Prediction of Electric Power Generation of Solar Cell Using the Neural Network (original) (raw)

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.

Preview

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Yamamoto, S., Park, J.S., Takata, M., Sasaki, K., Hashimoto, T.: Basic study on the prediction of solar irradiation and its application to photovoltaic-diesel hybrid generation system. Journal of Solar Energy Materials & Solar Cells 75(3–4), 577–584 (2003)
    Article Google Scholar
  2. Rumellhart, D.E., Hinton, G.E., Williams, R.J.: Learning internal representations by error propagation, Parallel distributed processing, pp. 318–362. MIT Press, Cambridge (1986)
    Google Scholar
  3. Ichikawa, S., Kawaguchi, M., Okuno, M.: Measurement and Prediction of Electric Power Generation of Solar Cell Using the Neural Network, Record of Tokai-Section Joint Conference of the Eight Institutes of Electrical and Relater Engineers, 34 (2003)
    Google Scholar

Download references

Author information

Authors and Affiliations

  1. Department of Electrical & Electronic Engineering, Suzuka National College of Technology, Shiroko, Suzuka, Mie, 510-0294, Japan
    Masashi Kawaguchi, Sachiyoshi Ichikawa & Masaaki Okuno
  2. Department of Environmental Technology and Urban Planning Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, 466-8555, Japan
    Takashi Jimbo
  3. Department of Information Network Engineering, Aichi Institute of Technology, Yachigusa, Yagusa-cho, Toyota, 470-0356, Japan
    Naohiro Ishii

Authors

  1. Masashi Kawaguchi
  2. Sachiyoshi Ichikawa
  3. Masaaki Okuno
  4. Takashi Jimbo
  5. Naohiro Ishii

Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK
    Bogdan Gabrys
  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK
    Robert J. Howlett
  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, SA, 5095, Mawson Lakes, Australia
    Lakhmi C. Jain

Rights and permissions

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kawaguchi, M., Ichikawa, S., Okuno, M., Jimbo, T., Ishii, N. (2006). Prediction of Electric Power Generation of Solar Cell Using the Neural Network. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004\_50

Download citation

Publish with us