This article addresses a comprehensive analysis of power electrical systems, employing a combined approach of genetic algorithms and mathematical optimization through nonlinear programming with discontinuous derivatives (DNLP) in GAMS. The primary objective is to minimize economic losses and associated costs faced by the network operator following disruptive events. The analysis is divided into two fundamental aspects. Firstly, it addresses the topological reconfiguration of the network, involving the addition of lines and distributed energy resources such as distributed generation. To determine the optimal topological reconfiguration, a genetic algorithm was developed and implemented. This approach aims to restore electrical service to the maximum load within the system. Secondly, an optimal energy dispatch was performed for each generator, considering the variation in load throughout the day. The system’s load curve is taken into account to determine the optimal energy distribution. Thus, the problem of economic losses is approached from two perspectives: the minimization of costs due to nonsupplied electrical energy and the determination of efficient energy dispatch for each generator after network reconfiguration. For the analysis and case studies, simulations were conducted on the IEEE 9- and 30-node test systems. The results demonstrate the effectiveness of the proposed solution, evaluated in terms of reduced load shedding and economic losses.

Electric power systems are subject to failures, due to both deliberate and fortuitous events. This paper addresses the first case in which a disruptive agent aims at maximizing the damage to the network (expressed through the total cost of operation), while the system operator takes the necessary measures to mitigate the effects of this attack. The interaction between these two agents is modeled by means of a bi-level optimization problem. On one hand, the disruptive agent is positioned in the upper-level optimization problem and must decide which elements to render out of service (lines and generators), given a limited destructive budget. On the other hand, the system operator, located in a lower-level optimization problem, reacts to the attack by deploying mitigation measures in order to minimize cost overruns in system operation. Based on the aforementioned dynamic, this paper proposes a novel approach to maximize the resiliency of the power system under intentional attacks through the implementation of distributed energy resources (DERs), namely, distributed generation (DG) and demand response (DR). Three metrics are proposed to assess resilience by assigning DERs in islands generated by the destruction of lines and generators. The results obtained in a didactic 5-bus test system and the IEEE RTS-24 bus test system demonstrate the applicability and effectiveness of the proposed methodology.

In this paper, a new analytical solution to the undamped Helmholtz oscillator equation in terms of the Weierstrass elliptic function is reported. The solution is given for any arbitrary initial conditions. A comparison between our new solution and the numerical approximate solution using the Range Kutta approach is performed. We think that the methodology employed here may be useful in the study of several nonlinear problems described by a differential equation of the form $z^{″}=F\left(z\right)$ in the sense that $z=z\left(t\right)$ . In this context, our solutions are applied to some physical applications such as the signal that can propagate in the LC series circuits. Also, these solutions were used to describe and investigate some oscillations in plasma physics such as oscillations in electronegative plasma with Maxwellian electrons and negative ions.

La siniestralidad vial es un problema para los tomadores de decisiones en el sector público. Se prospecta que de continuar esta tendencia, para 2030 la mortandad por eventos viales se ubicaría como la quinta causa a nivel global. El objetivo de este estudio analiza el escenario de dos ciudades metropolitanas que han aplicado infraestructura vial encaminada a la sostenibilidad de la movilidad urbana. Para ello, se elaboró una escala de valoración cualitativa y por medio de estadísticas de siniestralidad vial se identificaron y compararon patrones de utilización de infraestructura peatonal, ciclista y transporte público masivo. Se prospecta que de seguir implementándose estas medidas, se tendría en las ciudades de Bogotá-Colombia y Guadalajara-México una reducción en las tasas de mortandad por siniestros viales superiores a un 30% en 2030.

Introducción: este es un artículo de investigación en el que se crea un sistema de alerta temprana por movimiento en masa inducido por lluvia para la localidad de Ciudad Bolívar, en Bogotá, Colombia, desarrollado en la Universidad Distrital Francisco José de Caldas en el año 2018. Metodología: se desarrolló una red de sensores por medio de una estación base, que se encarga de generar una alerta si existe riesgo de deslizamiento. Resultados: los datos generados por la red de sensores, como humedad y temperatura, generan alertas aumentando la posibilidad de salvar vidas de personas vulnerables en la localidad. Conclusión: con este proyecto, se busca salvar lo más importante del ser humano: la vida; además de concientizar a la gente del peligro que conlleva construir casas en lugares con alto riesgo de deslizamiento, se pretende mostrar que por medio de la tecnología es posible salvar vidas, alertando con tiempo catástrofes naturales como los deslizamientos. Originalidad: en este trabajo, se genera un estudio de suelo previo en la localidad de Ciudad Bolívar y se crea una escala de alerta propia para el sistema, implementando en la localidad el Sistema de Información para la Gestión del Riesgo y Cambio Climático (SIRE). Limitaciones: el escaso desarrollo de los sistemas de alerta en deslizamiento de tierra inducido por lluvia en Colombia.

Traffic control in data networks has recently become very important due to the massive use of computer networks in different areas of society. Different techniques are usually used to carry out effective traffic control, allowing, among other things, to classify, predict and monitor network traffic. These techniques have evolved and are currently supported by artificial intelligence tools, which have made it possible to improve the results obtained with conventional techniques. This paper collects the different contributions made by the field of artificial intelligence to the improvement of these techniques and network management in general. The article describes the contributions made in aspects such as security, prediction, and classification of data traffic, as well as the optimization of routing in a computer network.