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A Deep Learning Model and Training Technique for 240 Hours Load Forecasting in Korea Power System
- Moon, C.-H.;
- Kwon, B.-S.;
- Song, K.-B.
SCOPUS
1초록
It is essential to forecast 240 hours load accurately for stable power system operation in South Korea. Training technique for 240 hours load forecasting using deep learning is proposed. Suitable training technique for 240 hours load forecasting is developed using deep learning model. The 240 hours load forecasting method is proposed applying training technique which consists of two different types for weather prediction. According to usable weather factors depending on forecast ranges, training technique is designed by reflecting time intervals between forecasting time and forecasting target. The proposed method has improved prediction accuracy compared to the existing exponential weighted moving average method. © 2022 Korean Institute of Electrical Engineers. All rights reserved.
키워드
- 제목
- A Deep Learning Model and Training Technique for 240 Hours Load Forecasting in Korea Power System
- 제목 (타언어)
- 한국 전력시스템의 240시간 전력수요예측에 대한 딥러닝 모델과 학습기법
- 저자
- Moon, C.-H.; Kwon, B.-S.; Song, K.-B.
- 발행일
- 2022-04
- 유형
- Article
- 저널명
- 전기학회논문지
- 권
- 71
- 호
- 4
- 페이지
- 585 ~ 591
- 언어
- KOR
- 출판사
- Korean Institute of Electrical Engineers
- 발행국가
- 대한민국
- 분량
- 7 페이지
- ISSN
- E 2287-4364
P 1975-8359