• español
  • English
  • français
  • Deutsch
  • português (Brasil)
  • italiano
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Ricerca

    Tutto UVaDOCArchiviData di pubblicazioneAutoriSoggettiTitoli

    My Account

    Login

    Estadísticas

    Ver Estadísticas de uso

    Compartir

    Mostra Item 
    •   UVaDOC Home
    • PRODUZIONE SCIENTIFICA
    • Departamentos
    • Dpto. Ingeniería Eléctrica
    • DEP45 - Artículos de revista
    • Mostra Item
    •   UVaDOC Home
    • PRODUZIONE SCIENTIFICA
    • Departamentos
    • Dpto. Ingeniería Eléctrica
    • DEP45 - Artículos de revista
    • Mostra Item
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano

    Exportar

    RISMendeleyRefworksZotero
    • edm
    • marc
    • xoai
    • qdc
    • ore
    • ese
    • dim
    • uketd_dc
    • oai_dc
    • etdms
    • rdf
    • mods
    • mets
    • didl
    • premis

    Citas

    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/53032

    Título
    Genetic algorithm methodology for the estimation of generated power and harmonic content in photovoltaic generation
    Autor
    Elvira Ortiz, David Alejandro
    Jaen Cuellar, Arturo Yosimar
    Moríñigo Sotelo, DanielAutoridad UVA Orcid
    Morales Velazquez, LuisAutoridad UVA
    Osornio Ríos, Roque Alfredo
    Romero Troncoso, René de Jesús
    Año del Documento
    2020
    Editorial
    MDPI
    Descripción
    Producción Científica
    Documento Fuente
    Applied Sciences, 2020, vol. 10, n. 2, 542
    Abstract
    Renewable generation sources like photovoltaic plants are weather dependent and it is hard to predict their behavior. This work proposes a methodology for obtaining a parameterized model that estimates the generated power in a photovoltaic generation system. The proposed methodology uses a genetic algorithm to obtain the mathematical model that best fits the behavior of the generated power through the day. Additionally, using the same methodology, a mathematical model is developed for harmonic distortion estimation that allows one to predict the produced power and its quality. Experimentation is performed using real signals from a photovoltaic system. Eight days from different seasons of the year are selected considering different irradiance conditions to assess the performance of the methodology under different environmental and electrical conditions. The proposed methodology is compared with an artificial neural network, with the results showing an improved performance when using the genetic algorithm methodology.
    Palabras Clave
    Genetic algorithms
    Algoritmos genéticos
    Photovoltaic systems
    Sistema fotovoltaicos
    ISSN
    2076-3417
    Revisión por pares
    SI
    DOI
    10.3390/app10020542
    Patrocinador
    CONACYT (scholarship 415315)
    FOFI –UAQ 2018 (project FIN201812)
    PRODEP (project UAQ-PTC-385)
    Version del Editor
    https://www.mdpi.com/2076-3417/10/2/542
    Propietario de los Derechos
    © 2020 The Authors
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/53032
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
    Aparece en las colecciones
    • DEP45 - Artículos de revista [38]
    Mostra tutti i dati dell'item
    Files in questo item
    Nombre:
    Genetic-algorithm-methodology.pdf
    Tamaño:
    3.148Mb
    Formato:
    Adobe PDF
    Thumbnail
    Mostra/Apri
    Atribución 4.0 InternacionalLa licencia del ítem se describe como Atribución 4.0 Internacional

    Universidad de Valladolid

    Powered by MIT's. DSpace software, Version 5.10