Modal analysis is essential for evaluating the small-signal stability of power systems by identifying poorly damped oscillatory modes. This paper introduces an automated framework for residue computation directly within DIgSILENT PowerFactory, exploiting its internal state-space matrices and scripting environment. Unlike traditional approaches that rely on external data processing, the proposed method enables a fully integrated, repeatable, and scalable workflow for residue-guided control design. The framework automatically extracts and computes modal residues, quantifying both controllability and observability to identify the most effective control locations. Its application to benchmark systems demonstrates accurate detection of critical modes and effective damping enhancement through residue-based tuning. This integration of automated residue analysis into PowerFactory bridges theoretical modal analysis with practical implementation, offering a novel and efficient tool for oscillatory stability assessment in modern power grids.

La integración de la movilidad eléctrica es una realidad en el mundo actual, las políticas gubernamentales se enfocan cada vez más en incentivar el uso de vehículos eléctricos (VE) particulares, pero, principalmente en reemplazar la movilidad pública convencional por el uso de buses eléctricos. Una adecuada gestión energética de los sistemas de buses eléctricos debe optimizar el uso de recursos, prolongando la vida útil de las unidades de transporte, estaciones de carga y brindando siempre un servicio de calidad a sus usuarios. El desempeño del sistema de transporte mediante VE depende de diversas variables determinísticas y estocásticas que necesitan ser debidamente simuladas a fin de analizar su comportamiento, lo más cercano a las condiciones reales. En el presente trabajo, mediante la aplicación del software SUMO (Simulation of Urban Mobility), se ha implementado un modelo para el análisis energético de VE y se lo ha aplicado en rutas de transporte público en Quito-Ecuador. A partir de las simulaciones realizadas se ha estimado el consumo energético y se ha efectuado un análisis de sensibilidad del consumo energético de las unidades de buses eléctricos ante variaciones de parámetros relevantes en la gestión energética de sistemas de transporte público. Para el caso de estudio se comprueba la reducción de la autonomía del bus eléctrico en 27% de acuerdo con la información del fabricante. El análisis del desempeño energético realizado bajo diversos escenarios de tráfico permitirá en futuros trabajos optimizar la operación de los sistemas de transporte público eléctrico, considerando niveles de tráfico, flujo vehicular variable y pronunciados desniveles en su relieve.

Lithium-ion batteries have become a beacon in modern energy storage, powering from small electronic devices to electric vehicles (EVs) and critical medical equipment. Since their commercial introduction in the 1990s, significant advancements in materials science and engineering have enhanced battery capacity, safety, and lifespan. However, the complexity of lithium-ion battery dynamics has necessitated the development of advanced charging and control strategies to optimize performance, safety, and longevity. This work proposes a comparative analysis of three advanced control methods for lithium-ion battery charging: reinforcement learning, fuzzy logic, and classic proportional–integral–derivative (PID) control. Traditional charging methods often fail to address the complexities of battery dynamics, leading to suboptimal performance. Our study evaluates these intelligent control strategies using MATLAB-Simulink simulations to enhance charging efficiency, speed, and battery lifespan. The findings indicate that reinforcement learning offers superior adaptability, fuzzy logic provides robust handling of nonlinearity, and PID control ensures reliable performance with minimal computational resources.

Electric mobility is one of the main pillars of the global energy transition towards a more sustainable and environmentally responsible model. Greenhouse gas emissions could be drastically reduced with electric mobility massification. Public transport systems represent the first step of this massification due to government policies, but these electromobility projects should optimize their resources to be cost-effective. Furthermore, the implementation of charging stations could cause negative impacts on electrical distribution networks, which should be evaluated beforehand for the adequate planning of power grids. A methodology was developed and implemented herein for the technical and economic evaluation of electric bus-based transport systems.

Hybrid transmission corridors combining overhead lines and underground cables introduce impedance discontinuities that significantly modify electromagnetic transient behavior. These discontinuities generate traveling-wave reflections, waveform distortions, and high-frequency components at relay measurement locations during the first microseconds following disturbance inception. This paper presents a waveform-level electromagnetic transient (EMT) analysis of overhead–cable transition effects using detailed EMTP-RV simulations including frequency-dependent line and cable models, tower representations, grounding systems, and instrument transformers within a differential protection measurement framework. The results show that overhead–cable transitions produce transient waveform modifications characterized by reflections, attenuation, dispersion, and temporary current imbalance mechanisms associated with traveling-wave propagation and cable capacitive effects. The analysis also demonstrates the transient evolution of instantaneous waveform-derived (EMT-derived) differential and restraining current quantities, defined as combinations of terminal current signals obtained directly from EMT waveforms. These quantities do not represent final phasor-domain operating values of practical numerical relays, but provide insight into the transient electromagnetic environment preceding conventional filtering and phasor estimation. The study contributes to a clearer physical interpretation of transient phenomena in hybrid transmission systems and supports EMT-based evaluation of signals relevant to differential protection applications.