Solid State Transformers (SST) are attracting considerable attention due to their great application potential in future smart grids. It is an essential technology capable of promoting the modernization of the electric power distribution system and it is considered a key element for interfacing future microgrid systems to medium voltage utility grids, allowing plug-and-play integration with multiple renewable energy sources, storage devices and DC power systems. Its main advantages in relation to conventional transformers are substantial reduction of volume and weight, fault isolation capability, voltage regulation, harmonic filtering, reactive power compensation and power factor correction. A three-stage modular cascaded topology has been considered as an adequate candidate for the SST implementation, consisting of multiple power modules with input series and output parallel connection. The modular structure presents many advantages, e.g., redundancy, flexibility, lower current harmonic content and voltage stress on the power switches, however component tolerances and mismatches between modules can lead to DC link voltage imbalance and unequal power sharing that can damage the solid state transformer. This paper proposes a decentralized strategy based on adaptive droop control capable of promoting voltage and power balance among modules of a modular cascaded SST, without relying on a communication network. The behavior of the proposed strategy is assessed through a MATLAB/Simulink simulation model of an 100 kVA SST and shows that power and voltage balance are attained through inner power distribution of the SST modules, being transparent to elements connected to the transformer input and output ports. Besides that, real-time simulation results are presented to validate the proposed control strategies. The performance of embedded algorithms is evaluated by the implementation of the SST in a real-time simulation hardware, using a Digital Signal Processor (DSP) and high level programming.


  • The electricity consumption growth and environmental concerns favor the proliferation of renewable sources and distributed generation (DG) integration into the grid [1]

  • In order to solve that issue, it is proposed that the droop virtual resistance should be a function of the instantaneous high voltage DC link (HVDC) voltage and power flow of the module, the latter defined by the low voltage DC bus (LVDC) output current direction, i.e., the droop resistance value should be autonomously adapted according to the HVDC link voltage level, : rd = rd0 f, (3)

  • The results show that with the performance of the adaptive droop function, initially the Dual Active Bridge (DAB) output current are unbalanced causing a change in the trajectory of the HVDC voltages, which gradually converges to the reference value, which occurs at t ≈ 3 s

Read more



The electricity consumption growth and environmental concerns favor the proliferation of renewable sources and distributed generation (DG) integration into the grid [1]. For microgrid applications, the three-stage topology, as shown, is more attractive In this structure, the interface with the medium voltage bus is performed by an active front-end rectifier (AFE), which regulates the high voltage DC link (HVDC). One of the main limitations regarding the selection of power converter topologies for the implementation of each SST stage is in the rectifier, which usually is coupled to a medium voltage grid with line voltage of about 10 kV. In this case, the voltage level of the HVDC link exceeds the blocking capacity offered by current semiconductor devices and imposes severe challenges in the construction of high frequency transformers.

60 Hz module 1
Modular SST Topology Description
Three-Phase Modular Cascaded H-Bridge Rectifier
Isolated Bidirectional DC-DC Converter
Voltage and Power Balancing Strategy
Hardware in the Loop Simulation
Software Simulation and HIL Experimental Results
Software Simulation Results
HIL Experimental Results
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call