is examined in various operating modes, such as fast charging and quick discharging.

Mode Predictive Direct Power Control Scheme with Fixed Operation Frequency for a Vienna Rectifier Based on Voltage‐Sensorless

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 low-computation model predictive direct power control strategy for three-level four-leg active power filter

An improved low-computation model predictive direct power control strategy for three-level four-leg active power filter

Model predictive direct power control strategy for leakage current suppression on a grid‐connected three‐level inverter

AbstractThe nonisolated grid‐connected photovoltaic inverter system suffers from the problem of leakage current. Therefore, a leakage current suppression control strategy based on the model predictive direct power control is proposed for the three‐level four‐leg grid‐connected inverter. At first, the system model is established to analyze the factors that affect the leakage current and the potential of the neutral point. Second, the first three legs, inverting part, use model predictive direct power control, and the fourth leg of the inverter is used to maintain a constant common‐mode voltage to achieve the suppression of the leakage current. The fourth leg is indirectly controlled by the switch state of the first three legs; thus, the number of optimization times is reduced. Finally, by simulation, the leakage current is compared and analyzed with the three‐level three‐leg inverter under conditions with different parasitic capacitance values. The results show that the proposed strategy suppresses the leakage current by more than 60% without affecting the neutral point potential and has a fast optimization speed.

Model Predictive Direct Power Control for Virtual-Flux-Based VSR With Optimal Switching Sequence

Three-phase voltage-source rectifier (VSR) has been widely used in energy, industry and other fields in the past few years. Model predictive control with optimal switching sequence (OSS-MPC) has further reduced output current THD and ripples with a constant switching frequency, compared with the conventional model predictive control (MPC). However, in practical application, the AC side voltage is often in a distorted state, which causes a distorted AC side current and a dramatic increase of THD. To overcome the drawback mentioned before, based on the analysis of OSS-MPC and combined with virtual flux oriented direct power control strategy, a virtual-flux-based model predictive direct power control strategy with optimal switching sequence (VF-OSS-MPDPC) is proposed in this paper. This control strategy for VSR combines the advantages of virtual-flux, low-pass filtering characteristics and optimal switching sequence model predictive control, which has high prediction accuracy and the AC current THD are greatly reduced under distorted AC voltage. The proposed control strategy can realize a constant switching frequency in steady-state operation without a modulator, which reduces the complexity of control strategy and the difficulty of AC side filter design. The proposed VF-OSS-MPDPC is validated through simulation and experiment compared with OSS-MPC, which proves the correctness and effectiveness of the proposed control strategy.

Model predictive direct power control scheme for Vienna rectifier with constant switching frequency

Model predictive direct power control (MPDPC) has strong robustness and fast dynamic response, so it is widely applied in the control system of grid-connected converter. However, the traditional FCS-MPC bears with variable switching state, which will reduce the current tracking accuracy, accidentally produce current ripple and electromagnetic noise. Here, a double closed-loop control strategy with constant switching frequency based on optimal switching sequence synthesis of model predictive direct power control (MPDPC-CF) in the inner loop and SMC control in the outer loop is proposed for the non-linear system of Vienna rectifier. Firstly, the Vienna rectifier is modelled to obtain the predicted values of input power. Then, the given values of active power and reactive power are obtained through the outer loop. Three adjacent voltage vectors with the lowest cost function in the sector are selected to synthesize the optimal voltage vector, and the pulse time of the corresponding vector is calculated according to the cost function of the voltage vector. To verify the correctness of the theoretical analysis, the Vienna rectifier is taken as the research object, and the comparison with the traditional MPDPC shows that the proposed constant frequency model predictive control has good steadystate and dynamic performance.

Novel model predictive direct power control strategy for grid‐connected three‐level inverters

Conventional switching table-based direct power control (DPC) usually suffers from higher power ripples due to the heuristic nature of the switching table. This study presents a novel model predictive DPC (MPDPC) strategy for grid-connected three-level inverters. In the proposed MPDPC strategy, a new synchronous frame-based predictive model is first developed and the conjugate of the complex power is then chosen as the control variable to simplify the analysis. Based on the newly developed predictive model, new principles of the voltage vector selection are further derived with the strict analytical proof to match all the control requirements, including the active and reactive power control, neutral point potential balance control, as well as the avoidance of the high voltage jumps. Finally, experimental results are provided to support the theoretical study and confirm the effectiveness of the proposed MPDPC strategy, as well as to demonstrate better performance in both steady-state and dynamic responses over the conventional DPC.

Improved three-vector based dead-beat model predictive direct power control strategy for grid-connected inverters

Since only one inverter voltage vector is applied during each duty cycle, traditional model predictive direct power control (MPDPC) for grid-connected inverters (GCIs) results in serious harmonics in current and power. Moreover, a high sampling frequency is needed to ensure satisfactory steady-state performance, which is contradictory to its long execution time due to the iterative prediction calculations. To solve these problems, a novel dead-beat MPDPC strategy is proposed, using two active inverter voltage vectors and one zero inverter voltage vector during each duty cycle. Adoption of three inverter vectors ensures a constant switching frequency. Thus, smooth steady-state performance of both current and power can be obtained. Unlike the traditional three-vector based MPDPC strategy, the proposed three vectors are selected based on the power errors rather than the sector where the grid voltage vector is located, which ensures that the duration times of the selected vectors are positive all the time. Iterative calculations of the cost function in traditional predictive control are also removed, which makes the proposed strategy easy to implement on digital signal processors (DSPs) for industrial applications. Results of experiments based on a 1 kW inverter setup validate the feasibility of the proposed three-vector based dead-beat MPDPC strategy.

Dead‐beat predictive direct power control of voltage source inverters with optimised switching patterns

This study presents a novel dead-beat predictive direct power control (PDPC) strategy working at nearly constant switching frequency for the voltage source inverter. The proposed strategy employs two active voltage vectors and one null voltage vector during every control period. To solve the problem of negative predicted duration time of active voltage vectors in the conventional dead-beat PDPC strategy, an automatic updating mechanism is designed. When the predicted duration time is negative, the applied voltage vectors will be updated automatically without the need of reselecting voltage vectors or recalculation of the duration time. Accurate tracking of both active and reactive power can be achieved with small power ripples using the strategy proposed in this study. The proposed PDPC strategy shows excellent steady performance and fast dynamic responses. High sampling frequency can also be avoided and the calculation process is simple enough to be implemented on normal DSPs. Simulation and Experimental results are presented to validate the feasibility of the proposed dead-beat PDPC strategy.

Model Predictive Direct Power Control for Nonredundant Fault Tolerant Grid-Connected Bidirectional Voltage Source Converter

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.

A Kalman Filter based Predictive Direct Power Control Scheme to Mitigate Source Voltage Distortions in PWM Rectifiers

In this paper, a predictive direct power control (DPC) method based on a Kalman filter is presented for three-phase pulse-width modulation (PWM) rectifiers to improve the performance of rectifiers with source voltages that are distorted with harmonic components. This method can eliminate the most significant harmonic components of the source voltage using a Kalman filter algorithm. In the process of predicting the future real and reactive power to select an optimal voltage vector in the predictive DPC, the proposed method utilizes source voltages filtered by a Kalman filter, which can mitigate the adverse effects of distorted source voltages on control performance. As a result, the quality of the source currents synthesized using the PWM rectifier is improved, and the total harmonic distortion (THD) values are reduced, even under distorted source voltages.

Predictive Direct Power Control Strategy Based on Two Stage Matrix Converter

Predictive Direct Power Control Strategy Based on Two Stage Matrix Converter

Three-Vector-Based Low-Complexity Model Predictive Direct Power Control Strategy for Doubly Fed Induction Generators

This paper proposes a three-vector-based low-complexity model predictive direct power control (LC-MPDPC) strategy for doubly fed induction generators (DFIGs) in wind energy applications. Previous studies have applied one- and two-vector-based LC-MPDPC strategies for ac/dc converters with a satisfactory control performance. In this paper, an elaborated analysis of the DFIG mathematical model is made and then the feasibility of one- and two-vector-based LC-MPDPC strategies for DFIG are analyzed. However, using these approaches, the steady-state errors cannot be eliminated completely. Thus, a three-vector-based LC-MPDPC is further proposed to eliminate the power error. Both simulation and experimental results indicate that the proposed three-vector-based LC-MPDPC can significantly improve the steady-state performance and achieve an error-free control. In addition, its dynamic performance remains satisfactory compared with one- and two-vector-based LC-MPDPC.

A three‐vector‐based direct power control strategy for three‐phase voltage source PWM converters

SummaryFor traditional direct power control strategy, there exist high steady‐state power ripples and large current harmonics. To solve this problem, this work proposes a novel three‐vector‐based direct power control strategy for three‐phase voltage source pulse‐width‐modulated (PWM) converters. Different from traditional predictive direct power control strategy, an improved vector table is presented and three voltage vectors are selected, which considers the impact of voltage vectors on the active and reactive power simultaneously. The performance of the three‐phase voltage source PWM converters with the proposed control strategy is investigated and compared with the predictive deadbeat direct power control strategy. Furthermore, the three‐phase voltage source PWM converters have also been tested in the condition of different loads and when voltage unbalance occurs. Simulation and experimental work are conducted. The results conclude that the proposed strategy is of simple structure and fast dynamic response. Besides, it can effectively reduce steady‐state power ripples and current harmonics, improving the performance of the three‐phase PWM converters. Copyright © 2016 John Wiley & Sons, Ltd.

Model Predictive Direct Power Control for Grid-Connected NPC Converters

This paper presents a model predictive direct power control scheme for high-power grid-connected neutral-point-clamped converters. The controller regulates the instantaneous real and reactive powers, as well as the neutral-point potential of the converter, within a set of symmetrical bounds while, at the same time, minimizing the switching frequency of the converter. The proposed approach is distinct from previous predictive power control strategies in that a long prediction horizon is used, allowing lower device switching frequencies to be achieved. A detailed model of the system is provided, and the control algorithm is discussed. Simulation results validate the applicability of the controller to a 3-kV 6.72-MVA system. Experimental results, which are presented for a 240-V 1.68-kVA prototype, show good agreement with those obtained in simulation and further validate the concept.

Model Predictive Control of Grid-Connected Inverters for PV Systems With Flexible Power Regulation and Switching Frequency Reduction

This paper presents a model predictive direct power control strategy for a grid-connected inverter used in a photovoltaic system as found in many distributed generating installations. The controller uses a system model to predict the system behavior at each sampling instant. The voltage vector that generates the least power ripple is selected using a cost function and applied during the next sampling period; thus, flexible power regulation can be achieved. In addition, the influence of a one-step delay in the digital implementation is investigated and compensated for using a model-based prediction scheme. Furthermore, a two-step horizon prediction algorithm is developed to reduce the switching frequency, which is a significant advantage in higher power applications. The effectiveness of the proposed model predictive control strategy was verified numerically by using MATLAB/Simulink and validated experimentally using a laboratory prototype.

A Study on Modified Model Predictive DPC of Rectifiers

In this paper, we study a modified predictive direct power control scheme (P-DPC).This scheme which based on model predictive control (MPC) uses a discrete rectifier model to infer the predictive direct power control theme again, and selects the operating time of voltage vector and voltage vector to realize fixed switching frequency through setting the minimum power errors of each sampling period. This control scheme has a lower switching frequency compared to MP-DPC; and it is still simple and clear implemented in the stationary reference frame directly, meanwhile, it does not need PI controllers or voltage-oriented controllers compared to other developed control schemes. We make simulations using MATLAB. The result show the excellence of this novel predictive direct power control scheme through improving the switching frequency, current THD and active power and reactive power quality compared to MP-DPC and LUT-DPC.

Model-Based Predictive Direct Power Control of Doubly Fed Induction Generators

This paper presents a predictive direct power control strategy for doubly fed induction generators (DFIGs). The method predicts the DFIG's stator active and reactive power variations within a fixed sampling period, which is used to directly calculate the required rotor voltage to eliminate the power errors at the end of the following sampling period. Space vector modulation is then used to generate the required switching pulses within the fixed sampling period that results in a constant switching frequency. The impact of sampling delay on the accuracy of the sampled active and reactive powers is analyzed, and detailed compensation methods are proposed to improve the power control accuracy and system stability. Experimental results for a 1.5-kW DFIG system demonstrate the effectiveness and robustness of the proposed control strategy during power steps, and variations of rotating speed and machine parameters. System performance for tracking varying stator power references further illustrates the dynamic performance of the proposed method.