SolarCAST: using widely accessible environmental variables to forecast solar power

  • Authors:
  • Chris Hatfield;David Umphress

  • Affiliations:
  • Asbury College, Wilmore, KY;Auburn University, Auburn, AL

  • Venue:
  • Proceedings of the 46th Annual Southeast Regional Conference on XX
  • Year:
  • 2008

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Abstract

The study in renewable energy is one of great discussion, since we, as energy users, are being faced with the dilemma of running out of non-renewable energy sources. A popular alternative to non-renewable energy, especially for residential areas, is solar energy. This paper demonstrates that it is possible to derive a function using linear regression and least squares approximation techniques with information from an online weather source, such as www.accuweather.com, which can predict, with little error, the voltage and photovoltaic (PV) energy that can be expected for the day. We provide empirical results using a solar system.