Search

This paper presents a different Finite Control Set – Model Predictive Control (FCS-MPC) for grid-connected three-phase bidirectional power inverters. These are typically used in dc or ac renewable-based microgrids (MGs), where bidirectional operation and fast dynamic response is required. The bidirectional grid-connected inverters are an essential part of MG, which inject energy into the ac grid or demand energy from it. The dynamic behavior of the system is a major concern since the current can suddenly change depending on the hierarchical controller. This paper proposes a different cost function using sliding mode theory, which offers a good dynamic response, reduced computational burden, and a parameter-free control model. The operation principle of the proposed controller is given and evaluated using a Hardware-In-the-Loop (HIL) system, but also experimentally with a 1kW laboratory prototype. The final results demonstrate the advantages of using this approach in grid-connected three-phase bidirectional power inverters in terms of dynamic response and reduced computational burden, making this solution technically attractive and viable. [ABSTRACT FROM AUTHOR]

Conventional model predictive control (MPC) for three-level active neutral point clamped converter (ANPC) utilizes weighting factors to achieve the optimal control of multiple control objectives in a single cost function. However, the selection of these weighting factors has an impact on the performance of the controlled objectives significantly. Tuning of weighting factors is usually tedious and lacks theoretical background. Moreover, the predictive and evaluation process for multiple objectives optimization have to be carried out by enumerating all admissible switching states within one loop. To simplify the complexity of this process and eliminate the effect of weighting factors, this paper proposes a cascaded predictive control scheme for a 3L-ANPC inverter fed induction machine (IM) drive. With the proposed approach, three separate cost functions for three control objectives, stator flux vector, neutral point voltage and device loss distribution are evaluated in a cascaded way, so that the optimization of these control objectives is performed independently. A 3L-ANPC inverter driven IM drive is studied in this paper to verify the effectiveness of the proposed algorithm. Experimental results in different operating conditions confirm that the proposed method achieves satisfactory steady-state and transient performances comparable to the conventional predictive control approach. The weighting factors used in the conventional method are eliminated and the computational effort is reduced by 68% compared to the conventional method without any sacrifice in the drive performance. [ABSTRACT FROM AUTHOR]

The implementation of finite-control-set model predictive control (FCS-MPC) in voltage source inverters (VSIs) can make the system suffer from poor current harmonics performance, which may complicate the design of the required AC filter. To overcome this shortcoming, a carrier-based modulated model predictive control (CB-MMPC) strategy is proposed in this paper. This method enables the utilization of existing PWM modulation techniques with FCS-MPC, where a modulation waveform with zero-sequence signal injection is generated and compared to a triangular carrier wave, while optimizing the selection of the switching states. As it is shown, the studied CB-MMPC strategy not only considerably improves the current total harmonic distortion (THD) but also attains the performance of fast current dynamic response and robustness as the traditional FCS-MPC. Herein, the detailed implementation of the CB-MMPC control strategy is given, while considering its application to the current feedback control loop of a three-phase three-wire two-level VSI modulated at constant switching frequency. Finally, PLECS circuit simulation and a 3-kW VSI prototype are used to verify the superiority and the effectiveness of the presented CB-MMPC strategy. This is also benchmarked to the FCS-MPC and dead-beat based controllers. [ABSTRACT FROM AUTHOR]