| 저자(한글) |
전병기,이경호,김의종,인하대학교 대학원 건축공학과,한국에너지기술연구원,인하대학교 건축공학과 |
| 저자(영문) |
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| 소속기관 |
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| 소속기관(영문) |
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| 출판인 |
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| 간행물 번호 |
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| 발행연도 |
2019-01-01 |
| 초록 |
The purpose of the work is to develop a simple solar irradiance prediction model using a deep learning method, the LSTM (long term short term memory). Other than existing prediction models, the proposed one uses only the cloudiness among the information forecasted from the national meterological forecast center. The future cloudiness is generally announced with four categories and for three-hour intervals. In this work, a daily irradiance pattern is used as an input vector to the LSTM together with that cloudiness information. The proposed model showed an error of 5% for learning and 30% for prediction. This level of error has lower influence on the load prediction in typical building cases. |
| 원문URL |
http://click.ndsl.kr/servlet/OpenAPIDetailView?keyValue=03553784&target=NART&cn=JAKO201932569574292 |
| 첨부파일 |
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