Adjustment of model parameters to estimate distribution transformers remaining lifespan

Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the margin for summer peaks is small). The advent of the Smart Grids allows electricity distribution companies to apply data analysis techniques to manage resources more efficiently at different levels (avoiding damages, better contingency management, maintenance planning, etc.). The Smart Grids in Argentina progresses slowly due to the high costs involved. In this context, the estimation of the lifespan reduction of distribution transformers is a key tool to efficiently manage human and material resources, maximizing the lifetime of this equipment. Despite the current state of the smart grids, the electricity distribution companies can implement it using the available data. Thermal models provide guidelines for lifespan estimation, but the adjustment to particular conditions, brands, or material quality is done by adjusting parameters. In this work we propose a method to adjust the parameters of a thermal model using Genetic Algorithms, comparing the estimation values of top-oil temperature with measurements from 315 kVA distribution transformers, located in the province of Tucumán, Argentina. The results show that, despite limited data availability, the adjusted model is suitable to implement a transformer monitoring system.Fil: Jimenez, Victor Adrian. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Will, Adrian L. E.. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Gotay Sardiñas, Jorge. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Rodriguez, Sebastian Alberto. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentin

Interdisciplinary Teaching in the Field of Resilient Energy Systems: Experiences with Expert Lecture Series Combined with Workshops

The increased complexity of renewable energy systems derives in uncertain and vulnerable systems behavior, making necessary for energy experts to understand and apply resilience studies with interdisciplinary approaches. With this aim, we have designed a postgraduate course on resilience of energy systems, pursuing an “exchange interdisciplinarity” level that enables students to (i) become aware of competing approaches in terms of methods and theories stemming from different disciplines, and (ii) to critically argue on the suitability of presented concepts for energy systems design and management. The course aimed at achieving a sound level of exchange interdisciplinarity as defined in relevant literature. We chose the following specific teaching methods and didactic items to facilitate this aim and address the different challenges of interdisciplinary education identified from the literature: fundamental introduction (FI), expert interviews and deepening workshops. The FI aimed at providing a sound common basis for understanding the perspectives and approaches from different disciplines. The expert lecture series exposed students to the broadness of state-of-the-art approaches existing in resilience research for energy systems, while the deepening workshops allowed students to develop a deep and critical appraisal of the disciplinary approaches and their relations. The course impact is evaluated through the standard questionnaire for teaching evaluation from the University of Oldenburg. The evaluation shows that the course fostered a critical and interdisciplinary thinking, with a high and interactive participation through the use of multiple didactic measures. This is supported by the high satisfaction of the students, the high level of engagement and academic performance and the qualitative perception from the lecturers. Topics of similar complexity or interdisciplinarity in energy higher education, such as sustainability, technology assessment or energy systems analysis could also benefit from such a course design

Galileo and EGNOS as an asset for UTM safety and security

GAUSS (Galileo-EGNOS as an Asset for UTM Safety and Security) is a H2020 project1 that aims at designing and developing high performance positioning systems for drones within the U-Space framework focusing on UAS (Unmanned Aircraft System) VLL (Very Low Level) operations. The key element within GAUSS is the integration and exploitation of Galileo and EGNOS exceptional features in terms of accuracy, integrity and security, which will be key assets for the safety of current and future drone operations. More concretely, high accuracy, authentication, precise timing (among others) are key GNSS (Global Navigation Satellite System) enablers of future integrated drone operations under UTM (UAS Traffic Management) operations, which in Europe will be deployed under U-Space [1]. The U-Space concept helps control, manage and integrate all UAS in the VLL airspace to ensure the security and efficiency of UAS operations. GAUSS will enable not only safe, timely and efficient operations but also coordination among a higher number of RPAS (Remotely Piloted Aircraft System) in the air with the appropriate levels of security, as it will improve anti-jamming and anti-spoofing capabilities through a multi-frequency and multi-constellation approach and Galileo authentication operations. The GAUSS system will be validated with two field trials in two different UTM real scenarios (in-land and sea) with the operation of a minimum of four UTM coordinated UAS from different types (fixed and rotary wing), manoeuvrability and EASA (European Aviation Safety Agency) operational categories. The outcome of the project will consist of Galileo-EGNOS based technological solutions to enhance safety and security levels in both, current UAS and future UTM operations. Increased levels of efficiency, reliability, safety, and security in UAS operations are key enabling features to foster the EU UAS regulation, market development and full acceptance by the society.Peer ReviewedPostprint (author's final draft

Primera ley de la termodinámica

Este material incluye los siguientes temas: Procesos y sistemas termodinámicos, Trabajo realizado por un gas, Energía interna de un sistema, Primera Ley de La Termodinámica, Capacidad calorífica del gas ideal, Procesos TermodinámicosThis material includes the following subjects: thermodynamical processes, Work made by a gas, Internal energ

Segunda ley de la termodinámica

Este material incluye los siguientes temas: Maquinas térmicas, Motores de combustión interna, Refrigeradores, Segunda Ley de la Termodinámica, Máquina y refrigerador de Carnot, Entropía y la segunda ley de la termodinámicaThis material includes the following subjects: Thermal machines, Second law of thermodynamics, entropy, Carnot cycl

Propiedades térmicas de la materia

Este material incluye los siguientes temas: Ley del gas ideal, Propiedades moleculares de la materia, Modelo cinético-molecular del gas ideal, Capacidad calorífica y principio de equipartición de la energíaThis material includes the following subjects: ideal gas, Molecular properties of matter, energy equipartition principl

Estimación de radiación solar horaria utilizando modelos empíricos y redes neuronales artificiales.

La radiación solar es uno de los parámetros más importantes para el desarrollo de aplicaciones e investigaciones relacionadas a energías renovables. Sin embargo, la adquisición de mediciones de radiación solar no siempre es posible por diferentes motivos y es necesario contar con modelos que permitan estimarla. Estos modelos en su mayoría utilizan variables climáticas difíciles de medir y que no siempre están disponibles en todos los sitios. El objetivo de este trabajo es aplicar un método para estimar radiación solar horaria, basado en redes neuronales, utilizando como variables de entrada estimaciones de radiación solar obtenidas mediante un modelo matemático simple y variables climáticas de fácil adquisición: Temperatura, Presión y Humedad. Además, para comprobar que las redes neuronales son más adecuadas en estos casos se hizo una comparativa con estimaciones realizadas con regresión lineal. Los modelos generados fueron ajustados y validados con datos provenientes de cinco estaciones meteorológicas de la provincia de Tucumán, Argentina, logrando obtener en promedio un error de 11.0% (Root Mean Squared Error) con regresión lineal y 7.84% con redes neuronales.Palabras claves: radiación solar horaria, modelos empíricos, redes neuronales feedforward, regresión lineal, energía renovabl

Temperatura y expansión térmica

Este material incluye los siguientes temas: Temperatura y equilibrio térmico, Escalas de Temperatura ,Dispositivos utilizados para medir temperaturas, Expansión térmicasThis material includes the following subjects: The concept of temperature, Thermal equilibrium, Temperature scale

Ondas estacionarias

Este material incluye los siguientes temas: ondas estacionarias, ondas estacionarias en una cuerda con extremos fijos, modos normales de vibracion,This material includes the following subjects: stationary waves, stationary waves on a string, normal modes of vibratio