At present, passive balancing methods dominate energy storage applications, however, they suffer from a long balancing duration. In this article, we took advantage of a modular architecture, where several modular power converters replace a central dc–dc converter for fast charging and balancing of a supercapacitor stack. A strategy has been proposed to control how power is shared among the converters during the charging period in order to balance the supercapacitors. However, some converters enter control saturation due to voltage differences between supercapacitors caused by their nonuniform conditions and characteristics. The originality of this article lies in taking into account the saturation by modifying an energy-based strategy to correct the power shares and make balancing the supercapacitors possible. Simulation and experimental case studies were used to demonstrate the strategy's performance and limitations.

The Philippines, being a tropical country, has a high photovoltaic (PV) energy generation potential that can help meet demand due to impending power supply shortage in the coming years. One factor that limits solar PV generation is nonuniform illumination or partial shading. Partial shading causes voltage and current mismatch which affect the performance of PV arrays. Partially shaded PV systems cannot operate at maximum efficiency because of shadows cast by the surrounding structures, foliage and cloud cover. In this study, the researchers observed the effects of partial shading on the voltage, current and power output of the total cross-tied (TCT) array configuration using 16 shading patterns. Results show that the TCT configuration has the ability to balance out the effects of uneven irradiance on the PV modules. This results in higher power output. However, this effect optimizes the power output most if shaded modules complete columns. Such cases minimize current mismatch among the rows in the array.

The need for energy, especially energy from renewable sources, to be distributed and flexible has driven the development of microgrids in recent years. They have been a key technology in achieving the sustainable development goal for energy particularly in rural off-grid areas. However, safe and reliable operation of microgrids remains a challenge given the difficulty in maintaining the physical system due to the lack of technical know-how in the rural localities where they are installed. A monitoring system with power forecasting capability is proposed in this article to aid in the safe and reliable operation of microgrids. The monitoring system features galvanic isolation in both the ac and dc measurement modules protecting users and the monitoring system itself from the high currents of the microgrid power system. The measurements can then be fed into a machine learning algorithm to forecast the power output of the microgrid. Experimental data were presented to validate the measurements and forecasts of the monitoring system. Users can monitor and forecast the power output of a microgrid and conduct maintenance if significant deviations are observed between forecasts and measurements.

Amélioration de la durée de vie des systèmes de stockage d’énergie électrique par optimisation des convertisseurs d’énergie modulaires associés: L’hétérogénéité des caractéristiques « constructeur » des dispositifs de stockage d’énergie tels que les supercondensateurs et leurs conditions environnementales affectent leurs performances et entraînent un vieillissement déséquilibré. Les circuits d’équilibrage conventionnels reposent sur l’équilibrage des tensions ou des états de charge (SoC) des cellules. Dans ce travail, nous proposons plutôt d’équilibrer les états de santé (SoH) des cellules pour optimiser la durée de vie du système de stockage d’énergie électrique. Des convertisseurs statiques d’énergie modulaires sont utilisés pour interfacer les supercondensateurs avec le système de charge/décharge et sont commandés de façon à ce que les vieillissements des supercondensateurs soient homogènes. Cela est rendu possible par une méthode d’allocation de commande qui utilise une matrice de pondération basée sur la durée de vie utile restante des supercondensateurs comme indicateur d’état de santé. Pour deux applications, nous avons simulé des équipements complets par utilisation de modèles électrothermiques de supercondensateurs et de modèles des convertisseurs modulaires contrôlés par un module d’allocation de commande. Les simulations ont été validées par des essais expérimentaux. Il est montré que l’utilisation de convertisseurs modulaires associés à une méthode d’allocation de commande optimisant l’état de santé des supercondensateurs prolonge grandement leur durée de vie par rapport à l’utilisation d’un simple convertisseur d’énergie avec circuit d’équilibrage classique.

The growing adoption of electric vehicles (EVs) and the increasing need for coordinated charging and energy management have highlighted the importance of vehicle-to-everything (V2X) technologies within battery management systems (BMSs). However, existing studies often treat EVs as idealized storage systems, overlooking battery and BMS-related operational constraints, and typically analyze driving, charging, and bidirectional energy exchange in isolation, limiting realistic, end-to-end evaluation of daily operation scenarios. This paper addresses these gaps by analyzing how advanced, BMS-integrated V2X capabilities can be deployed in real-world EV operation, focusing on battery utilization, operational performance, and system-level energy interactions. A unified, scenario-based methodology combines mobility demand, AC/DC charging behavior, and bidirectional V2X services within a single daily operational framework. Representative use cases for both passenger EVs and electric light commercial vehicles (eLCVs) are developed to capture realistic driving patterns, environmental conditions, and energy exchange scenarios. The results indicate that V2X operation can provide substantial gross economic value in the investigated scenarios. For the eLCV cases, the estimated increase in equivalent full cycle (EFC) throughput rate ranges from approximately 14.3% to 30.3%, while combined summer–winter cumulative avoided electricity purchase cost reaches approximately EUR 4033 for the higher-power charging strategy, equivalent to 57.0% of the adopted battery cost reference. The analysis also highlights the strong influence of ambient temperature and usage patterns on energy consumption, charging strategies, and overall system performance. Overall, this work provides a holistic and practical evaluation framework for V2X-enabled BMS operation, demonstrating its potential to improve grid support, enhance energy efficiency, and support sustainable EV integration while balancing economic and battery-lifetime trade-offs.