Thesis Defence: Numerically Efficient and Accurate Modeling of a Multi-Active-Bridge Solid-State Transformer for Accelerated Electromagnetic Transient Simulation

Kuizhang Gao, supervised by Dr. Liwei Wang, will defend their thesis titled “Numerically Efficient and Accurate Modeling of a Multi-Active-Bridge Solid-State Transformer for Accelerated Electromagnetic Transient Simulation” in partial fulfillment of the requirements for the degree of Master of Applied Science in Electrical Engineering.
An abstract for Kuizhang Gao’s thesis is included below.
Defences are open to all members of the campus community as well as the general public. Please email [email protected] to receive the Zoom link for this defence.
Abstract
The development of modern power systems, including distribution networks, electric vehicle (EV) fast charging, and energy storage systems, has led to increasing demand for flexible, efficient, and high-performance power conversion technologies. Solid-state transformers (SSTs) have emerged as a promising solution due to their high-power density, modular structure, bidirectional power flow capability, and ability to operate at high frequencies. However, the increasing system complexity and large number of switching devices make accurate and efficient electromagnetic transient (EMT) simulation computationally expensive.
This thesis presents a numerically efficient and accurate modelling framework for multi-winding solid-state transformers (SSTs) for electromagnetic transient (EMT) type simulation. Due to the large number of switching devices and complex converter structures, conventional detailed models suffer from high computational cost. To address this issue, a switching-function-based detailed equivalent model (SFB-DEM) is developed to model the converter using controlled voltage sources, enabling decoupling through the DC-link capacitors. An EMT-based implementation is further formulated using forward Euler (FE) and backward Euler (BE) discretization. Moreover, a switching interpolation technique is incorporated to improve the accuracy under fixed-time-step EMT simulation.
The proposed equivalent model is validated through comprehensive case studies, including accuracy evaluation under different simulation time steps and computational efficiency analysis with increasing submodule numbers, and fault-condition simulation. The results demonstrate that the proposed SFB-DEM achieves well-matched simulation results with the reference model while significantly reducing simulation time and improving scalability. The switching interpolation technique significantly enhances accuracy for large time-step simulations.