Open Access
Comparison of State-of-Charge estimation methods for stationary Lithium-ion batteries
(IEEE, 2016) Berrueta Irigoyen, Alberto; San Martín Biurrun, Idoia; Sanchis Gúrpide, Pablo; Ursúa Rubio, Alfredo; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa; Institute of Smart Cities - ISC
An 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.
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 María; San Martín Biurrun, Idoia; Sanchis Gúrpide, Pablo; Ursúa Rubio, Alfredo; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación; Gobierno de Navarra / Nafarroako Gobernua, PI038 INTEGRA-RENOVABLES
Lithium-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.
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, Adrián; Marcos Álvarez, Javier; Parra Laita, Íñigo de la; Sanchis Gúrpide, Pablo; Ursúa Rubio, Alfredo; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, ReBMS PJUPNA1904; Gobierno de Navarra / Nafarroako Gobernua, 0011-1411-2018-000029 GERA
Lithium-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.
Open Access
Critical comparison of energy management algorithms for lithium-ion batteries in renewable power plants
(IEEE, 2019) Berrueta Irigoyen, Alberto; Soto Cabria, Adrián; García Solano, Miguel; Parra Laita, Íñigo de la; Sanchis Gúrpide, Pablo; Ursúa Rubio, Alfredo; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Lithium-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.

Berrueta Irigoyen, Alberto

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