A cascaded multilevel converter (CMC) with hybrid energy storage system (HESS) offers a promising solution for high-voltage and high-power hybrid dc-ac systems. However, asymmetric power distribution (APD) across different energy storage systems (ESSs) presents a challenge. This article proposes a dynamic power management strategy for CMC-based HESS, featuring dynamic power sharing to optimize power allocation between batteries and supercapacitors (SCs) based on their distinct response times. In addition, battery state-of-charge (SOC) balancing and SC energy management strategies are introduced to maintain optimal energy distribution and ensure long-term operation. The approach enhances overall system performance by fully leveraging the complementary strengths of batteries and SCs. The effectiveness of this strategy is validated through simulations and experiments, confirming its scalability and adaptability to various CMC-based HESS configurations.

With increasing renewable penetration and declining grid strength, power electronic converters must ensure reliable operation under adverse conditions. This paper presents a unified control strategy that embeds nonlinear oscillator-based voltage synthesis into modular multilevel converters (MMCs) to enable robust grid-forming functionality. The unified Virtual Oscillator Control (uVOC) is integrated with circulating current suppression and voltage modulation coordination, enabling autonomous voltage regulation and fault-limited behavior without the use of phase-locked loops. Simulation results validate the proposed method under weak grid, disturbance, and islanded scenarios. Fault ride-through (FRT) capabilities are demonstrated in compliance with IEEE 1547 standards, confirming improved transient performance and system resilience.

Three-phase inverters have many applications, including motor drive and grid converter systems. Grid connected inverters, as interface for renewable energy sources integration, are key elements of modern grids. While the inverter voltage and current regulation is performed using a digitally-controlled voltage source inverter (VSI), a control related delay is often not completely analysed in the control design. This results in an inaccurate inverter model and degraded performance. In this paper, a discrete-time inverter model with delayed control input is obtained. A linear-quadratic regulator (LQR) based current loop and integral control voltage loop are designed, achieving stable converter operation. Simulation results validate the effectiveness of the proposed model and controller design guideline for guaranteed stability. Experimental results demonstrate the applicability of the proposed model to a real-world scenario.

The large integration of modular multilevel converters (MMC) has introduced stability issues. The impedance-based stability analysis method is widely adopted, where the impedance model can be directly achieved at the terminals through nonintrusive measurement, which facilitates the black-box stability analysis of the MMC-grid interaction system. Yet, due to the limited impedance data amount in the practical application of online impedance identification, the accuracy of the identified model stability analysis cannot be guaranteed with existing methods in variable operating point scenarios. This article proposes a transfer learning based online impedance identification for MMC to address this research gap. The two-phase online impedance identification method is developed where the physical model of MMC in the offline phase is utilized to facilitate the online impedance identification. The proposed method can significantly reduce the data amount requirement in online impedance identification and achieve online stability analysis of the MMC system. The case studies confirm the effectiveness of the proposed method.