A measure of credibility of solar power prediction

Haoyang Shen, Hideitsu Hino, Noboru Murata, Shinji Wakao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recently, remarkable developments of new energy technologies have been achieved against various energy problems. Photovoltaic (PV) system, one of such technologies, has an advantage of utilizing infinite and clean energy. On the contrary, it also has a disadvantage of unreliable power supply mainly caused by unstable weather. The fluctuation of the power supply of PV systems are considerably large because of rapid insulation changes and rapid weather changes, and in some cases, it seems impossible to realize high-accuracy prediction even with sophisticated prediction models. In this paper, using recently proposed estimator for the Shannon information content, a method to output a measure of credibility for prediction is proposed. With the proposed method, it is possible to judge whether the energy supply at a certain future time is unpredictably fluctuate compared to the current value or not, and it is possible to take measures against the rapid change of solar energy generation in advance. From an experimental result using solar energy supply data, we see that the proposed measure of credibility reflects the difficulty of predicting solar energy supply.

Original languageEnglish
Title of host publicationProceedings - 10th International Conference on Machine Learning and Applications, ICMLA 2011
Pages286-291
Number of pages6
DOIs
Publication statusPublished - 2011 Dec 1
Event10th International Conference on Machine Learning and Applications, ICMLA 2011 - Honolulu, HI, United States
Duration: 2011 Dec 182011 Dec 21

Publication series

NameProceedings - 10th International Conference on Machine Learning and Applications, ICMLA 2011
Volume2

Conference

Conference10th International Conference on Machine Learning and Applications, ICMLA 2011
CountryUnited States
CityHonolulu, HI
Period11/12/1811/12/21

Keywords

  • Measure of Credibility
  • Prediction
  • Shannon Information Content
  • Solar Energy

ASJC Scopus subject areas

  • Computer Science Applications
  • Human-Computer Interaction

Fingerprint Dive into the research topics of 'A measure of credibility of solar power prediction'. Together they form a unique fingerprint.

  • Cite this

    Shen, H., Hino, H., Murata, N., & Wakao, S. (2011). A measure of credibility of solar power prediction. In Proceedings - 10th International Conference on Machine Learning and Applications, ICMLA 2011 (pp. 286-291). [6147689] (Proceedings - 10th International Conference on Machine Learning and Applications, ICMLA 2011; Vol. 2). https://doi.org/10.1109/ICMLA.2011.14