Simple Finite-Control-Set Model Predictive Control of Grid-Forming Inverters With LCL Filters

Young, Héctor; Marin, Victor Augustus; Pesce, Cristián; Rodríguez, José

doi:10.1109/access.2020.2991396

Cited by 43 publications

(24 citation statements)

References 29 publications

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“…According to Eqs. (1), (2), and (7), the output voltage of the converter is derived as: (16) The output voltage includes pulses in which their amplitude is determined by the transformer voltages. Their frequency is obtained by the matrix of the converter switching states.…”

Section: Reducing Motor Torque Ripple and Supply Current Thdmentioning

confidence: 99%

See 1 more Smart Citation

An Improved Model Predictive Control Method to Drive an Induction Motor Fed by Three-Level Diode-Clamped Indirect Matrix Converter

Farhadi

Akbari

Zakerian

et al. 2020

Int. j. eng. technol. innov.

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In this paper, an improved model predictive control method is proposed to drive an induction motor fed by a three-level matrix converter. The main objective of this paper is to present a novel method to increase the switching frequency at a constant sampling time. Also, it is analytically discussed that increasing the switching frequency not only can decrease the motor current ripples, but it can also significantly reduce its torque ripples. Finally, this study demonstrates that reducing the motor current ripple will improve the quality of the supply current. To be the accurate model and validate the motor drive system, a co-simulation method, which is a combination of FLUX and MATLAB software packages, is employed to find the simulation results. The findings indicate that the proposed method diminishes the THD of the supply current up to 26% approximately. Furthermore, increasing the switching frequency results in the torque ripple reduction by up to 10% almost.

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Section: Reducing Motor Torque Ripple and Supply Current Thdmentioning

confidence: 99%

“…On the other hand, finite control set model predictive control (FCS-MPC) has gained in popularity among many researchers [12][13][14][15][16][17]. This method is applicable in different types of linear and non-linear systems and has some advantages such as high-speed response and controlling multiple variables without creating extra loops.…”

Section: Introductionmentioning

confidence: 99%

An Improved Model Predictive Control Method to Drive an Induction Motor Fed by Three-Level Diode-Clamped Indirect Matrix Converter

Farhadi

Akbari

Zakerian

et al. 2020

Int. j. eng. technol. innov.

View full text Add to dashboard Cite

show abstract

“…In [39]- [46], the finite control model predictive control is applied to the grid-connected inverter, and the results show that MPC is superior to traditional controllers in terms of steady-state and transient response. In [41], a FCS-MPC is developed that does not require tuning and has low computational burden. [42] proposes a hybrid control strategy of FCS-MPC and deadbeat control to achieve a fixed frequency and robustness.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Finite Control Set Model Predictive Control Strategy of Microgrids for Unbalanced and Harmonic Power Management

et al. 2020

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In this paper, a modified decentralized finite control set model predictive control (FCS-MPC) scheme for the distributed energy resources (DERs) is proposed to improve the power management quality of the prosumers integrated microgrids under the condition of harmonic and unbalance loads. The proposed control strategy for the microgrids mainly consists of the power droop controller, the model predictive controller delay compensation, feedback correction and the unbalance compensation mechanism. The feedback correction method is used to correct the delay compensation, which effectively reduces the average switching frequency (ASF) and voltage total harmonic distortion (THD). By sharing the negative sequence reactive power of the microgrid, power distribution between the prosumers' DERs is improved. The DERs in the prosumers can be integrated without any communication wire. The transient response and robustness to parameter changes are far superior to hierarchical cascaded control. Moreover, the proposed control strategy can better suppress harmonic and reduce and share fundamental negative sequence reactive power under microgrid unbalance and nonlinear load conditions. Finally, the effectiveness of the proposed FCS-MPC control strategy is validated by time-domain simulation results and real-time tests with RT-Lab under the condition of unbalanced and nonlinear loads in the microgrids.INDEX TERMS Microgrids, finite control set (FCS), model predictive control (MPC), voltage source converter (VSC), unbalance and harmonics control.

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“…Different control algorithms proposed many researchers to satisfy the targeted control goals. A model predictive control (MPC) with a finite control set is reported in [28]. The system response time is reduced,as the cost function is designed only for current controller tracking.…”

Section: Introductionmentioning

confidence: 99%

Frame-Angle Controlled Wavelet Modulated Inverter and Self-Recurrent Wavelet Neural Network-Based Maximum Power Point Tracking for Wind Energy Conversion System

et al. 2020

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In this work, a new control methodology is proposed for Type-IV wind energy conversion system (WECS) using a self-recurrent wavelet neural network (SRWNN) control with a Vienna rectifier as the machine side converter (MSC). A SRWNN combines excellent dynamic properties of recurrent neural networks and the fast convergence speed of wavelet neural network. Hidden neurons of SRWNN contains local self-feedback loops, which provide the memory feature and the necessary information of past values of the signals, allowing it to track maximum power from WECS under varying wind speeds. The Vienna rectifier allows unity power factor operation to increase electrical efficiency. Frame angle-controlled wavelet modulation is proposed for the grid side converter (GSC). Wavelet modulated inverter produces output voltage fundamental components with higher magnitudes than those obtained from the pulse width modulated inverters. The non-linear load compensation and power quality enhancement are achieved by executing frame angle control for WM inverter. The overall system is modeled, and performance is verified in MATLAB Simulink. The hardware prototype is developed, and the switching pulses for the rectifier and inverter are generated using dSPACE1104 controller. The results prove that the system provides low harmonic content and high magnitude of the fundamental current component at the machine and grid sides and ensures maximum power operation at various wind speeds. INDEX TERMS Wind Energy Conversion System (WECS), Wavelet modulation (WM), Maximum power point tracking (MPPT), Self recurrent wavelet neural network (SRWNN)

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Simple Finite-Control-Set Model Predictive Control of Grid-Forming Inverters With LCL Filters

Cited by 43 publications

References 29 publications

An Improved Model Predictive Control Method to Drive an Induction Motor Fed by Three-Level Diode-Clamped Indirect Matrix Converter

An Improved Model Predictive Control Method to Drive an Induction Motor Fed by Three-Level Diode-Clamped Indirect Matrix Converter

Decentralized Finite Control Set Model Predictive Control Strategy of Microgrids for Unbalanced and Harmonic Power Management

Frame-Angle Controlled Wavelet Modulated Inverter and Self-Recurrent Wavelet Neural Network-Based Maximum Power Point Tracking for Wind Energy Conversion System

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