Multi-port solid-state transformer (SST) characterized by high scalability is expected to be widely used in AC/DC hybrid microgrid. However, the DC bus voltage deviation and dynamic response speed are two key issues in its application. Therefore, a model predictive direct power control (MPDPC) of the three-port SST (TPSST) is proposed. Compared with the traditional PI-based method, the oscillation of the DC bus voltage is inhibited, and the steady-state performance is improved with the MPDPC method. Moreover, a direct power path is incorporated into the control system in order to integrate the rectifier and dual active bridge (DAB) stage. This power path delivers the power required by the load to the DAB stage and the rectifier stage for power control, thereby improving the dynamic response of the system in the process. Besides, since the MPDPC strategy is a control scheme for the whole system, the design of the control system is simplified. Finally, a low power prototype has been built and tested, and the experimental comparison with the traditional voltage control (TVC) and model predictive voltage control (MPVC) method verifies the efficiency improvement of the proposed control strategy.

In order to cope with the energy crisis, the concept of an energy internet (EI) has been proposed as a novel energy structure with high efficiency which allows full play to the advantages of multi-energy coupling. In order to adapt to the multi-energy coupled energy structure and achieve flexible conversion and interaction of multi-energy, the concept of energy routing centers (ERCs) is proposed. A two-layered structure of an ERC is established. Multi-energy conversion devices and connection ports with monitoring functions are integrated in the physical layer which allows multi-energy flow with high flexibility. As for the EI with several ERCs connected to each other, energy flows among them are managed by an energy routing controller located in the information layer. In order to improve the efficiency and reduce the operating cost and environmental cost of the proposed EI, an optimal multi-energy management-based energy routing design problem is researched. Specifically, the voltages of the ERC ports are managed to regulate the power flow on the connection lines and are restricted on account of security operations. An artificial neural network (ANN)-based reinforcement learning algorithm was proposed to manage the optimal energy routing path. Simulations were done to verify the effectiveness of the proposed method.

Three-phase unbalance issue can cause adverse impacts on the power quality of the solid-state transformer (SST) based AC/DC hybrid microgrid. In this paper, an unbalanced power control strategy for cascaded dual active bridge (DAB) converter is proposed. With the strategy, the transmitted power of each DAB module in each phase is evenly distributed in terms of the three-phase unbalance degree of the threephase AC grid. Thus, the idea of unequal power sharing in cascaded DAB can be applied to mitigate the three-phase unbalance from the perspective of power control. Moreover, this paper proposed a three-phase unbalance power mitigation algorithm based on the unbalanced power control strategy for the cascaded DAB. The proposed strategy can help the SST realize the function of mitigating three-phase unbalance when it transmits energy to the DC microgrid. Thus, the proposed control strategy can mitigate the threephase unbalance on the premise that the power demand of the system is met. Finally, the simulations and the experiment results have verified the effectiveness and correctness of the proposed control method.

Due to the uncertainty of the power load and the randomness of distributed generations, low-voltage direct current (LVDC) bus voltage fluctuation will greatly affect the safety of an energy router-enabled direct current (DC) microgrid. In this paper, a power feedforward control strategy based on a dual active bridge (DAB) DC/DC converter in an energy router-based DC Microgrid is proposed. Based on this strategy, the LVDC bus voltage is controlled by virtual inertia control of the DC microgrid, instead of by the DAB converter. Thus, two benefits of the proposed strategy can be achieved: the power feedforward control can be realized, to mitigate the voltage fluctuation range of the LVDC bus; and the modulation algorithm in the DAB converter can be simplified. Experimental results verify the correctness and effectiveness of the proposed control method.

Owing to the intermittent output power and variable load variability of distributed generation (DG), voltage fluctuation and power mismatch tend to occur during AC/DC hybrid microgrid operation with power electronic transformers (PET). Therefore, a distributed energy coordination strategy is proposed in this paper. This strategy can coordinate the power exchange between PET, AC microgrid, DC microgrid and energy storage to effectively suppress the fluctuation of DC bus voltage. At the same time, the proposed hybrid mode control method, only with on local information, can ensure the full utilization of all subsystems and buffer the energy fluctuations of hybrid microgrids. The simulation results show that the proposed control strategy can accurately control the bidirectional flow of power between the PET interfaces and regulate the power distribution between the main network, the AC microgrid and the DC microgrid to achieve the stable operation of the AC/DC hybrid microgrid.