Big Data Analysis Applied for Short Term Solar Irradiance Forecasting Lavanya R1,*, Thanigaivelan V.2 1Assistant Professor, Dept. of CSE, SRM Institute of Science and Technology, Chennai 2Assistant Professor, Dept. of Mechanical, SRM Institute of Science and Technology, Chennai *Corresponding author: R Lavanya, E-mail: lavanyaconf@gmail.com
Online published on 4 June, 2019. Abstract An improvement of accuracy in Forecasting of Solar Weather requires more specific parameters. Parameters that are feasible to implement and the collected data to be ready to be blended and becauseof this, the parameters need to be easy to use and its of prime importance that it remains the case. In this case giving our focuson getting the pollution parameter in order to make a module that will integrate with an existing solar weather prediction system. The module takes in pollution data uses the light beams reaction to the particulates per million content and its characteristic reaction to compound that'sclassified as a pollutant or a heavy molecule. It is getting the data about the light beams hitting the surface below the cloud cover, and that gives an output of energy that's hitting the ground to suncast system. Top Keywords Big data, suncast system, weather forecasting, renewable energy, light diffraction coefficients, solar irradiance. Top |