Very Short-Term Estimation of Global Horizontal Irradiance Using Data Mining Methods


7th International Conference on Renewable Energy Research and Applications (ICRERA), Paris, Fransa, 14 - 17 Ekim 2018, ss.1472-1476 identifier identifier

  • Cilt numarası:
  • Doi Numarası: 10.1109/icrera.2018.8566747
  • Basıldığı Şehir: Paris
  • Basıldığı Ülke: Fransa
  • Sayfa Sayıları: ss.1472-1476


Solar energy is one of the safe, clean and environment-friendly renewable energy sources. In solar energy systems, it is important to obtain the maximum solar irradiance during the day, predict the solar energy generation and increase the efficiency of solar systems. In this study, we focus on the very short term estimation of global horizontal irradiance utilizing k nearest neighbor and Naive Bayes algorithms. In the estimation process, direct normal irradiance, diffuse horizontal irradiance, dry-bulb temperature and relative humidity parameters arc used in the multi-tupled input structure. The k-nearest neighbor algorithm which employs direct normal irradiance and diffuse horizontal irradiance parameters in the 2-tupled input structure is observed as the most promising model with the lowest mean absolute percentage error.