Pattern sequence-based energy demand forecast using photovoltaic energy records

研究成果: Conference contribution

11 引用 (Scopus)

抜粋

Considering recent trends in energy technology development, consumer's energy demand could be influenced by the renewable energy supply in any way. A simple extension of pattern sequence-based forecasting (PSF) enables us to predict demand curves based on the correlated bidimensional time-series by using co-occurrence patterns of energy supply and demand. However, prediction accuracy of PSF deeply depends on the clustering result, which is used for pattern matching. In this paper, a promising clustering method based on nonnegative tensor factorization is applied for this task and evaluated experimentally from the viewpoint of prediction accuracy.

元の言語English
ホスト出版物のタイトル2012 International Conference on Renewable Energy Research and Applications, ICRERA 2012
DOI
出版物ステータスPublished - 2012 12 1
イベント1st International Conference on Renewable Energy Research and Applications, ICRERA 2012 - Nagasaki, Japan
継続期間: 2012 11 112012 11 14

出版物シリーズ

名前2012 International Conference on Renewable Energy Research and Applications, ICRERA 2012

Conference

Conference1st International Conference on Renewable Energy Research and Applications, ICRERA 2012
Japan
Nagasaki
期間12/11/1112/11/14

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment

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  • これを引用

    Fujimoto, Y., & Hayashi, Y. (2012). Pattern sequence-based energy demand forecast using photovoltaic energy records. : 2012 International Conference on Renewable Energy Research and Applications, ICRERA 2012 [6477299] (2012 International Conference on Renewable Energy Research and Applications, ICRERA 2012). https://doi.org/10.1109/ICRERA.2012.6477299