Finite Control Set Model Predictive Control Strategy Research Articles

Finite Control Set Model Predictive Control for LCL-Filtered Grid-Tied Inverter With Minimum Sensors

Recently, finite control set model predictive control (FCS-MPC) has been successfully applied in the grid-tied inverter with the LCL filter. However, to achieve active damping and grid synchronization, many sensors are required, increasing cost, and complexity. In addition, a considerable computational delay should be addressed when it is experimentally implemented, which may degrade the performance of the overall system. In order to reduce the number of sensors, eliminate the computational delay, and enhance the control reliability of the system, a novel FCS-MPC strategy with merely grid-injected current sensors is proposed, which contains four compositions: virtual flux observer, state observer, delay compensation, and FCS-MPC algorithm based on estimations. A 3-kW/3-phase/110-V experimental platform is established to validate that utilizing the proposed observations-based control method with only grid-injected current sensors is capable to obtain satisfactory performance of grid synchronization and high-quality grid-injected current both under balanced and unbalanced grid voltage condition.

An Improved Finite Control Set-MPC-Based Power Sharing Control Strategy for Islanded AC Microgrids

Hierarchical linear control scheme is widely used in ac microgrids. However, its transient response is slow and parameter tuning is time-consuming. Finite Control Set-Model Predictive Control (FCS-MPC) strategy has desired dynamic performance. Nevertheless, it requires an additional sensor to measure the inductor current. This article aims to mitigate these problems by introducing an improved FCS-MPC strategy for paralleled Voltage Source Inverters (VSIs). A capacitor current estimator is employed to reduce the extra current sensor in each VSI. The proposed control scheme consists of two loops: voltage reference generation loop and voltage tracking loop. The voltage reference generation loop achieves accurate load power sharing using virtual impedance-based droop control. Thus, communication is unnecessary among parallel VSIs. The voltage tracking loop utilizes a modified FCS-MPC block with capacitor current estimator to regulate the VSI output voltage. In order to verify the concept of the proposed control strategy, an ac microgrid consisting of two paralleled VSIs is implemented in dSPACE DS1202 hardware-in-the-loop platform. Then a single VSI hardware prototype is implemented and tested experimentally. The proposed method has the merits of good extensibility, low system cost and compact structure. Its steady-state performance is competitive with hierarchical linear control, while the transient response is significantly improved.

Finite Control Set Model Predictive Control for an LCL-Filtered Grid-Tied Inverter with Full Status Estimations under Unbalanced Grid Voltage

This paper proposes a novel finite control set model predictive control (FCS-MPC) strategy with merely grid-injected current sensors for an inductance-capacitance-inductance (LCL)-filtered grid-tied inverter, which can obtain a sinusoidal grid-injected current whether three-phase grid voltages are balanced or not. Compared with the conventional FCS-MPC method, four compositions are added in the proposed FCS-MPC algorithm, where the grid voltage observer (GVO) and Luenberger observer are combined together to achieve full status estimations (including grid voltage, capacitor voltage, inverter-side current, and grid-injected current), while the sequence extractor and the reference generator are applied to eliminate the double frequency ripples of the active or reactive power, or the negative sequence component (NSC) of the grid-injected current caused by the unbalanced grid voltage. Simulation model and experimental platform are established to verify the effectiveness of the proposed FCS-MPC strategy, with full status estimations under both balanced and unbalanced grid voltage conditions.

Finite-Control-Set Model Predictive Control of Modular Multilevel Converters With Cascaded Open-Circuit Fault Ride-Through

Open-circuit fault ride-through (FRT) is indispensable for the reliable operation of modular multilevel converters (MMCs). In this paper, finite-control-set model predictive control (FCS-MPC)-based fault detection and isolation (FDI) and fault-tolerant (FT) schemes are proposed for cascaded open-circuit FRT of MMCs. Taking advantage of the known switching state in FCS-MPC, the errors between the applied and estimated inserted submodule (SM) numbers are utilized for FDI directly. These fault diagnostic signals are independent of the voltage and current ratings and not sensitive to parameter variations. Moreover, it can locate the fault very fast within a fundamental period. By introducing the healthy state set of the SMs, an FCS-MPC strategy with cascaded open-circuit FRT is developed. Switching combinations, which will insert the faulty SMs, are inherently avoided by imposing an additional constraint in the cost function. This integrates the FRT into the control scheme, thereby, resulting in seamless FT operations. The reliability improvement by the proposed FRT scheme is numerically analyzed to present the effectiveness of the proposed method. Experimental results show that open-circuit faults can be detected and isolated within several milliseconds and the cascaded open-circuit faults of MMCs can be seamlessly ridden through by the proposed scheme.

A Computationally Efficient FCS-MPC Method Without Weighting Factors for NNPCs With Optimal Duty Cycle Control

In this paper, a computationally efficient finite control-set model predictive control (FCS-MPC) method without weighting factors is proposed for nested neutral point-clamped converters (NNPCs) with optimal duty cycle control. The aim of this paper is to design a modification of the FCS-MPC scheme that improves the steady-state performance, as well as to avoid the weighting factors selection while remaining computationally feasible. First, in order to improve the calculation efficiency, a simplified computational method is proposed by introducing the Lyapunov principle into the design of sector distribution method based on space vector modulation technique, and eliminates unwanted switching states. Second, aiming at improving the steady-state control performance, an optimal duty cycle control technique is incorporated into the proposed FCS-MPC strategy to determine the time duration of the selected voltage vector. In that sense, a new FCS of candidate voltage vectors with different duty cycles are synthesized without sacrificing the simplicity of the control structure. Besides, in order to avoid the selection of weighting factors, the proposed method replaces the single cost function with simplified multiobjective optimization strategy based on a fuzzy-decision-making method. Finally, the performance of the proposed strategy for NNPCs is evaluated by simulation studies in various operating conditions.

Finite control set model predictive control with feedback correction for power converters

As an open-loop model predictive control algorithm, finite control set model predictive control (FCS-MPC) scheme in power converter system is based on assumption that responses of optimal control implemented on prediction model agree well with actual system. The influence of model parameter mismatches and environment disturbance on control performance of scheme is neglected. Then, based on feedback correction strategy in traditional model predictive control algorithm, we derive a finite control set model predictive control with feedback correction scheme (FCS-MPCFC) that allows us to adjust prediction model output at current instant by model prediction error at previous instant, and the closed-loop correction of prediction model output is achieved. Simulations comparison analyses on a two-level three-phase inverter with multi-type model parameter mismatches controlled by traditional and improved FCS-MPC scheme are presented. Experiments are carried out on DSP controller platform.

An improved finite control-set model predictive control for nested neutral point-clamped converters under both balanced and unbalanced grid conditions

Finite control-set model predictive control (FCS-MPC) is an alternative strategy, in particular, for multi-level converters. However, the computational burden is rapidly increased with the number of voltage vectors to be predicted and objectives to be controlled. This will hinder the development of the FCS-MPC strategy. In this paper, an improved FCS-MPC is proposed for nested neutral point-clamped converters (NNPCs) under both balanced and unbalanced grid conditions. Specifically, to reduce the computational burden, an optimized voltage vector selection process based on deadbeat technique is embedded into the proposed design. Meanwhile, a simplified cascade-free control strategy is presented to directly govern the DC-link voltage and reactive power in NNPCs while the flying capacitor voltages are maintained balanced. Moreover, the inclusion of a power compensation approach is presented for the FCS-MPC method in an attempt to obtain desired grid-side currents under nonideal grid-side voltage conditions. The novelty of this work lies not only in a compatible reference design that directly allows to formulate the optimal control problem using a simplified cascade-free control strategy, but also in the utilization of combining the proposed FCS-MPC and the power compensation technique for suppressing the distorted grid-side currents under unbalanced grid conditions. The performance of the proposed strategy for NNPCs is evaluated by simulation studies in various operating conditions.

Grid Integration and Power Smoothing of an Oscillating Water Column Wave Energy Converter

This paper applies model predictive control (MPC) for the power processing of an oscillating water column (OWC) wave energy conversion (WEC) system to achieve smooth power delivery to the grid. The particular air turbine design adopted in this study produces large power pulses ranging from 0 to 1 MW in magnitude, and thus, direct connection to the grid is practically impossible, especially in weak grid conditions. Therefore, energy storage is an essential element that should be integrated into this particular WEC system in order to absorb power pulses and thereby ensure smooth delivery of power to the grid. Taking into account the repetitive nature, duration, and magnitude of the power pulses, this study has chosen “supercapacitor” as the suitable energy storage technology. The supercapacitor energy storage (SCES) is integrated into the dc-link of the back-to-back power converter of the WEC system through a bidirectional dc-dc converter. In order to achieve the desired operation of this complex power converter arrangement, a finite control set MPC strategy is proposed in this paper. Performance of the proposed energy storage system (ESS) and control strategy are evaluated through computer simulations. Simulation results show that the proposed SCES system and the control strategy are able to achieve smooth power delivery to the grid amidst power pulses coming from the generator.

Model Predictive Control of Power Converters for Robust and Fast Operation of AC Microgrids

This paper proposes the application of a finite control set model predictive control (FCS-MPC) strategy in standalone ac microgrids (MGs). AC MGs are usually built from two or more voltage source converters (VSCs) which have the capability of regulating the voltage at the point of common coupling, while sharing the load power at the same time. Those functionalities are conventionally achieved by hierarchical linear control loops. However, they present severe limitations in terms of slow transient response and high sensitivity to parameter variations. This paper aims to mitigate these problems by first introducing an improvement of the FCS-MPC strategy for a single VSC that is based on explicit tracking of derivative of the voltage reference trajectory. Using only a single step prediction horizon, the proposed strategy exhibits very low computational expense, but provides steady-state performance comparable to carrier-based sinusoidal PWM, while its transient response and robustness to parameter variation is far superior to hierarchical linear control. These benefits are exploited in a general ac MG setting where a methodology for paralleling multiple FCS-MPC regulated VSCs is described. Such an MG is characterized by rapid transient response, inherent stability in all operating conditions, and fully decentralized operation of individual VSCs. These findings have been validated through comprehensive simulation and experimental verification.

Finite Control Set–Model Predictive Control with Modulation to Mitigate Harmonic Component in Output Current for a Grid-Connected Inverter under Distorted Grid Conditions

This paper presents an improved current control strategy for a three-phase grid-connected inverter under distorted grid conditions. In terms of performance, it is important for a grid-connected inverter to maintain the harmonic contents of inverter output currents below the specified limit even when the grid is subject to harmonic distortion. To address this problem, this paper proposes a modulated finite control set–model predictive control (FCS-MPC) scheme, which effectively mitigates the harmonic components in output current of a grid-connected inverter. In the proposed scheme, the system behavior in the future is predicted from the system model in the discrete-time domain. Then, the cost function is selected based on the control objective of system. This cost function is minimized during the optimization process to determine the control signals that minimize the cost function. In addition, since the proposed scheme requires pure sinusoidal reference currents in the stationary frame to work successfully, the moving average filter (MAF) is employed to enhance the performance of the traditional phase lock loop (PLL). Due to the control performance of the FCS-MPC scheme as well as the harmonic disturbance rejection capability of the MAF-PLL, the proposed scheme is able to suppress the harmonic distortion even in the presence of distorted grid condition, while retaining fast transient response. Comparative simulation results of different controllers verify the effectiveness of the proposed control scheme in compensating the harmonic disturbance. To validate the practical feasibility of the proposed scheme, the whole control algorithm is implemented on a 32-bit floating-point digital signal processor (DSP) TMS320F28335 to control a 2 kW three-phase grid-connected inverter. As a result, the proposed scheme is a promising approach toward improving the current quality of a grid-connected inverter under distorted grid conditions.

Predictive Control of Cascaded H-Bridge Converters Under Unbalanced Power Generation

This paper presents a predictive control strategy for grid-connected cascaded H-bridge (CHB) converters under unbalanced power generation among each converter phase. The proposed controller belongs to the finite-control-set model predictive control (FCS-MPC) family and is designed to extract unbalanced power from each CHB converter phase while providing balanced power to the grid. The key novelty of this strategy lies in the way the unbalanced power generation among the phases is explicitly considered into the optimal control problem. Power balance is achieved by enforcing the CHB converter to work with a suitable zero-sequence voltage component. The proposed predictive controller is directly formulated in the original $abc$ -framework to account for the common-mode voltage. Simulation and experimental results are provided to verify the effectiveness of the proposed FCS-MPC strategy.

Nonlinear FCS-MPC strategy of NPC/H-5 L inverter based on satisfactory optimization algorithm

In the design of the cost function in the nonlinear finite control set model predictive control (FCS-MPC) system, the traditional method based on weighting factors demonstrates some limitations, such as the weighting factors adjusting and heavy predictive calculation due to the increased number of voltage vectors applied in controlling multilevel converters. This paper proposes a simplified FCS-MPC method based on common mode voltage satisfactory optimization, which could considerably reduce the predictive calculation by the optimized switch combination and simplify the cost function design. Moreover, satisfactory optimization is adopted to achieve the accuracy control of common-mode voltage amplitude without adjusting process of weighting factors. The simulation and experimental results verify the feasibility of this control strategy.

Indirect Finite Control Set Model Predictive Control of Modular Multilevel Converters

The modular multilevel converter (MMC) is a potential candidate for medium/high-power applications, specifically for high-voltage direct current transmission systems. One of the main challenges in the control of an MMC is to eliminate/minimize the circulating currents while the capacitor voltages are maintained balanced. This paper proposes a control strategy for the MMC using finite control set model predictive control (FCS-MPC). A bilinear mathematical model of the MMC is derived and discretized to predict the states of the MMC one step ahead. Within each switching cycle, the best switching state of the MMC is selected based on evaluation and minimization of a defined cost function. The defined cost function is aimed at the elimination of the MMC circulating currents, regulating the arm voltages, and controlling the ac-side currents. To reduce the calculation burden of the MPC, the submodule (SM) capacitor voltage balancing controller based on the conventional sorting method is combined with the proposed FCS-MPC strategy. The proposed FCS-MPC strategy determines the number of inserted/bypassed SMs within each arm of the MMC while the sorting algorithm is used to keep the SM capacitor voltages balanced. Using this strategy, only the summation of SM capacitor voltages of each arm is required for control purposes, which simplifies the communication among the SMs and the central controller. This paper also introduces a modified switching strategy, which not only reduces the calculation burden of the FCS-MPC strategy even more, but also simplifies the SM capacitor voltage balancing algorithm. In addition, this strategy reduces the SM switching frequency and power losses by avoiding the unnecessary switching transitions. The performance of the proposed strategies for a 20-level MMC is evaluated based on the time-domain simulation studies.

Switching Strategy Based on Model Predictive Control of VSI to Obtain High Efficiency and Balanced Loss Distribution

This paper proposes the switching strategy based on finite control set model predictive control (FCS-MPC) method, to reduce switching losses and obtain balanced loss distribution of the voltage-source inverters (VSIs). Unlike the conventional FCS-MPC method with no explicit information of the reference voltage, the developed voltage-based FCS-MPC scheme produces the future reference voltage vector with the Lyapunov function every sampling period. With information of both the future reference voltage and the future load current vectors, the proposed switching strategy instantaneously determines one optimum clamped phase among the three legs in the VSI every sampling period. By optimally determining the clamping phase and its duration on the basis of every sampling period, the proposed switching strategy can successfully reduce the VSI switching losses. In addition, the proposed switching method can yield a balanced loss distribution among the switches in the VSI, contrary to the conventional FCS-MPC. The balanced loss generation as well as the switching loss reduction by the proposed method, which is optimal at the sampling period scale, is directly incorporated with the platform of the FCS-MPC algorithm, since the FCS-MPC operates on the basis of the sampling period. Thus, the proposed switching operation based on the voltage-based FCS-MPC algorithm enables the future VSI output currents to track the future reference current vector, as well as results in the reduced switching losses and the balanced loss performance.

영구자석 동기 전동기의 토크 제어 및 토크 리플 저감을 위한 유한 제어요소 모델 예측제어(FCS-MPC) 설계

This paper proposes a torque control method of permanent magnet synchronous motor, which has small torque ripple. The proposed control method is using the finite control set-model predictive control(FCS-MPC) strategy. An optimal input voltage vector minimizing a cost function is chosen among 6 passible active input voltage vectors following the FCS-MPC strategy. Then, a modulation factor for the optimal input voltage vector is computed to minimize the torque ripple. Thus, the proposed control method yields fast torque response and small torque ripple. The efficacy of the proposed method was verified through simulation and experiment.