Proceedings of JSES conference
Online ISSN : 2758-478X
JSES Conference (2023)
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8 Study on a day-ahead solar power forecast reducing serious overestimation with integrating multiple forecast data
*Takahiro TAKAMATSUKou NAKAJIMAHideaki OHTAKETakashi OozekiKoji YAMAGUCHI
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CONFERENCE PROCEEDINGS FREE ACCESS

Pages 25-28

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Abstract

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.

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© Japan Solar Energy Society
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