Model Predictive Control for Solid State Transformers: Advances and Trends

Tiago Oliveira, André Mendes () and Luís Caseiro
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Tiago Oliveira: Department of Electrical and Computer Engineering (DEEC), University of Coimbra—Pole 2, P-3030-290 Coimbra, Portugal
André Mendes: Department of Electrical and Computer Engineering (DEEC), University of Coimbra—Pole 2, P-3030-290 Coimbra, Portugal
Luís Caseiro: Instituto de Telecomunicações, University of Coimbra—Pole 2, P-3030-290 Coimbra, Portugal

Energies, 2022, vol. 15, issue 22, 1-27

Abstract: Due to its high functionality, the solid state transformer (SST) represents an emerging technology with huge potential to replace the conventional low-frequency transformer (LFT) in a wide range of applications, including railway traction, smart grids, and others. On the other hand, model predictive control (MPC) has proven to be a highly promising control approach for several power electronics systems, especially those based on multiple power converters. Considering these facts, over recent years, different MPC techniques have been proposed for different types of SSTs. In addition to that, numerous MPC strategies have also been investigated for various power converters topologies that can be used in SSTs. However, a paper summarizing and discussing MPC strategies in the framework of SSTs has not yet been proposed in the literature, being the main goal of this work. In this paper, all the existing MPC techniques in complete SST topologies will be presented and discussed. In addition, for the sake of the example, an overview of MPC strategies in converter topologies typically used in SSTs will also be presented.

Keywords: model predictive control; digital control; solid state transformer; power electronics transformer; energy router; multi-port system; power quality (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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