Determining suitability of locations for installation of solar power station based on probabilistic inference

Colak I., SAĞIROĞLU Ş., DEMİRTAŞ M., KAHRAMAN H. T.

9th International Conference on Machine Learning and Applications, ICMLA 2010, Washington, United States Of America, 12 - 14 December 2010, pp.714-719 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icmla.2010.169
  • City: Washington
  • Country: United States Of America
  • Page Numbers: pp.714-719
  • Keywords: Installation of solar power stations, Meteorological data, Naïve Bayes classification, Rule based inference, Solar energy
  • Karadeniz Technical University Affiliated: Yes

Abstract

This paper presents a novel system is to develop to determine the suitability of a location for installation of solar power stations. Necessary data including speed and direction of wind, solar radiation and rainfall are received from a meteorology station, and data acquired are then converted to the labels. Finally, the labels are evaluated in a Naïve Bayes algorithm to determine the suitability of the location for the installation and axial structure of a Solar Power Plant. This helps to determine complicated calculations by means of the support system developed. © 2010 IEEE.