Person: UrsĂșa Rubio, Alfredo
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UrsĂșa Rubio
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Alfredo
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IngenierĂa ElĂ©ctrica, ElectrĂłnica y de ComunicaciĂłn
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ISC. Institute of Smart Cities
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0000-0001-6240-8659
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3245
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Publication Open Access Influence of the aging model of lithium-ion batteries on the management of PV self-consumption systems(IEEE, 2018) Berrueta Irigoyen, Alberto; Pascual Miqueleiz, Julio MarĂa; San MartĂn Biurrun, Idoia; Sanchis GĂșrpide, Pablo; UrsĂșa Rubio, Alfredo; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; IngenierĂa ElĂ©ctrica, ElectrĂłnica y de ComunicaciĂłn; Gobierno de Navarra / Nafarroako Gobernua, PI038 INTEGRA-RENOVABLESLithium-ion batteries are gaining importance for a variety of applications due to their improving characteristics and decreasing price. An accurate knowledge of their aging is required for a successful use of these ESSs. The vast number of models that has been proposed to predict these phenomena raise doubts about the suitability of a model for a particular battery application. The performance of three models published for a Sanyo 18650 cylindrical cell in a self-consumption system are compared in this work. Measured photovoltaic production and home consumption with a sampling frequency of 15 minutes are used for this comparison. The different aging predictions calculated by these three models are analyzed, compared and discussed. These comparison is particularized for two management strategies. The first of them maximizes the self-consumption PV energy, while the second reduces the maximum power peak demanded from the grid.Publication Open Access Comparison of State-of-Charge estimation methods for stationary Lithium-ion batteries(IEEE, 2016) Berrueta Irigoyen, Alberto; San MartĂn Biurrun, Idoia; Sanchis GĂșrpide, Pablo; UrsĂșa Rubio, Alfredo; IngenierĂa ElĂ©ctrica y ElectrĂłnica; Ingeniaritza Elektrikoa eta Elektronikoa; Institute of Smart Cities - ISCAn accurate monitoring of the State of Charge (SoC) is mandatory for an efficient management of a Lithium-ion battery. Batteries of stationary systems barely have long resting periods when the cumulative errors can be reset. These special requirements make a robust and accurate SoC estimation algorithm necessary. A real stationary system including an experimental microgrid with renewable energy generation, home consumption and a 5.3 kWh Li-ion storage system is analyzed in this paper. Three representative SoC monitoring algorithms are applied and compared in terms of accuracy and robustness to battery aging and current measurement offset. A closed-loop method consisting of an adaptive filter and a state observer achieves best results while having a reasonable computational complexity.Publication Open Access Identification of critical parameters for the design of energy management algorithms for Li-ion batteries operating in PV power plants(IEEE, 2020) Berrueta Irigoyen, Alberto; Soto Cabria, AdriĂĄn; Marcos Ălvarez, Javier; Parra Laita, Ăñigo de la; Sanchis GĂșrpide, Pablo; UrsĂșa Rubio, Alfredo; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; IngenierĂa ElĂ©ctrica, ElectrĂłnica y de ComunicaciĂłn; Universidad PĂșblica de Navarra / Nafarroako Unibertsitate Publikoa, ReBMS PJUPNA1904; Gobierno de Navarra / Nafarroako Gobernua, 0011-1411-2018-000029 GERALithium-ion batteries are gaining importance for a variety of applications due to their price decrease and characteristics improvement. For a proper use of such storage systems, an energy management algorithm (EMA) is required. A number of EMAs, with various characteristics, have been published recently, given the diverse nature of battery problems. The EMA of deterministic battery problems is usually based on an optimization algorithm. The selection of such an algorithm depends on a few problem characteristics, which need to be identified and closely analyzed. The aim of this article is to identify the critical optimization problem parameters that determine the most suitable EMA for a Li-ion battery. With this purpose, the starting point is a detailed model of a Li-ion battery. Three EMAs based on the algorithms used to face deterministic problems, namely dynamic, linear, and quadratic programming, are designed to optimize the energy dispatch of such a battery. Using real irradiation and power price data, the results of these EMAs are compared for various case studies. Given that none of the EMAs achieves the best results for all analyzed cases, the problem parameters that determine the most suitable algorithm are identified to be four, i.e., desired computation intensity, characteristics of the battery aging model, battery energy and power capabilities, and the number of optimization variables, which are determined by the number of energy storage systems, the length of the optimization problem, and the desired time step.Publication Open Access Critical comparison of energy management algorithms for lithium-ion batteries in renewable power plants(IEEE, 2019) Berrueta Irigoyen, Alberto; Soto Cabria, AdriĂĄn; GarcĂa Solano, Miguel; Parra Laita, Ăñigo de la; Sanchis GĂșrpide, Pablo; UrsĂșa Rubio, Alfredo; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; IngenierĂa ElĂ©ctrica, ElectrĂłnica y de ComunicaciĂłn; Universidad PĂșblica de Navarra / Nafarroako Unibertsitate PublikoaLithium-ion batteries are gaining importance for a variety of applications due to their price decrease and characteristics improvement. A good energy management strategy is required in order to increase the profitability of an energy system using a Li-ion battery for storage. The vast number of management algorithms that has been proposed to optimize the achieved profit, with diverse computational power requirements and using models with different complexity, raise doubts about the suitability of an algorithm and the required computation power for a particular application. The performance of three energy management algorithms based on linear, quadratic, and dynamic programming are compared in this work. A realistic scenario of a medium-sized PV plant with a constraint of peak shaving is used for this comparison. The results achieved by the three algorithms are compared and the grounds of the differences are analyzed. Among the three compared algorithms, the quadratic one seems to be the most suitable for renewableenergy applications, given the undue simplification of the battery aging required by the linear algorithm and the discretization and computational power required by a dynamic algorithm.Publication Open Access Modelling of PEM fuel cell performance: steady-state and dynamic experimental validation(MDPI, 2014) San MartĂn Biurrun, Idoia; UrsĂșa Rubio, Alfredo; Sanchis GĂșrpide, Pablo; IngenierĂa ElĂ©ctrica y ElectrĂłnica; Ingeniaritza Elektrikoa eta Elektronikoa; Gobierno de Navarra / Nafarroako GobernuaThis paper reports on the modelling of a commercial 1.2 kW proton exchange membrane fuel cell (PEMFC), based on interrelated electrical and thermal models. The electrical model proposed is based on the integration of the thermodynamic and electrochemical phenomena taking place in the FC whilst the thermal model is established from the FC thermal energy balance. The combination of both models makes it possible to predict the FC voltage, based on the current demanded and the ambient temperature. Furthermore, an experimental characterization is conducted and the parameters for the models associated with the FC electrical and thermal performance are obtained. The models are implemented in Matlab Simulink and validated in a number of operating environments, for steady-state and dynamic modes alike. In turn, the FC models are validated in an actual microgrid operating environment, through the series connection of 4 PEMFC. The simulations of the models precisely and accurately reproduce the FC electrical and thermal performance.