Model Predictive Direct Power Control Research Articles

A Dual control strategy for improved power quality in grid-tied off-board bidirectional electric vehicle charger

Electric vehicle (EV) chargers face significant challenges in maintaining grid power quality (PQ) and ensuring efficient power management during grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operations. Additionally, they must seamlessly switch to vehicle-to-load (V2L) mode during grid disturbances to provide uninterrupted power supply (UPS) for domestic loads. This article explores a dual control approach incorporating adaptive model predictive direct power control (AMP-DPC) on the rectifier side and adaptive direct power control (ADPC) on the dual active bridge (DAB) side to address these challenges. The AMP-DPC employs a control strategy referred to the second-order generalized integrator (SOGI) which estimate synchronizing voltage templates specifically designed for single-phase systems. The proposed optimization control aims to mitigate the cost function value by selecting appropriate switching modes. The optimized function is independent of the weighting factor, expressing the optimal modulation function across various weighting factors without additional design or selection. The current reference used by the charger is designed to ensure that the power factor remains at closer unity throughout G2V and V2G modes. The proposed control algorithm ensures the grid current remains low in harmonics during G2V, V2G, and V2L modes of operation. The experimental validation of the proposed control strategy is performed in the laboratory on a 0.5 kW off-board electric vehicle charger (EVC) prototype under various conditions to demonstrate its effectiveness in compliance with the IEEE 519–2022 standard.

Reduced complexity model predictive direct power control for unbalanced grid

The model predictive control (MPC) group is frequently used as a controller in PWM rectifiers because of its accuracy. Yet, the requirement of a processor with high computational efficiency for its real-time implementation has been a significant drawback. Although a few low-complexity MPCs have been reported in the past, none of such methods are validated in an unbalanced grid. Hence, this work aims to propose a reduced-complexity MPC algorithm that can also handle an unbalanced grid. The conventional MPC evaluates the cost function for all the switching vectors and then chooses the switching vector that produces the minimum cost. In contrast, by equating its first-order derivative of the cost function to 0, the proposed analytical approach directly evaluates switching vectors, resulting in a minimum value of the cost function. Thus, the controller estimates only the closest possible solutions of the cost function minimization process and abandons the rest. Furthermore, the proposed method also endorses the use of additional non-linear constraints in the cost function, which eradicates one of the major drawbacks of the previous low-complexity techniques. To ascertain the practicability of the proposed method, it is examined in the MATLAB/Simulink environment and the real-time system. The obtained results look promising as the proposed controller is able to imitate the performance of conventional MPC with less computational burden.

High-Efficient Direct Power Control Scheme Using Predictive Virtual Flux for Three-Phase Active Rectifiers

In recent years, the pulse-width-modulation (PWM) converter has been found to have extensive applications in renewable energy, industrial fields, and others. The high efficiency requirement is crucial to operating a PWM rectifier in various applications, in addition to the fundamental control objectives of sinusoidal grid currents and the correct DC bus voltage. Additionally, in practical application, another issue arises when the grid voltage frequently experiences distortion, leading to a distorted grid current and a significant rise in total harmonic distortion (THD). To resolve these problems, a model predictive virtual flux-based direct power control (MPVFDPC) with improved power loss performance is proposed based on an integrated switching state predetermination strategy. The proposed MPVFDPC for PWM rectifier inherits the merits of both virtual flux control and direct power control, which have fast dynamic performance and the grid current THD is considerably decreased under distorted grid voltage states. The proposed technique aims to minimize switching loss under ideal and distorted grid voltage states by exploiting the discontinuous modulation concept by using a switching state predetermination strategy. The MPVFDPC with switching state predetermination strategy is proven by employing it in experiments as well as simulations in comparison with previous models: predictive direct power control (Conv. MPDPC) and conventional MPVFDPC (Conv. MPVFDPC). The acquired waveforms and quantitative data are employed to prove the effectiveness of the developed algorithm.

Model predictive direct power control of energy storage quasi-Z-source grid-connected inverter

Model predictive direct power control of energy storage quasi-Z-source grid-connected inverter

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.

Research on protection and control technology of power electronic transformers

As the key equipment in the modern power system, the power electronic transformer's performance and reliability play a vital role in the stable operation of the power system. This paper studies the soft switching technology, control technology and fault protection method of power electronic transformer. First, the soft switching technology of power electronic transformers is introduced, including zero voltage switching, zero current switching and so on. These soft switching technologies can effectively reduce the switching loss of the transformer, improve efficiency, and reduce electromagnetic interference and harmonic generation. Secondly, the control technology of power electronic transformer is introduced, including traditional proportional, integral, and derivative control (PID) control, model predictive control and direct power control. These control technologies can realize the precise control of the output voltage and current of the power electronic transformer, to meet the requirements of the power system for power quality and stability. In addition, this paper also introduces the fault protection methods of power electronic transformers, including short-circuit protection, over-voltage protection and over-medium current protection. These fault protection methods can effectively protect power electronic transformers from various faults and ensure their normal operation and safety.

Research on the overvoltage suppression strategy of single-phase photovoltaic grid-connected systems based on FCS-MPDPC

For the overvoltage problem brought by the access of high-penetration photovoltaic power plants to the low-voltage distribution network, this paper chooses to deal with it by using the reactive power regulation capability of photovoltaic power plant inverters, which reduces the equipment investment in distribution line voltage regulation. Based on the reactive power regulation theory of the inverter, a finite set model predictive direct power control method is proposed by constructing a virtual voltage vector, taking a single-phase cascaded 2H bridge grid-connected inverter as an example, to realize independent control of active and reactive power. By setting different power reference values, the inverter can be made to have two functions: grid-connected per-unit power factor and reactive power control during overvoltage. Finally, the two modes of inverter operation are verified by Simulink simulation, and the verification by example shows that the method can limit the grid-connected voltage deviation to within 7% and meet the requirements of grid-connected regulations.

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

A power compensated triple-vector model predictive direct power control (PCTV-MPDPC) strategy is proposed in this paper for non-redundant fault-tolerant three-phase rectifiers. The system fault tolerance ability and post-fault control performance are enhanced with low hardware complexity. By defining the negative conjugate of complex power as the control variable, a straight-forward pattern of power-voltage relationship analysis is obtained. Besides, a novel voltage vector selection method is put forward based on the location of the error vector between the reference and real control variables. The sector identification process can be omitted to derive a unified expression for duty ratio calculation. On top of that, an intuitive power compensation architecture is proposed to eliminate the dc-bus voltage deviation so that its utilization rate can be maximized. With the proposed PCTV-MPDPC strategy, the power ripples and input current harmonics can be significantly reduced. Superior steady-state and dynamic performance can be achieved compared with the conventional finite-control-set MPDPC (FCS-MPDPC) scheme and a recently proposed multiple-vector model predictive power control (MV-MPPC) method, along with excellent dc-bus voltage deviation suppression effect. Furthermore, simulation validation in Matlab/Simulink and experimental verification on a four-switch three-phase rectifier are carried out to demonstrate the effectiveness of the proposed PCTV-MPDPC strategy.

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

Finite-Set Model Predictive Direct Power Control for DFIG with Reduced Number of Voltage Vectors

This paper proposes a Simplified Finite-Set Model Predictive Power Controller (MPPC) to improve the performance of the Doubly-Fed Induction Generator (DFIG). The MPPC is implemented to regulate the stator active and reactive powers of DFIG, minimizing the error between them and their references, with an optimized null vector selection and a reduced number of active vectors, to decrease the computational burden. This reduction is applied in a two-level converter, reducing the test to 4 or 2 active vectors. Simulations and laboratory experiments were performed, showing results for a 0.56 kW DFIG. Finally, it was verified that the proposed system can maintain the stator powers at a reference.

Improved Model Predictive Direct Power Control for Parallel Distributed Generation in Grid-Tied Microgrids

This research proposes an improved finite control set direct power model predictive control method (FCS-DPMPC) for grid-tie distributed generation (DG). FCS-DPMPC predicts the system outcomes using the system model. During the next sampling time, a voltage vector is defined using the cost function to minimize the power ripple, consequently allowing flexibility for power regulation. Furthermore, the impact of implementing a one-step delay is studied and compensated through a model forecast pattern. In addition, a new two-step horizon technique has been developed to minimize switching frequency and computation burden. Simulation results for single DG and parallel operated DGs in a grid-tie manner confirm the effectiveness of the suggested control strategy, which signifies that this is an appropriate approach for distributed generation in microgrids.

Performance-Based Tuning for a Model Predictive Direct Power Control in a Grid-Tied Converter With L-Filter

Model predictive control (MPC) is a powerful and widely used technique to address the control challenges in power converters as the grid interface for renewable energy systems. This technique combines closed-loop control with error and control effort minimization; however, its design is challenging, and we know little about how the controller parameters affect the closed-loop performance of grid-connected voltage source converters. In this study, we applied an MPC direct power control with modulation for a grid-connected power converter with an inductive filter. For the controller design, we proposed an initial set based on the power converter’s nominal setup. Then, we define the range of settings to guarantee stability by analyzing the closed-loop poles of the system. The fine-tuning to improve the performance can be identified visually using the performance maps built from simulations of the control system, simultaneously sweeping the time horizons of the predictive model and the weight factors of the cost function. Experimental results on a low-power bench demonstrate the excellent performance of the designed controller, following and even outperforming the classical proportional-integral (PI) controller and other advanced control techniques.

Research on MPDPC with FADRC control strategy for three-phase rectifying converter

Due to unpredictable factors, the model predictive direct power control (MPDPC) exists weak robustness when the parameters change of three-phase rectifying converter. Therefore, this paper introduced Fractional Active Disturbance Rejection Control (FADRC) into the MPDPC system to improve the robustness of rectifying converter, that is, the power loop of PID controller in conventional model predictive control is replaced by FADRC. In order to verify the effectiveness of the proposed control strategy in this paper, a model of three-phase rectifying converter is established in MATLAB, and the simulation is conducted. Compared with the control effects of the MPDPC with PID (MPDPC-PID) control strategy and MPDPC with Linear Active Disturbance Rejection Control (MPDPC-LADRC) under different operational scenarios, the simulation results demonstrate that the MPDPC with FADRC (MPDPC- FADRC) strategy has best disturbance rejection capability, robustness and rapidity, and it can significantly reduce the voltage fluctuation of DC bus. This study can provide a valuable guidance and reference for the design of the efficient and stable three-phase rectifying converter.

Simplified Three-Vector-Based Model Predictive Direct Power Control for Dual Three-Phase PMSG

The conventional model predictive power control suffers from heavy computational burden and large power ripple. To address the problem, this paper proposes a simplified three-vector-based model predictive direct power control, which can greatly optimize the control set. Firstly, a switching table is designed to exclude the redundant virtual voltage vectors (VVs). Only half of the candidate VVs are retained. Then, the effect of each VV on power is analyzed in detail. The deviation of reactive power is used as the evidence to further simplify the control set. In this way, the prediction behavior is reduced from 12 to 2, which effectively reduces the computational burden. In addition, the concept of power deadbeat is employed to determine the duty cycles of the two virtual VVs and one zero VV. Thus, the power ripples and current harmonics can be considerably suppressed. With this proposed method, the calculation complexity is reduced, and the steady-state performance is improved. The simulation and experimental results are given to verify the proposed method.

An Improved Low-Complexity Model Predictive Direct Power Control With Reduced Power Ripples Under Unbalanced Grid Conditions

This article proposes an improved low-complexity model predictive direct power control (LC-MPDPC) along with reduced power ripples. Different from those MPDPC methods under balanced grid voltage conditions, both the design and implication of MPDPC under unbalanced grid conditions are further studied. In the proposed MPDPC, to reduce the computational burden of the controller, an improved LC-MPDPC based on the extended reactive <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">pq</i> theory is proposed. Only one prediction is needed to select the next voltage vector. Besides, the defined cost function under balanced grid conditions cannot obtain the minimized value if the unbalanced grid conditions occur. Accordingly, a new power error is defined, which is described analytically in the optimal model. With the proposed LC-MPDPC, a negative conjugate of the new defined complex power is selected as the control variable, and an improved modulation for the LC-MPDPC is presented to ensure the best voltage and calculate the optimal duration under unbalanced grid conditions. Compared with prior MPDPC, the proposed LC-MPDPC obtains much lower power ripples and grid current total harmonic distortion, and further, it offers a fast dynamic response and robustness. The effectiveness of the proposed LC-MPDPC is evaluated and validated by the experimental results.

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.

Performance Enhancement of a Hybrid Renewable Energy System Accompanied with Energy Storage Unit Using Effective Control System

The current study aims to present a detailed analysis of a hybrid renewable energy system used for standalone operation. The hybrid system consists of a wind-driven synchronous generator, a photovoltaic solar system, and a battery storage system. The modeling of each system component is presented and described in detail. To achieve optimal energy exploitation, the maximum power point tracking algorithm is adopted. The management of synchronous generator operation is achieved through controlling the machine-side converter using a newly formulated predictive control scheme. To visualize the advantages of the proposed control algorithm, its performance is compared with the other two traditional predictive control approaches, mainly the model predictive direct power control and model predictive direct torque control systems. An effective control scheme is also adopted to manage the power storage in the battery using a bi-directional DC/DC converter. To maintain a balanced power flow between the system units, an energy management strategy is presented. Extensive tests are carried out to evaluate the performance of the hybrid system considering variable wind speed, variable sun irradiation, and variable load profiles. The obtained results for the synchronous generator performance visualize the validity and superiority of the proposed control scheme over the other two classic controllers. The results are also validating the effectiveness of the battery storage control system and confirming the validity of the constructed energy management strategy in achieving the energy balance between the system units.

Dynamic Performance Enhancement of a Renewable Energy System for Grid Connection and Stand-Alone Operation with Battery Storage

This paper introduces a new formulated control scheme for enhancing the dynamic performance of a wind driven surface permanent magnet synchronous generator. The designed control scheme is based on predictive control theory, in which the shortcomings of previous predictive controllers are avoided. To visualize the effectiveness of the proposed control scheme, the performance of the generator was dynamically evaluated under two different operating regimes: grid connection and standalone operation in which a battery storage system was used to enhance the power delivery to the isolated loads. In addition, a detailed performance comparison between the proposed controller and traditional predictive controllers was carried out. The traditional control topologies used for comparison were the model predictive direct power control, model predictive direct torque control, and model predictive current control. A detailed description of each control scheme is introduced illustrating how it is configured to manage the generator operation. Furthermore, to achieve the optimal exploitation of the wind energy and limit the power in case of exceeding the nominal wind speed, maximum power point tracking and blade pitch angle controls were adopted. A detailed performance comparison effectively outlined the features of each controller, confirming the superiority of the proposed control scheme over other predictive controllers. This fact is illustrated through its simple structure, low ripples, low computation burdens and low current harmonics obtained with the proposed control scheme.

Model predictive direct power control of three-level T-type inverter-fed doubly-fed induction generator for wind energy system

The paper proposes a simplified direct power control strategy of a doubly-fed induction generator fed by a three-level T-type inverter based on finite control set model predictive control. A mathematical model based on grid voltage orientation was employed to determine the predictive values of the stator flux, rotor current, and capacitor voltages for all feasible rotor-side inverter output voltages. The active and reactive powers were calculated by using the grid voltage and the rotor current. A cost function was applied to track the active and reactive powers, maintain the balance of capacitor voltages, and reduce the common-mode voltage. The best switching control input was chosen by minimizing the cost function and implemented to the inverter. Different operating conditions of wind turbine systems were studied with Matlab/Simulink environment. The simulation results validate the improved performance of the proposed method compared with the classical control in terms of transient response and steady-state conditions.

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.