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The number of Fuel Cell Electric Vehicles (FCEVs) in circulation has undergone a significant increase in recent years. This trend is foreseen to be stronger in the near future. In correlation with the FCEVs market increase, the hydrogen delivery infrastructure must be developed. With this aim, many countries have announced ambitious projects. For example, Spain has the objective of increasing the number of Hydrogen Refuelling Stations (HRS) with public access from three units in operation currently to about 150 by 2030. HRSs are complex systems with high variability in terms of layout design, size of components, operational strategy, hydrogen generation method or hydrogen generation location. This paper is focused on on-site HRS with electrolysis-based hydrogen production, which provides interesting advantages when renewable energy is utilized compared to off-site hydrogen production despite their complexity. To optimize HRS design and operation, a simulation model must be implemented. This paper describes a generic on-site HRS with electrolysis-based hydrogen production, a cascaded multi-tank storage system with multiple compressors, renewable energy sources, and multiple types of dispensing formats. A modelling approach of the layout is presented and tested with real-based parameters of an HRS currently under development, which is capable of producing 11.34 kg/h of green H2 with irradiation at 1000 W/m2. For the operation, an operational strategy is proposed. The modelled system is tested through several simulations. A sensitivity analysis of the effects of hydrogen demand and day-ahead hydrogen production objective on emissions, demand satisfaction and variable costs is performed. Simulation results show how the operational strategy has achieved service up to 310 FCEVs refuelling events of heavy duty and light duty FCEVs, bringing the total H2 sold up to almost 7200 H2kg in one month of winter. Additionally, considering variable costs of the energy from the utili

© 2023 The Author(s). Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC. This is an open access article under the CC BY-NCND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)., The number of Fuel Cell Electric Vehicles (FCEVs) in circulation has undergone a significant increase in recent years. This trend is foreseen to be stronger in the near future. In correlation with the FCEVs market increase, the hydrogen delivery infrastructure must be developed. With this aim, many countries have announced ambitious projects. For example, Spain has the objective of increasing the number of Hydrogen Refuelling Stations (HRS) with public access from three units in operation currently to about 150 by 2030. HRSs are complex systems with high variability in terms of layout design, size of components, operational strategy, hydrogen generation method or hydrogen generation location. This paper is focused on on-site HRS with electrolysis-based hydrogen production, which provides interesting advantages when renewable energy is utilized compared to off-site hydrogen production despite their complexity. To optimize HRS design and operation, a simulation model must be implemented. This paper describes a generic on-site HRS with electrolysis-based hydrogen production, a cascaded multi-tank storage system with multiple compressors, renewable energy sources, and multiple types of dispensing formats. A modelling approach of the layout is presented and tested with real-based parameters of an HRS currently under development, which is capable of producing 11.34 kg/h of green H2 with irradiation at 1000 W/m2 . For the operation, an operational strategy is proposed. The modelled system is tested through several simulations. A sensitivity analysis of the effects of hydrogen demand and day-ahead hydrogen production objective on emissions, demand satisfaction and variable costs is performed. Simulation results show how the operational strategy has achieved service up to 310 FCEVs refuelling events of heavy duty and light duty FCEVs, bringing the total H2 sold up to almost 7200 H2kg in one month of winter. Additionally, considering variable costs of the energy from the util, This research has been developed within the CSIC Interdisciplinary Thematic Platform (PTIþ) Transición Energética Sostenible+ (PTI-TRANSENER+)[TRE2103000] as part of the CSIC program for the Spanish Recovery, Transformation and Resilience Plan funded by the Recovery and Resilience Facility of the European Union, established by the Regulation (EU) 2020/2094; project MASHED [TED2021-129927BeI00] funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR; and the project MAFALDA [PID2021-126001OB-C31] funded by MCIN/AEI/10.13039/501100011033 and by ERDF A way of making Europe., Peer Reviewed, Postprint (published version)

In this paper, we propose the use of nonlinear oblique subspace projections (NObSP) with support vector machines (SVM), as well as an out-of-sample extension of this algorithm to reduce its arithmetic complexity. NObSP was originally developed for least-Squares SVM, and it aims at decomposing the model output into additive components. Each component represents the partial (non)linear contribution of each input regressor, and their interaction effects, on the output. The original NObSP has an arithmetic complexity of O(N3), being N the number of observations. The proposed out-of-sample extension, combined with SVM, reduces the arithmetic complexity of NObSP to O(N*d2), with d the number of support vectors., Peer Reviewed, Postprint (published version)

L’objectiu d’aquest treball és implementar un controlador en una placa basada en Arduino per controlar una maqueta del sistema ball and beam i desenvolupar una documentació que pugui ajudar estudiants tant del Grau com del Màster d’Enginyeria Industrial de l’ETSEIB (o qual- sevol persona amb coneixements bàsics de control automàtic) a entendre el funcionament del controlador i com implementar-lo en un entorn real. Aquesta memòria documenta els diferents processos que s’han seguit per implementar el controlador. Aquests processos inclouen el muntatge del model físic, incloent els esquemàtics del circuit elèctric o les característiques més rellevants dels components, la inicialització i config- uració de la placa i la sintonització dels seus perifèrics. La memòria també inclou l’abstracció matemàtica del model físic, la qual és la clau del càlcul del controlador que finalment serà im- plementat a la placa Arduino i evaluat, El objetivo de este trabajo es implementar un controlador en una placa basada en Arduino para controlar una maqueta del sistema ball and beam y desarrollar una documentación que pueda ayudar a estudiantes tanto del Grado como del Máster de Ingeniería Industrial de la ETSEIB (o a cualquier persona con conocimientos básicos de control automático) a entender el fun- cionamiento del controlador y como implementarlo en un entorno real. Esta memoria documenta los diferentes procesos que se han seguido para implementar el con- trolador. Estos procesos incluyen el montaje del modelo físico, incluyendo los esquemáticos del circuito eléctrico o las características más relevantes de los componentes, la inicialización y configuración de la placa y la sintonización de sus periféricos. La memoria también incluye la abstracción matemática del modelo físico, la cual es la clave del cálculo del controlador que finalmente será implementado en la placa Arduino y evaluado, The goal of this project is to implement a controller in an Arduino based board in order to control a low-cost ball and beam model, and to develop a series of documentation which can help students from either ETSEIB Industrial Engineering Bachelor’s or Master’s Degree -or anyone with basic automatic control knowledge- understand the controller’s functioning and how to implement it into a real environment. This memory documents the different processes which have been followed in order to imple- ment the controller. These processes include the model’s physical layout assembly, including the electric circuit’s schematics or the components’ most relevant data, the initialization and configuration of the board and the tuning of its peripherals. It also includes the mathematical abstraction of the physical model, which is the key to the calculation of the controller which will be then implemented in the Arduino board and tested

Parabolic-trough solar collector fields are large-scale systems, so the application of centralized optimizationbased control methods to these systems is often not suitable for real-time control. As such, this paper formulates a novel coalitional control approach as an appropriate alternative to the centralized scheme. The key idea is to split the overall solar collector field into smaller subsystems, each of them governed by a local controller. Then, controllers are clustered into coalitions to solve a local optimization-based problem related to the corresponding subset of subsystems, so that an approximate solution of the original centralized problem can be obtained in a decentralized fashion. However, the operational constraints of the solar collector field couple the optimization problems of the multiple coalitions, thus limiting the ability to solve them in a fully decentralized manner. To overcome this issue, a novel population-dynamics-assisted resource allocation strategy is proposed as a mechanism to decouple the local optimization problems of the multiple coalitions. The proposed coalitional methodology allows to solve the multiple local subproblems in parallel, hence reducing the overall computational burden, while guaranteeing the satisfaction of the operational constraints and without significantly compromising the overall performance. The effectiveness of proposed approach is shown through numerical simulations of a 10- and 100-loop version of the ACUREX solar collector field of Plataforma Solar de Almería, Spain., Peer Reviewed, Postprint (published version)

Remaining useful life (RUL) is the crucial element in predictive maintenance, helping to reduce significant costs in factories and avoiding production downtime. This work contributes to a non-intrusive condition monitoring to estimate the RUL of the most critical component in an electromechanical system, which does not depend on previous historical run-to-failure data. Although most of the approaches characterize the behavior of the mechanical components from a vibration analysis, this work is focused on monitoring the characteristic frequencies from the torque oscillations that are transmitted via the three-phase stator currents. In this way, several features can be extracted by processing the current signals. Modeling the behavior of the features in a healthy stage, a health indicator is proposed that measures how well a new sample fits the healthy model. This indicator is processed to ensure an indicator with a monotonically increasing trend. Therefore, a procedure is proposed to estimate the RUL by calculating multiple exponential regressions at each sampling time, considering only incremental samples. Based on a defined failure threshold and exponential regressions, a time-to-failure (TTF) non-parametric distribution is updated online, as more samples are processed, the most likely TTF is revealed over time and used to estimate RUL along with its confidence bounds. The proposed approach has been validated with three experiments performed on a run-to-failure ball-bearing testbed, lasting 65 hours, 30 hours and 180 hours. As a result, the methodology achieved high accuracy in anticipating bearing failures 50 hours, 26 hours, and 100 hours before failure; with an accuracy of 93.78%, 89.49% and 64.31%, respectively. A comparative assessment with reported approaches was carried out using the PRONOSTIA-FEMTO datasets, demonstrating the suitable performance of the proposed approach to converge faster to the real RUL with high accuracy., Peer Reviewed, Postprint (author's final draft)

© 2023 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., We consider a large population of decision makers that choose their evolutionary strategies based on simple pairwise imitation rules. We describe such a dynamic process by the replicator dynamics. Differently from the available literature, where the payoffs signals are assumed to be updated continuously, we consider a more realistic scenario where they are updated occasionally. Our main technical contribution is to devise two event-triggered communication schemes with asymptotic convergence guarantees to a Nash equilibrium. Finally, we show how our proposed approach is applicable as an efficient distributed demand response mechanism., This research was supported by the project PID2020-115905RB-C21 (L-BEST) funded by MCIN/ AEI /10.13039/501100011033, the ERC under research project COSMOS (802348), and the project BPIN 2021000100499 funded by CTeI - SGR and MinCiencias, Colombia., Peer Reviewed, Postprint (author's final draft)

Parabolic-trough solar collector fields are large-scale systems, so the application of centralized optimization-based control methods to these systems is often not suitable for real-time control. As such, this paper formulates a novel coalitional control approach as an appropriate alternative to the centralized scheme. The key idea is to split the overall solar collector field into smaller subsystems, each of them governed by a local controller. Then, controllers are clustered into coalitions to solve a local optimization-based problem related to the corresponding subset of subsystems, so that an approximate solution of the original centralized problem can be obtained in a decentralized fashion. However, the operational constraints of the solar collector field couple the optimization problems of the multiple coalitions, thus limiting the ability to solve them in a fully decentralized manner. To overcome this issue, a novel population-dynamics-assisted resource allocation strategy is proposed as a mechanism to decouple the local optimization problems of the multiple coalitions. The proposed coalitional methodology allows to solve the multiple local subproblems in parallel, hence reducing the overall computational burden, while guaranteeing the satisfaction of the operational constraints and without significantly compromising the overall performance. The effectiveness of proposed approach is shown through numerical simulations of a 10- and 100-loop version of the ACUREX solar collector field of Plataforma Solar de Almería, Spain.