Prediction of electric power generation of solar cell using the neural network

  • Authors:

  • Masashi Kawaguchi;Sachiyoshi Ichikawa;Masaaki Okuno;Takashi Jimbo;Naohiro Ishii

  • Affiliations:

  • Department of Electrical & Electronic Engineering, Suzuka National College of Technology, Suzuka, Mie, Japan;Department of Electrical & Electronic Engineering, Suzuka National College of Technology, Suzuka, Mie, Japan;Department of Electrical & Electronic Engineering, Suzuka National College of Technology, Suzuka, Mie, Japan;Department of Environmental Technology and Urban Planning Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Japan;Department of Information Network Engineering, Aichi Institute of Technology, Toyota, Japan

  • Venue:
  • KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
  • Year:
  • 2006

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Abstract

We proposed the prediction system of electric power generation of solar cell using neural network. Recently, the solar cell system is developing in many fields. However this system is easily to influence by the weather condition. In the practical application, it has been required the prediction of electric power generation. By this system, it is possible to make the planning of supply and the security of alternative power source. This prediction system is used neural network system and it can predict the integral power consumption, largest electric power and time-serial prediction.