Experimental Validation of a Robust Continuous Nonlinear Model Predictive Control Based Grid-Interlinked Photovoltaic Inverter

This paper presents a robust continuous nonlinear model predictive control (CNMPC) for a grid-connected photovoltaic (PV) inverter system. The objective of the proposed approach is to control the power exchange between the grid and a PV system, while achieving unity power factor operation. As the continuous nonlinear MPC cannot completely remove the steady-state error in the presence of disturbances, the nonlinear disturbance observer-based control is adopted to estimate the offset caused by parametric uncertainties and external perturbation. The stability of the closed-loop system under both nonlinear predictive control and disturbance observer is ensured by convergence of the output-tracking error to the origin. The proposed control strategy is verified using a complete laboratory-scale PV test-bed system consisting of a PV emulator, a boost converter, and a grid-tied inverter. High performance with respect to dc-link voltage tracking, grid current control, disturbance rejection, and unity power factor operation has been demonstrated

Continuous Nonlinear Model Predictive Current Control of PWM AC/DC Rectifier

The present work applies a nonlinear model predictive current control (NLMPCC) approach to ac/dc pulse width modulation (PWM) rectifier. A cascade structure is used to regulate Dc-link voltage and grid currents. The outer loop objective is to regulate the Dc-link voltage to the desired value, providing the level of the required active power to be used with the reactive power to calculate the referencing current for the inner loop. In the inner loop, the proposed approach is considered. After that, the nonlinear model of the converter is developed, based on continuous minimization of predicted tracking errors, the voltage at the terminal of the converter is deduced. After that, a PWM block is used to generate gate signals. Simulation results are performed to illustrate the efficiency of the proposed control la

Discrete Model-Predictive-Control-Based Maximum Power Point Tracking for PV Systems:Overview and Evaluation

The main objective of this work is to provide an overview and evaluation of discrete model-predictive control (MPC)-based maximum power point tracking (MPPT) for photovoltaic systems. A large number of MPC-based MPPT methods have been recently introduced in the literature with very promising performance; however, an in-depth investigation and comparison of these methods has not been carried out yet. Therefore, this paper has set out to provide an in-depth analysis and evaluation of MPC-based MPPT methods applied to various common power converter topologies. The performance of MPC-based MPPT is directly linked with the converter topology, and it is also affected by the accurate determination of the converter parameters; sensitivity to converter parameter variations is also investigated. The static and dynamic performance of the trackers is assessed according to the EN 50530 standard, using detailed simulation models, and validated by experimental tests. The analysis in this work aims to present useful insight for practicing engineers and academic researchers when selecting the maximum power point tracker for their application.</p