Browsing by Author "Rodriguez, Jose"

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    An Overview of Microgrids Challenges in the Mining Industry
    (2020) Gómez, Juan S.; Rodriguez, Jose; Garcia, Cristian; Tarisciotti, Luca; Flores-Bahamonde, Freddy; Pereda Torres, Javier Eduardo; Nuñez Retamal, Felipe Eduardo; Cipriano, Aldo; Salas, Juan Carlos
    The transition from fossil fuels to renewable energies as power sources in the heavy industries is one of the main climate change mitigation strategies. The carbon footprint in mining is related to its inherent extraction process, its high demand of electric power and water, and the use of diesel. However, considering its particular power requirements, the integration of microgrids throughout the whole control hierarchy of mining industry is an emergent topic. This paper provides an overview of the opportunities and challenges derived from the synergy between microgrids and the mining industry. Bidirectional and optimal power flow, as well as the integration of power quality have been identified as microgrid features that could potentially enhance mining processes. Recommendations pertaining to the technological transition and the improvement of energy issues in mining environments are also highlighted in this work.
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    Denoising and Voltage Estimation in Modular Multilevel Converters Using Deep Neural-Networks
    (2020) Langarica Chavira, Saúl Alberto; Pizarro Lorca, Germán Eduardo; Poblete Durruty, Pablo Martín; Radrigán Sepúlveda, Felipe Ignacio; Pereda Torres, Javier Eduardo; Rodriguez, Jose; Núñez Retamal, Felipe Eduardo
    Modular Multilevel Converters (MMCs) have become one of the most popular power converters for medium/high power applications, from transmission systems to motor drives. However, to operate properly, MMCs require a considerable number of sensors and communication of sensitive data to a central controller, all under relevant electromagnetic interference produced by the high frequency switching of power semiconductors. This work explores the use of neural networks (NNs) to support the operation of MMCs by: i) denoising measurements, such as stack currents, using a blind autoencoder NN; and ii) estimating the sub-module capacitor voltages, using an encoder-decoder NN. Experimental results obtained with data from a three-phase MMC show that NNs can effectively clean sensor measurements and estimate internal states of the converter accurately, even during transients, drastically reducing sensing and communication requirements.
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    Diaphragmatic Ultrasound Predictors of High-Flow Nasal Cannula Therapeutic Failure in Critically Ill Patients With SARS-CoV-2 Pneumonia
    (2023) Bruna, Mario; Hidalgo, Gabriela; Castaneda, Sebastian; Galvez, Miguel; Bravo, Diego; Benitez, Rodrigo; Tobar, Rodolfo; Quevedo, Jose; Rodriguez, Jose; Murua, Camila; Madariaga, Rafael; Benavides, Claudia; Huilcaman, Marcos; Martinez, Felipe; Retamal, Jaime; Kattan, Eduardo
    ObjectivesHigh flow nasal cannula (HFNC) is frequently used in patients with acute respiratory failure, but there is limited evidence regarding predictors of therapeutic failure. The objective of this study was to assess diaphragmatic ultrasound criteria as predictors of failure to HFNC, defined as the need for orotracheal intubation or death. MethodsProspective cohort study including adult patients consecutively admitted to the critical care unit, from July 24 to October 20, 2020, with respiratory failure secondary to SARS-CoV-2 pneumonia who required HFNC. After 12 hours of HFNC initiation we measured ROX index (ratio of SpO(2)/FiO(2) to respiratory rate), excursion and diaphragmatic contraction speed (diaphragmatic excursion/inspiratory time) by ultrasound, both in supine and prone position. ResultsIn total, 41 patients were analyzed, 25 succeeded and 16 failed HFNC therapy. At 12 hours, patients who succeeded HFNC therapy presented higher ROX index in supine position (9.8 [9.1-15.6] versus 5.4 [3.9-6.8], P < .01), and higher PaO2/FiO(2) ratio (186 [135-236] versus 117 [103-162] mmHg, P = .03). To predict therapeutic failure, the supine diaphragmatic contraction speed presented sensitivity of 89% and a specificity of 57%, while the ROX index presented a sensitivity of 92.8% and a specificity of 75%. ConclusionsDiaphragmatic contraction speed by ultrasound emerges as a diagnostic complement to clinical tools to predict HFNC success. Future studies should confirm these results.
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    Model Predictive Control in Multilevel Inverters Part I: Basic Strategy and Performance Improvement
    (2024) Garcia, Cristian; Mora, Andres; Norambuena, Margarita; Rodriguez, Jose; Aly, Mokhtar; Carnielutti, Fernanda; Pereda, Javier; Acuna, Pablo; Aguilera, Ricardo; Tarisciotti, Luca
    Multilevel inverters (MLIs) have lately become important due to their extended application to electrical transmission and distribution systems. At the same time, the control and modulation of MLIs are especially challenging due to the high number of switching states, many of them redundant in terms of output voltage generation, and their nonlinear characteristics. In order to ease their implementation in real environment, model predictive control (MPC) is often considered, where the main control targets are: 1) to generate a the desired output current and 2) to keep the internal converter capacitor voltages at their reference value. However, a major issue with the implementation of MPC in MLIs is that the number of calculations to be done online increases dramatically with the number of levels, making it almost impossible to apply MPC in some practical cases. For these reasons, one of the main research trend in MPC for MLIs is to provide an algorithm which can reduce the computational burden necessary to operate the control. The article proposes a review of such control techniques. Starting from the basic MPC implementation and using a flying capacitor converter as an example the article review the basic strategies to avoid calculating the weighting factor in the cost function, simplifying the implementation. Also, methods to reduce the number of calculations necessary to implement MPC are shown and applied to cascaded H-bridge converters. These techniques allow to keep an high load current quality while reducing more than 95% in the number of calculations necessary to implement the control. Finally, other operation improvements of MPC are also included, such as fixed switching frequency operation and multistep MPC, reaching an important performance improvement compared to the basic MPC strategy.
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    Model Predictive Control in Multilevel Inverters Part II: Renewable Energies and Grid Applications
    (2024) Norambuena, Margarita; Mora, Andres; Garcia, Cristian; Rodriguez, Jose; Aly, Mokhtar; Carnielutti, Fernanda; Pereda, Javier; Castillo, Cristian; Zhang, Zhenbin; Yaramasu, Venkata; Tarisciotti, Luca; Yin, Yafei
    This article presents the use of model predictive control (MPC) in multilevel inverters for some applications, such as, first, wind generation and, second, photovoltaics, showing that the particular restrictions of each of them can be very easily included in the control algorithm, which is an important advantage of this technique. Another application is in modular multilevel cascaded converters, where it is demonstrated that MPC can operate with very few calculations and fixed switching frequency. The second part of this article is dedicated to comparing MPC with linear control and pulsewidth modulation for multilevel inverters. The main comparison criteria are the switching losses, the distortion in the load current, and the number of commutations. The main conclusion is that MPC is a competitive alternative to linear control for application in multilevel inverters.
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    Predictive Control for Current Distortion Mitigation in Mining Power Grids
    (2023) Gomez, Juan S. S.; Navas-Fonseca, Alex; Flores-Bahamonde, Freddy; Tarisciotti, Luca; Garcia, Cristian; Nunez, Felipe; Rodriguez, Jose; Cipriano, Aldo Z. Z.
    Current distortion is a critical issue of power quality because the low frequency harmonics injected by adjustable speed drives increase heating losses in transmission lines and induce torque flickering in induction motors, which are widely used in mining facilities. Although classical active filtering techniques mitigate the oscillatory components of imaginary power, they may not be sufficient to clean the sensitive nodes of undesirable power components, some of which are related to real power. However, the usage of power electronic converters for distributed generation and energy storage, allows the integration of complementary power quality control objectives in electrical systems, by using the same facilities required for active power transferring. This paper proposes a predictive control-based scheme for mitigating the current distortion in the coupling node between utility grid and the mining facility power system. Instead of the classical approach of active filtering, this task is included as a secondary level objective control referred into the microgrid control hierarchy. Hardware-in-the-Loop simulation results showed that the proposed scheme is capable of bounding the current distortion, according to IEEE standard 1547, for both individual harmonics and the total rated current distortion, through inequality constraints of the optimization problem.