Modelling, Control System Design and Comparison of Star and Delta Connected Solid-State Transformers

Modelling, Control System Design and Comparison of Star and Delta Connected Solid-State Transformers: A study of three MVAC to LVDC Modular Multilevel Converter based Solid State Transformers for Ultra-Fast EV Charging Applications

Grootes, Casper (TU Delft Electrical Engineering, Mathematics and Computer Science)

Qin, Z. (mentor)
Bauer, P. (graduation committee)
Qin, Z. (graduation committee)
Manganiello, P. (graduation committee)

Delft University of Technology

Delft University of Technology

Electrical Engineering | Electrical Power Engineering

2023-11-28

With an increase in higher power (ultra) fast EV charging stations and a new EU law for mandatory deployments of EV charging stations, an optimal MVAC grid connection for these charging stations is desired. Considering this connection, the use of a solid-state transformer (SST) performs better in terms of weight, size and efficiency with a similar cost, compared to the conventional low-frequency transformer (LFT) for MVAC to LVDC conversions. This study compares three MMC-based SST topologies where a DAB is connected to each submodule: Double-Star, Single-Star and Single-Delta. The cost of an MMC mainly depends upon the required energy storage and the switch stress. The topologies are therefore mainly compared based on these parameters, but other parameters are considered as well. With the goal of minimising the required energy storage, an 80% MMC energy storage reduction compared to the theoretical minimum requirement has been achieved by control.

A novel mathematical model has been proposed for each SST; this uses an MMC model based on the switching function and a DAB model based on the single phase-shift control. The model has been implemented in simulation and proven to accurately determine the average behaviour of the SST while significantly reducing the simulation complexity and time. This model helps to understand the SST's behaviour and furthermore allows for control system tuning both manually and automatically using the Genetic Algorithm.

Three different control systems have been designed. Control system A, where the MMC current is controlled by the average submodule voltage and the DAB controls the LVDC bus voltage. Control system B, where the DAB controls each individual submodule voltage and the MMC current is controlled by the LVDC bus voltage. Control system C, which is similar to control system B, but uses a stable DC voltage source on the LVDC bus and a set MMC current. An improved DAB control has been designed for control systems B and C, resulting in control systems B* and C*. This control is based on the use of a current feedforward and a PI controller combined with the inverted equations of the DAB model. The three topologies have been successfully simulated with this improved DAB control system using an 80% MMC energy storage reduction compared to the theoretical minimum requirement. This improves the general behaviour and significantly reduces the cost of the SST. The improved DAB control system has been tested using a hardware DAB with a current step input, which has shown that the new control system performs better in voltage peak reduction compared to PI control.

Out of the three topologies, the Single-Star topology performs the best. It has the lowest energy storage requirement and switch stress. Furthermore, its behaviour lies the closest to the ideal model. The best result for the Single-Star SST is achieved with the proposed improved DAB control, which leads to the lowest energy storage requirement, switch stress, THD, submodule voltage deviations and settling time. Out of these two control systems, C* performs the best.

MMC
Modular multilevel converter
SST
Solid State Transformer
EV charging
Dual Active Bridge
DAB
Modelling and simulation
Control system

http://resolver.tudelft.nl/uuid:a101e2cf-6d0a-4b38-aad8-b1b3f9dad38f

2025-11-28

Student theses

master thesis

© 2023 Casper Grootes