Context: This research presents two main results: (i) the application of deep learning networks for the classification of transient overvoltage in the frequency domain, and (ii) the physical-mathematical formulation for the coupling of atmospheric electrical discharges in polarized media in the frequency domain. Method: Initially, transient overvoltage records resulting from atmospheric electrical discharges were obtained from simulations in EMTP-ATP software, using the IEEE 13-node distribution network as a reference. Each transient overvoltage was transformed from the time domain to the frequency domain via the Fast Fourier Transform. Subsequently, the neural networks were trained, and their results were compared. For indirect lightning strikes, a complex-variable analysis of permittivity and permeability was performed. These variables were applied to the lightning coupling model in distribution lines or networks. Results: Classification accuracies of 80 and 89.99% were achieved for transient overvoltage using the GoogLeNet and Python-ChatGPT neural networks, respectively. Furthermore, this work presents the coupling expression for atmospheric electrical discharges in polarized media. Conclusions: The classification of transient overvoltage records using deep-layer neural networks and the physical-mathematical expression for lightning coupling in the frequency domain through complex variables allows for a broader understanding of the network response to this type of natural phenomenon.
Voltage stability is a fundamental aspect of power system reliability, which refers to an electrical network’s ability to maintain acceptable voltage levels under normal operating conditions and various types of disturbances
Context: Evaluating third-party logistics (3PL) providers is a complex task since multiple criteria assessed by experts with potentially diverse perspectives are involved, leading to varying scores based on individual prioritizations. This study attempts to evaluate 3PL providers for a mid-sized fishery company in Jakarta, Indonesia, focusing on refrigerated transportation within cold chain logistics. Method: A methodology integrating rough stepwise weight assessment ratio analysis (R-SWARA) and complex proportional assessment (COPRAS) is employed to address expert uncertainty and rank six providers based on seven criteria: security, punctuality, cost, delivery area, customer service, assurance, and logistics experience. R-SWARA assigns weights using rough set intervals, while COPRAS ranks providers. Results: The integrated methods yield Vendor A as the top choice, with a utility degree of 100%, followed by Vendor D and others ranging from 96.7 to 98.4%. These rankings highlight the critical role of punctuality and security in refrigerated transportation, aligning with the fishery industry’s need to ensure product freshness and reliability. A sensitivity analysis that varies the weight of punctuality by ± 20% confirms the ranking’s stability, highlighting the methodology’s robustness. The findings align with prior studies emphasizing performance and quality in logistics, while R-SWARA’s use of intervals offers a novel approach to handling uncertainty. Conclusions: The proposed method recommends Vendor A to ensure timely and secure seafood delivery, with implications for perishable goods logistics. The limitations include a small expert panel and a single-case focus, suggesting the need for future research with larger samples and broader applications. Another limitation of the proposed approach is its reliance on expert judgement for criteria weighting, as well as its sensitivity to the selected criteria and case context. Therefore, the findings should be interpreted as a decision support rather than universal rankings.
Context: In recent times, access to electricity in non-interconnected areas has been a constant challenge. Therefore, this article evaluates the technical feasibility of implementing direct-current (DC) microgrids in these areas, focusing on food conservation. Our evaluation focuses on the region of Chacón Playa (Timbiquí) in the Cauca Pacific, Colombia. Method: This work analyzes the advantages and disadvantages of DC microgrids vs. alternating-current (AC) systems, selecting a radial topology for its simplicity and expandability. A simulation is performed in MATLAB-Simulink with a control system based on the incremental conductance algorithm, which incorporates solar photovoltaic generation, battery backup, power converters, and a load composed of four DC coolers. Results: The results and simulations show that DC microgrids are effective in meeting voltage and current demands in response to changes in solar radiation and power demand. Our findings highlight the ability of DC microgrids to provide a stable and efficient power supply suitable for food conservation in non-interconnected areas. Conclusions: DC microgrids represent a viable solution to cover energy needs in isolated areas. This study supports their implementation as a sustainable and reliable alternative, opening new opportunities for the development of regulatory frameworks that facilitate the expansion of this type of technology in similar regions.
Contexto: Las tasas de siniestralidad en la red vial terciaria de Colombia superan los promedios nacionales, en gran parte debido a la falta de instrumentos para la recolección sistemática de datos y a la limitada participación de las comunidades locales en la identificación de riesgos. Este estudio tuvo como objetivo diseñar una herramienta de diagnóstico de seguridad vial que pueda ser aplicada por la comunidad, adaptada a contextos rurales y validada con actores locales en el departamento del Cauca, Colombia. Método: Se realizó una revisión de literatura para identificar los principales factores de riesgo que afectan la seguridad vial en las vías terciarias de Colombia. Se incorporó la escala KABCO por su simplicidad y su idoneidad para el trabajo colaborativo. A partir de estos insumos, se desarrolló una herramienta de diagnóstico y una guía de usuario. Finalmente, se implementó un estudio piloto mediante talleres participativos, durante los cuales se recolectaron puntos georreferenciados y evaluaciones de riesgo. Resultados: La aplicación piloto de la herramienta permitió identificar y georreferenciar siete puntos críticos a lo largo de un tramo vial en el municipio de Popayán. En estos lugares, la velocidad fue identificada como uno de los factores más influyentes en los siniestros viales reportados por la comunidad. La herramienta demostró claridad y viabilidad de uso por parte de participantes sin formación técnica previa. Conclusiones: La herramienta desarrollada ofrece un método replicable que permite a las comunidades rurales identificar y gestionar los riesgos de seguridad vial, generando datos valiosos para la formulación de planes de mantenimiento y políticas de prevención. Su implementación puede optimizar la asignación de recursos y fortalecer la colaboración entre las comunidades y las autoridades responsables.
