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    The influence of mass on dynamic response of cracked Timoshenko beam with restrained end conditions: the truncated theory
    (MDPI - Publisher of Open Access Journals, 2025-02-07) De Rosa, María Anna; Ceraldi, Carla; Martín, Héctor Daniel; Onorato, Antonella; Piovan, Marcelo Tulio; Lippiello, María
    n this paper, the dynamic response of the Timoshenko cracked beam subjected to a mass is investigated. In turn, it is assumed that the beam has its ends restrained with both transverse and rotational elastic springs. Based on an alternative beam theory, truncated Timoshenko theory (TTT), the governing equations of motion of the cracked beam are derived and the influence of a mass on the behavior of free vibrations is investigated. The novelty of the proposed approach lies in the fact that the variational method used in the truncated theory simplifies the derivation of the equation of motion via the classical theory, and the perfect analogy between the two theories is shown. The objective of the present formulation lies in finding the equations of the truncated Timoshenko model with their corresponding boundary conditions and establishing their mathematical similarity with the geometric approach. It is shown that the differential equations with their corresponding boundary conditions, used to solve the dynamic problem of Timoshenko truncated beams through variational formulations, have the same form as those obtained through the direct method. Finally, some numerical examples are carried out to evaluate the influence of a mass and its position on the vibration performances of the cracked Timoshenko model. Additionally, the effects of the crack positions, the shear deformation and rotational inertia, and the yielding constraints on the natural frequencies are also discussed in some numerical examples.
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    State-space modelling of a commercial lithium-ion battery
    (IEEE Xplore, 2021-12-24) Alarcón, Rodrigo Germán; Alarcón, Martín Alejandro; González, Alejandro H.; Ferramosca, Antonio
    In this paper, a continuous and discrete-time dynamical model of a commercial lithium-ion battery is proposed. It is modelled through an electrical equivalent circuit, applying the method of parameter extraction in the time domain to determine its values. As parameters vary according to the state of charge of the battery, a procedure for parametric identification based on the least-squares method is presented, using the Simulink ® Design Optimization™.
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    Economic model predictive control for energy management in a hybrid storage microgrid
    (IEEE Xplore, 2021-12-24) Alarcón, Martín Alejandro; Alarcón, Rodrigo Germán; González, Alejandro H.; Ferramosca, Antonio
    This paper proposes a Model Predictive Control (MPC) strategy for energy resources management in a microgrid. A state-space discrete-time linear model is presented, characterized by an hybrid storage system, consisting of lithium ion battery banks and ultracapacitors. The renewable resource is composed by an array of solar panels and the microgrid is considered to be connected to the main electricity grid, having the possibility to interact with it, under certain restrictions. Simulation results are presented under different generation and consumption scenarios.
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    Economic model predictive control for energy management of a microgrid connected to the main electrical grid
    (ScienceDirect, 2022-09) Alarcón, Martín Alejandro; Alarcón, Rodrigo Germán; González, Alejandro H.; Ferramosca, Antonio
    Electric microgrids have become an interesting tool to facilitate the inclusion of renewable energies. Its architecture and control system plays a fundamental role in the implementation of these systems. This paper proposes a control strategy for the management of energy resources in a residential microgrid. The system is made up of a set of solar panels as renewable resource, a storage system formed by a lithium-ion battery bank and a consumption profile according to a residence. The microgrid will be connected to the main electrical grid and the proposed management strategy consists in the implementation of a suitable Economic Model Predictive Control, where it considers the costs of use for the different components of the microgrid, thus contemplating the participation of the system as an active agent in the electricity market. Simulations were carried out with different scenarios of available resources and prediction times. In all cases, the objectives fulfilling by satisfying the restrictions operational and technical imposed on the system.
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    Approximating the solution of an economic MPC using artificial neural networks
    (IEEE Xplore, 2024-05-21) Alarcón, Rodrigo Germán; Alarcón, Martín Alejandro; González, Alejandro H.; Ferramosca, Antonio
    Abstract: Economic model predictive control is a recognized advanced control strategy which calculates control actions by solving an optimization problem in real time. The issue of numerical computation is the main barrier to implementing this type of controller. Deep learning has emerged as a promising solution to reduce the computational cost. This paper proposes a deep learning approximation of an Economic MPC, particularly with artificial neural networks, of the control strategy for managing energy resources in a residential microgrid. Operational data were generated from the solution established by the controller to train, validate and test the neural network using Matlab. Simulation results showed that the proposed approach can approximate the control strategy correctly.
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    A scenario-based economic-stochastic model predictive control for the management of microgrids
    (ScienceDirect, 2023-12) Alarcón, Martín Alejandro; Alarcón, Rodrigo Germán; González, Alejandro H.; Ferramosca, Antonio
    Abstract The world’s electricity generation is heavily dependent on the consumption of fossil fuels. Electric generation from renewable resources is necessary due to the imperative need to reduce greenhouse gases to avoid a climate crisis. These resources exhibit random and intermittent behaviour. Therefore, there is a need to develop new management and control tools for these insertions into the current electricity system. Microgrids have become an effective tool to solve this problem, where these control systems play a principal role. For this reason, an optimal control structure consisting of two Model Predictive Control strategies is proposed for a microgrid Energy Management System. The first controller aims to optimise the microgrid’s economic performance under an established criterion, using nominal forecasts of the disturbances on the system, such as the energy generated by renewable resources. The second is a stochastic approach using scenario-based methods to consider forecast errors in the nominal predictions used for the disturbances. The simulations were carried out on a microgrid model corresponding to the National Technological University, Reconquista Regional Faculty, highlighting that actual samples of energy consumption are available. It is worth noting that with the proposed structure, optimal solutions are obtained considering the random behaviour of the disturbances, without making assumptions about the distribution functions of the random variables. Moreover, it applies to different scales of microgrids.
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    Sistema mecánico para seguimiento solar a dos ejes con una fuerza motriz
    (2024-10-16) Ros, Mario Alberto; Crudeli, Rossana; Suligoy, Juan Pablo; Capeletti, Walter Hernán
    El sistema mecánico para seguimiento solar a dos ejes con una fuerza motriz se conforma de un eje vertical y uno horizontal, el primero sigue el movimiento aparente del sol desde su salida en el Este hasta su ocaso en el Oeste, describiendo por lo tanto un ángulo en el plano horizontal del observador llamado acimutal, el segundo eje (cabezal) que sirve a la vez de soporte de los paneles fotovoltaicos posee un movimiento que describe, en su seguimiento, el ángulo de altitud solar en un plano perpendicular al anterior. El giro del eje vertical se logra por medio de su corona central que recibe el movimiento de una fuerza motriz mediante un sin-fin y piñón, mientras que el movimiento del cabezal, eje horizontal, se debe a otro engranaje de igual característica a la corona central más un brazo pivote, el cual se vincula a la parte baja de la estructura del panel por medio de una rótula y tensor. La segunda corona engrana a la corona central diametralmente opuesta y en sentido Norte-Sur al piñón motriz. De esta forma el sistema con el mecanismo propuesto logra en su funcionamiento, en su giro de Este a Oeste, un aumento en la distancia entre la parte baja del cabezal y la columna central (alejamiento), logrando una menor inclinación del panel respecto al suelo para las horas del mediodía en las que se tiene una mayor altitud solar y, una disminución en la distancia entre la parte baja del cabezal y la columna central (acercamiento) para lograr una mayor inclinación del panel respecto al suelo, tanto a las primeras como a las últimas horas del día, donde la posición del Sol presenta una menor altitud solar. Con el mecanismo propuesto se logra un 89% en el año de perpendicularidad de los rayos solares a la superficie del panel.
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    Artificial neural networks for energy demand prediction in an economic MPC-Based energy management system
    (International Journal of Robust and Nonlinear Control, 2024-10-20) Alarcón, Rodrigo Germán; Alarcón, Martín Alejandro; González, Alejandro H.; Ferramosca, Antonio
    ABSTRACT Microgrids are a development trend and have attracted a lot of attention worldwide. The control system plays a crucial role in implementing these systems and, due to their complexity, artificial intelligence techniques represent some enabling technologies for their future development and success. In this paper, we propose a novel formulation of an economic model predictive control (economic MPC) applied to a microgrid designed for a faculty building with the inclusion of a predictive model to deal with the energy demand disturbance using a recurrent neural network of the long short-term memory (RNN-LSTM). First, we develop a framework to identify an RNN-LSTM using historical data registered by a smart three-phase power quality analyzer to provide feedforward power demand predictions. Next, we present an economic MPC formulation that includes the prediction model for the disturbance within the optimization problem to be solved by the MPC strategy. We carried out simulations with different scenarios of energy consumption, available resources, and simulation times to highlight the results obtained and analyze the performance of the energy management system. In all cases, we observed the correct operation of the proposed control scheme, complying at all times with the objectives and operational restrictions imposed on the system.
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    Análisis vibratorio de pórtico: Teoría de Timoshenko-Ehrenfest con truncamiento
    (2024-09-18) Martín, Héctor Daniel; De Rosa, María Anna; Lippiello, María; Fantini, Sebastián Hugo
    En este trabajo se propone el estudio del análisis dinámico de un pórtico Timoshenko-Ehrenfest utilizando la teoría truncada propuesta en 2022 por (De Rosa, Lippiello, Elishakoff) para vigas. Esta teoría, desarrollada tanto con el método variacional como con el geométrico, muestra que los resultados obtenidos son casi los mismos, pero lo interesante resulta ser que las ecuaciones diferenciales quedan simplificadas. Se considera un pórtico clásico, formado por dos columnas y una viga, con análisis de cedimiento de vínculos además de los vínculos a tierra clásicos como las articulaciones y el empotramiento. Se resuelven las ecuaciones diferenciales y en los ejemplos se destaca la influencia sobre las frecuencias libres de vibraciones de los cedimientos en los vínculos, el efecto de la altura de la sección recta de las columnas y de la viga.
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    Método intuitivo para el cálculo de entramados planos con reducción en la cantidad de incógnitas
    (2024-10-22) Martín, Héctor Daniel; De Rosa, María Anna; Fantini, Sebastián Hugo; Peresón, Marcos
    El trabajo consiste en la resolución de pórticos planos utilizando series de potencias enteras para el desarrollo de las funciones desplazamiento tanto transversal como axial de las barras. Luego de obtener estas funciones, mani pulando un número muy bajo de incógnitas, se realizan los diagramas de esfuerzos de corte, normal y momentos de cada una de las barras. El método es intuitivo y logra resolver entramados hiperestáticos sujetos a diversas cargas puntuales en los nodos o distribuidas sobre las barras. El modelado es fácil de implementar para estudian tes con conocimientos de estática y series de potencias. La precisión de los resultados aumenta con el grado de potencia de las series seleccionadas. La novedad es que este incremento de términos en el desarrollo en serie no eleva la cantidad de incógnitas del problema planteado, situación que si se produce en otros métodos. Se aclara la metodología con ejemplos resueltos.