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1,765 results on '"Rico A"'

1. Sizing a Battery Energy Storage System for Hybrid Renewable Power Plants Based on Optimal Market Participation Under Different Market Scenarios

Author

Ingeniería Energética, Energia Ingenieritza, Martínez Rico, Jon, Zulueta Guerrero, Ekaitz, Ruiz de Argandoña, Ismael, Armendia, Mikel, Fernández Gámiz, Unai, Ingeniería Energética, Energia Ingenieritza, Martínez Rico, Jon, Zulueta Guerrero, Ekaitz, Ruiz de Argandoña, Ismael, Armendia, Mikel, and Fernández Gámiz, Unai

Abstract

This article presents a method for selecting the best battery sizing based on an optimal market participation strategy in a hybrid renewable power plant. The proposed formulation consid-ers different scenarios to ensure the reserve provision compliance and includes two terms. The first one maximizes the day- ahead and automatic frequency restoration reserve (aFRR) market revenues. The second minimizes the battery degradation, accounting for both cycling and calendar ageing effects. The Iberian Electricity Market is selected as the study case, and two different market scenarios are compared: the current market scenario and the upcoming one, in which the upward and downward aFRR band offers are independent. The operation of a set of batteries is simulated until their end of life, and results reveal that energy/power ratios higher than 3 h for the current market scenario, and than 4 h for the upcoming one, are less cost effective. Regarding the best battery energy storage systems sizing, the selection varies considering incomes or profitability criteria. Moreover, keeping the current prices, in the upcoming market scenario hybrid renewable power plants are encouraged to participate more in the downward than in the upward aFRR market

Published
2024

17. Power Efficient Simple Technique to Convert a Reset-and-Hold Into a True-Sample-and-Hold Using an Auxiliary Output Stage

Author

Hector Daniel Rico-Aniles, Jaime Ramirez-Angulo, Antonio J. Lopez-Martin, Ramon Gonzalez Carvajal, Jose Miguel Rocha-Perez, and M. Pilar Garde

Subjects
Amplifiers, mixed-signal circuits, offset compensation, track-and-hold, sample-and-hold (S/H), switched capacitor, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

A technique to implement true-sample-and-hold circuits that hold the output for almost the entire clock cycle without resetting to zero is introduced, alleviating the slew rate requirement on the op-amp. It is based on a Miller op-amp with an auxiliary output stage that increases power dissipation by only 1.3%. The circuit is offset-compensated and has close to rail-to-rail swing. Experimental results of a test chip prototype in 130nm CMOS technology with 0.3mW power dissipation are provided, which validate the proposed technique.

Published
2020
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20. Design and characterization of an EOG signal acquisition system based on the programming of saccadic movement routines

Author

Frem-Sosa, Luis A., primary, Valenzuela-Delgado, Mónica, additional, Flores-Fuentes, Wendy, additional, Rodríguez-Quiñonez, Julio C., additional, Sergiyenko, Oleg, additional, Hernández-Balbuena, Daniel, additional, Murrieta-Rico, Fabián N., additional, Miranda-Vega, Jesús E., additional, and Mercorelli, Paolo, additional

Published
2023
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28. Numerical artifacts in finite-difference time- domain algorithms analyzed by means of principal components

Author

López Alonso, José Manuel, Rico-García, José María, Alda, Javier, López Alonso, José Manuel, Rico-García, José María, and Alda, Javier

Abstract

© 2005 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”, Finite-difference time-domain (FDTD) algorithms are affected by numerical artifacts and noise. In order to obtain better results we propose the use of the principal component analysis based on multivariate statistical techniques. It allows a straightforward discrimination between the numerical noise and the actual electromagnetic field distributions, and the quantitative estimation of their respective contributions. Besides, the FDTD results can be filtered to clean the effect of the noise. The method has been applied successfully to two dimensional simulations: propagation of a pulse in vacuum using total field-scattered field techniques, and mode computation in a two-dimensional photonic crystal. In this last case, PCA has revealed hidden electromagnetic structures related to actual modes of the photonic crystal., Sección Deptal. de Óptica (Óptica), Fac. de Óptica y Optometría, TRUE, pub

Published
2023

29. Identifying Student Profiles Within Online Judge Systems Using Explainable Artificial Intelligence

Author

Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos, Rico-Juan, Juan Ramón, Sánchez-Cartagena, Víctor M., Valero-Mas, Jose J., Gallego, Antonio-Javier, Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos, Rico-Juan, Juan Ramón, Sánchez-Cartagena, Víctor M., Valero-Mas, Jose J., and Gallego, Antonio-Javier

Abstract

Online Judge (OJ) systems are typically considered within programming-related courses as they yield fast and objective assessments of the code developed by the students. Such an evaluation generally provides a single decision based on a rubric, most commonly whether the submission successfully accomplished the assignment. Nevertheless, since in an educational context such information may be deemed insufficient, it would be beneficial for both the student and the instructor to receive additional feedback about the overall development of the task. This work aims to tackle this limitation by considering the further exploitation of the information gathered by the OJ and automatically inferring feedback for both the student and the instructor. More precisely, we consider the use of learning-based schemes—particularly, Multi-Instance Learning and classical Machine Learning formulations—to model student behaviour. Besides, Explainable Artificial Intelligence is contemplated to provide human-understandable feedback. The proposal has been evaluated considering a case of study comprising 2,500 submissions from roughly 90 different students from a programming-related course in a Computer Science degree. The results obtained validate the proposal: the model is capable of significantly predicting the user outcome (either passing or failing the assignment) solely based on the behavioural pattern inferred by the submissions provided to the OJ. Moreover, the proposal is able to identify prone-to-fail student groups and profiles as well as other relevant information, which eventually serves as feedback to both the student and the instructor.

Published
2023

40. Identifying Student Profiles Within Online Judge Systems Using Explainable Artificial Intelligence

Author

Juan Ramon Rico-Juan, Victor M. Sanchez-Cartagena, Jose J. Valero-Mas, Antonio Javier Gallego, Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos, Reconocimiento de Formas e Inteligencia Artificial, and Transducens

Subjects
eXplainable Artificial Intelligence, Machine Learning, General Engineering, Online Judge systems, Student profile identification, Multi-Instance Learning, Computer Science Applications, Education
Abstract

Online Judge (OJ) systems are typically considered within programming-related courses as they yield fast and objective assessments of the code developed by the students. Such an evaluation generally provides a single decision based on a rubric, most commonly whether the submission successfully accomplished the assignment. Nevertheless, since in an educational context such information may be deemed insufficient, it would be beneficial for both the student and the instructor to receive additional feedback about the overall development of the task. This work aims to tackle this limitation by considering the further exploitation of the information gathered by the OJ and automatically inferring feedback for both the student and the instructor. More precisely, we consider the use of learning-based schemes—particularly, Multi-Instance Learning and classical Machine Learning formulations—to model student behaviour. Besides, Explainable Artificial Intelligence is contemplated to provide human-understandable feedback. The proposal has been evaluated considering a case of study comprising 2,500 submissions from roughly 90 different students from a programming-related course in a Computer Science degree. The results obtained validate the proposal: the model is capable of significantly predicting the user outcome (either passing or failing the assignment) solely based on the behavioural pattern inferred by the submissions provided to the OJ. Moreover, the proposal is able to identify prone-to-fail student groups and profiles as well as other relevant information, which eventually serves as feedback to both the student and the instructor. This work has been partially funded by the “Programa Redes-I3CE de investigacion en docencia universitaria del Instituto de Ciencias de la Educacion (REDES-I3CE-2020-5069)” of the University of Alicante. The third author is supported by grant APOSTD/2020/256 from “Programa I+D+I de la Generalitat Valenciana”.

Published
2023

50. Chained Orchestrator Algorithm for RAN-Slicing Resource Management: A Contribution to Ultra-Reliable 6G Communications

Author

Jose J. Rico-Palomo, Jesus Galeano-Brajones, David Cortes-Polo, Juan F. Valenzuela-Valdes, and Javier Carmona-Murillo

Subjects
General Computer Science, Capacity, Resource management, Latency, General Engineering, Channel estimation, General Materials Science, Electrical and Electronic Engineering, Reliability, 6G, RAN slicing
Abstract

The exponentially growing trend of Internet-connected devices and the development of new applications have led to an increase in demands and data rates flowing over cellular networks. If this continues to have the same tendency, the classification of 5G services must evolve to encompass emerging communications. The advent of the 6G Communications concept takes this into account and raises a new classification of services. In addition, an increase in network specifications was established. To meet these new requirements, enabling technologies are used to augment and manage Radio Access Network (RAN) resources. One of the most important mechanisms is the logical segmentation of the RAN, i.e. RAN-Slicing. In this study, we explored the problem of resource allocation in a RAN-Slicing environment for 6G ecosystems in depth, with a focus on network reliability. We also propose a chained orchestrator algorithm for dynamic resource management that includes estimation techniques, inter-slice resource sharing and intra-slice resource assignment. These mechanisms are applied to new types of services in the future generation of cellular networks to improve the network latency, capacity and reliability. The numerical results show a reduction in blocked connections of 38.46% for eURLLC type services, 21.87% for feMBB services, 12.5% for umMTC, 11.86% for ELDP and 11.76% for LDHMC., Spanish National Program of Research, Development, Innovation, under Grant RTI2018-102002-A-I00, Junta de Extremadura under Project IB18003 and Grant GR21097

Published
2022

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