DC current injection is a common problem in grid-tied inverters and it is especially emphasized when current transformers are employed to sense the current. Although the dc current elimination is already addressed for linear controllers, it is not faced for model predictive control. This manuscript proposes a dc current elimination strategy for cascaded H-bridge (CHB) static synchronous compensators controlled by finite control set model predictive control (FCS-MPC). In addition to the two optimization layers of typical FCS-MPC, this article proposes using a third optimization layer to balance the voltages of the clusters. This article demonstrates that the dc current is suppressed by minimizing the imbalance among the clusters through the common-mode voltage. The algorithm is simple to implement and the ac output current is not affected. Validation is carried out with a five-level CHB-STATCOM, and a classical approach is compared.

DC Current Suppression in CHB-STATCOM With Model Predictive Control Employing Current Transformers

Simonetti F.
;
Mohamadian S.;Buccella C.;Cecati C.
2024-01-01

Abstract

DC current injection is a common problem in grid-tied inverters and it is especially emphasized when current transformers are employed to sense the current. Although the dc current elimination is already addressed for linear controllers, it is not faced for model predictive control. This manuscript proposes a dc current elimination strategy for cascaded H-bridge (CHB) static synchronous compensators controlled by finite control set model predictive control (FCS-MPC). In addition to the two optimization layers of typical FCS-MPC, this article proposes using a third optimization layer to balance the voltages of the clusters. This article demonstrates that the dc current is suppressed by minimizing the imbalance among the clusters through the common-mode voltage. The algorithm is simple to implement and the ac output current is not affected. Validation is carried out with a five-level CHB-STATCOM, and a classical approach is compared.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/229340
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