8　複数予報データを用いた翌日日射予報の大外し低減手法の検討

DOI

書誌事項

タイトル別名
  • 8　Study on a day-ahead solar power forecast reducing serious overestimation with integrating multiple forecast data

抄録

<p>In power systems where large amounts of photovoltaic power generation have been installed, operational planning is based on next-day solar radiation forecasts. In order to realize efficient and stable power system operation, advanced next-day solar radiation forecasting is necessary, and forecasts must not only have average accuracy but also be able to control the risk of rare large outages. In this study, a multiple solar radiation forecast model using ensemble forecast data was constructed by machine learning, and a forecast model that can both improve the average accuracy and suppress the risk of large over-estimation was investigated.</p>

収録刊行物

キーワード

詳細情報 詳細情報について

  • CRID
    1390580637985065728
  • DOI
    10.24632/jsesc.2023.0_25
  • ISSN
    2758478X
  • 本文言語コード
    ja
  • データソース種別
    • JaLC
  • 抄録ライセンスフラグ
    使用可

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