Robust Predictive Control of Grid-Tied Modular Multilevel Converters for HVDC Systems With Virtual-Flux Based Online Inductance Estimation

Sun, Yuanxiang; Zhang, Zhenbin; Wang, Yongdu

Abstract

Direct model predictive control (DMPC) has become an effective control alternative for the grid-tied modular multilevel converter. However, classical DMPC of the grid-tied MMC relies on accurate system model. System parameter variations will deteriorate the control performances of power, grid current, and circulating current. Besides, the inherent fewer switching actions of DMPC will also lead to poor circulating current performance. To solve these issues, this work proposes a robust DMPC solution for the grid-tied MMC. Novelties lie in two aspects. First, a virtual-flux (VF) based online inductance estimator is proposed, which utilizes the VF estimation error caused by inductance deviation. It achieves fast and accurate estimation of AC equivalent inductance, and reduces the dependency on system parameters. Thereafter, we propose a hybrid predictive control frame with a simple proportional-resonant (PR) controller, which considerably suppresses the circulating current. Finally, experimental results verify the effectiveness of the proposed solution.

Más información

Título según WOS: Robust Predictive Control of Grid-Tied Modular Multilevel Converters for HVDC Systems With Virtual-Flux Based Online Inductance Estimation
Título de la Revista: IEEE TRANSACTIONS ON POWER DELIVERY
Volumen: 37
Número: 4
Editorial: IEEE
Fecha de publicación: 2022
Página de inicio: 3189
Página final: 3199
DOI:

10.1109/TPWRD.2021.3125036

Notas: ISI