Berrueta Irigoyen, AlbertoSoto Cabria, AdriánMarcos Álvarez, JavierParra Laita, Íñigo de laSanchis Gúrpide, PabloUrsúa Rubio, Alfredo2021-02-192021-06-182020A. Berrueta, A. Soto, J. Marcos, Í. de la Parra, P. Sanchis and A. Ursúa, 'Identification of Critical Parameters for the Design of Energy Management Algorithms for Li-Ion Batteries Operating in PV Power Plants,' in IEEE Transactions on Industry Applications, vol. 56, no. 5, pp. 4670-4678, Sept.-Oct. 2020, doi: 10.1109/TIA.2020.3003562.1939-9367 (Electronic)10.1109/TIA.2020.3003562https://academica-e.unavarra.es/handle/2454/39253Lithium-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.8 p.application/pdfeng© 2020 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 work.Energy managementLithium-ion batteryMicrogridPhotovoltaic (PV) plantRenewable energyinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccessAcceso abierto / Sarbide irekia