• Title of article

    Applying Rough Sets for the Identification of Significant Variables in Photovoltaic Energy Production with Isolated Systems

  • Author/Authors

    Rodríguez, José Antonio Pérez Rúa da Universidade - Centro de Formación e Recursos, Spain , Fdez-Riverola, Florentino Universitario As Lagoas - Escuela Superior de Ingeniería Informática Campus, Spain , Fdez-Riverola, Florentino Centro de Investigación, Transferencia e Innovación - Parque Tecnológico de Galic, Spain

  • From page
    9
  • To page
    16
  • Abstract
    The main objective of this work is to study the state of the art of current techniques and algorithms for improving the efficiency of isolated solar photovoltaic systems. Additionally, a study will be conducted regarding the feasibility of applying rough sets (RS) for the practical identification of a minimum set of significant input variables (condition attributes) which determine the value of the output variables (decision attributes) in solar photovoltaic systems. Several experiments were carried out using a TS97 solar photovoltaic system donated by T-Solar for research purposes. The developed system was used to capture the values of input variables in different periods of time and climatic conditions (obtained through a MeteoGalicia monitoring station). The experimental prototype implemented was composed of a solar photovoltaic panel, a resistive load to dissipate the energy generated by the panel, a MPPT (Maximum Power Point Tracking) placed between the panel and the charge, a data logger equipped with a RTC (Real-Time Clock) and several sensors for measuring the values of physical and electrical variables of the system. Data captured was stored in a 2GB solid state card using a plain text format in order to facilitate later study and analysis using RS.
  • Keywords
    Isolated solar photovoltaic systems , MPPT algorithms , rough sets , variable selection , classification quality
  • Journal title
    Jurnal Teknologi :F
  • Journal title
    Jurnal Teknologi :F
  • Record number

    2715980