Marcos Álvarez, Javier
Loading...
Email Address
person.page.identifierURI
Birth Date
Job Title
Last Name
Marcos Álvarez
First Name
Javier
person.page.departamento
Ingeniería Eléctrica, Electrónica y de Comunicación
person.page.instituteName
ISC. Institute of Smart Cities
ORCID
person.page.observainves
person.page.upna
Name
- Publications
- item.page.relationships.isAdvisorOfPublication
- item.page.relationships.isAdvisorTFEOfPublication
- item.page.relationships.isAuthorMDOfPublication
2 results
Search Results
Now showing 1 - 2 of 2
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, 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 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 On the on-site measurement of the degradation rate of crystalline silicon PV modules at plant level(IEEE, 2018) Pascual Miqueleiz, Julio María; Berrueta Irigoyen, Alberto; Marcos Álvarez, Javier; García Solano, Miguel; Marroyo Palomo, Luis; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de ComunicaciónThis paper proposes a method for measuring the degradation rate of crystalline silicon PV modules at plant level in two different ways as a form of verification. As actual levels of degradation rate have been observed to be as low as 0.2%/a, the uncertainties make it difficult to measure this value accurately at plant level. However, despite the low value, it is still important to know the actual degradation rate due to its impact on energy yield. In this paper, two ways of measuring the degradation rate at plant level are proposed. These two methods, with different uncertainty sources, are proposed to be used jointly in order to have a better approach to the real value. Finally, an example of measurement in a 1.78 MW PV plant is presented.