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The multiport power router (PR) is becoming an indispensable part of modern power systems. However, in the case of severe three-phase voltage imbalance and grid voltage distortion, it becomes challenging to simultaneously suppress harmonics on both the ac side and the dc side merely by relying on the grid-tied port. Consequently, this article proposes a multiport passivity-based collaborative control (PBCC) scheme considering simultaneous suppression of ac and dc harmonics, takes the grid-connected port (GTP), energy storage port (ESP), and ac load port of PR as the research objects. First, only through the collaboration of GTP and ESP can the multiple goals of mitigating grid-side current harmonics, compensating for current imbalances, and eliminating dc-bus voltage ripple simultaneously be achieved. Therefore, the hybrid passivity-based control (PBC) laws for the GTP and ESP are reconstructed separately based on internal model control and resonance control. Then, a dc bus power compensation controller is also introduced, based on the collaboration of the GTP and ESP, which is capable of adaptively compensating for dc power based on varying grid voltage drop depths to suppress grid-side over-current. In addition, the impedance stability analysis of GTP, ESP, and dc bus are developed to verify the impedance matching between port–port and port–bus under the proposed PBCC scheme. Finally, a three-port-based PR prototype was built and tested, and the results proved that the proposed PBCC method can decouple the ac and dc harmonics of the PR system, exhibiting strong robustness and anti-interference ability compared with the existing control methods.

The ${{LLC}}$ converter-based dc transformer is popular for its stiff voltage gain, very high efficiency, and simple control. To avoid excessive start-up inrush current and hardware overdesign, the fixed-frequency variable duty-cycle soft start-up strategy is often adopted. However, in this conventional strategy, the optimal current-limiting curve (OCC) is derived by the challenging numerical model iterative algorithm, which is difficult to model, calculate online, and adapt to different operating conditions. To solve this problem, a closed-form OCC (COCC)-based soft start-up strategy is proposed. The COCC is derived by state-trajectory analysis and can be quickly calculated through the simple closed-form equation, providing greater practicality and flexibility while accurately maximizing the utilization of the allowable peak current. Furthermore, the closed-form equation makes it possible to estimate the start-up capability under the variable duty-cycle strategy. The calculation method of the maximum allowable start-up load is proposed, offering an important basis for the design of distribution system restoration schemes. Finally, a 50-kW dc transformer is built to verify the effectiveness of the proposed strategy under various conditions.

This article proposed a generalized extended state observer (GESO)-based data-driven predictive control (DDPC) strategy with multivector for three-level inverters, which is thoroughly independent of system parameters while obtaining a satisfactory multiobjective control performance considering common-mode voltage (CMV) reduction. In the proposed strategy, the predictive dynamic of output current is achieved by DDPC, and only the system input and output knowledge is needed. Meanwhile, due to the complex dynamics and difficulty of identifying by DDPC, the system uncertainties can still degrade the control performance if not solved. In this regard, the GESO is introduced to estimate the unknown uncertainties as a new extended state, which is further compensated in the control law, enabling a significant robust performance enhancement. Then, aiming to reduce the CMV, virtual vectors are constructed into the candidate vectors to replace the small vectors with high CMV magnitude. Moreover, three optimal vectors are selected to synthesize the reference voltage, where the current harmonic and the neutral-point (NP) imbalance are simultaneously suppressed. Finally, the validity of the proposed strategy is proved by simulation and experiments on a three-level T-type inverter (3LT2I).

For three-level T-type inverter (3LT2I), the unbalanced neutral-point (NP) voltage is required in some photovoltaic (PV) generation systems. Meanwhile, the unbalanced NP voltage easily leads to the fault of power switches. However, the existing fault-tolerant control (FTC) strategies are only capable of the balanced NP voltage conditions. In order to simultaneously realize the FTC and unbalanced NP voltage control (UNPVC), a half-cycle FTC (HC-FTC) strategy and a whole cycle FTC (WC-FTC) strategy are proposed in this article. The carrier is modified to avoid using the impossible switching states and realize FTC. Meanwhile, the mathematical models of NP current under both normal and fault conditions are established based on volt-second balance principle, and thereby, the zero-sequence component (ZSC) derived by the model can be used to realize the UNPVC whether the switch is fault or not. In addition, the ZSC is selected in detail to improve the NP voltage control ability in HC-FTC. Furthermore, the application range of HC-FTC is obtained, and the WC-FTC with wider application range is proposed. The two proposed strategies can be selected according to the requirements. Finally, experimental results validate the effectiveness of the proposed strategies.

This article proposes a double vector model predictive control (MPC) method for the $LC$ filtered three-level T-type inverter to gain superior voltage performance, which is current sensorless and computationally efficient. In the proposed scheme, inverter voltage increment is induced in the multiobjectives cost function, and the desired voltage is derived based on the simplified discrete model, which optimizes the output voltage control performance. The prepositive prediction calculation is shifted out from the evaluation circle, and the computation is lessened simultaneously. Then, aiming to estimate the capacitor current of the simplified discrete model with voltage feedback only, the strong-tracking Kalman filter-based observer is designed, which gets rid of the dependence on current sensors and lowers hardware cost. Furthermore, to improve the control accuracy of tracking the desired voltage, a two-layer decision algorithm based on the search tree is developed to find the optimal double vector easily, which obtains a low-complexity selection process using the univariate cost function. Finally, the simulation and experimental results are given to demonstrate the effectiveness of the theoretical analyses and the proposed method.

Paralleled three-level T-type inverters face the unavoidable pitfall of the zero-sequence circulating current (ZSCC). Although the conventional model predictive control (MPC) could eliminate the ZSCC, the control error occurs inevitably since only one vector is adopted in each sampling period, which decreases the current control performance. Thus, simultaneous ZSCC elimination and accurate current tracking become imperative to the inverter using MPC. This article proposes a multivector MPC to eliminate the ZSCC and reduce the current distortion without the weighting factor. As the common-mode voltage (CMV) and neutral point (NP) voltage are the main factors that induce the ZSCC, the virtual vector with zero-average CMV is constructed to eliminate the ZSCC. Meanwhile, the small vector is introduced to improve the NP voltage control capability. In addition, to enhance the current accuracy and reduce the ZSCC ripple, three optimal vectors are adopted to synthesize desired voltage. Moreover, the multivector preselection algorithm is proposed to reduce the computational complexity of implementation process. Finally, the effectiveness of the proposed method is verified with comprehensive simulation and experimental results.

The hybrid modular dc transformer (HMDCT) combining the series resonant dual active bridge (SR-DAB) and phase shift dual active bridge (PS-DAB) has the advantages of high efficiency and bidirectional power regulation. However, due to the unregulated SR-DAB resonant tank inertia and limited PS-DAB output power, the dynamic response of HMDCT is slower than the pure PS-DAB-based DCT, which could lead to a larger output overshoot. To address the problems, first, a novel trajectory-switching-modulation (TSM) method is proposed to control the SR-DAB resonant tank to track the desired state trajectory rapidly using SR-DAB switch states. Compared with the conventional $LLC$ trajectory control, TSM is more suitable for the SR-DAB in the bidirectional HMDCT because TSM is available under bidirectional power flow without changing the topology or increasing the magnetizing losses. Then, a TSM-based fast power transient control strategy (TSM-FPTC) is proposed to improve the bidirectional HMDCT dynamic performance by controlling the PS-DAB and SR-DAB simultaneously. Besides, PS-DAB current stress can also be reduced during the load transients. Experimental results show that the proposed strategy has better dynamic performance than the classic proportional–integral (PI) feedforward-based strategy.