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머신러닝을 이용한 수상태양광 발전량 예측에 관한 연구 A Study on the Prediction of Floating Photovoltaic System using Machine Learning

이정우, 고아름, 김대호, 김시경
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  • URLhttp://db.koreascholar.com/Article/Detail/432329
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한국기계기술학회지 (韓國機械技術學會誌)
제26권 제1호 (2024.02)
pp.142-148
한국기계기술학회 (Korean Society of Mechanical Technology)
초록

The government is implementing a policy to expand eco-friendly energy as a power source. However, the output of new and renewable energy is not constant. It is difficult to stably adjust the power supply to the power demand in the power system. Therefore, the government predicts day-ahead the amount of renewable energy generation to cope with the output volatility caused by the expansion of renewable energy. It is a system that pays a settlement amount if it transitions within a certain error rate the next day. In this paper, Machine Learning was used to study the prediction of power generation within the error rate.

키워드
신재생에너지수상태양광 Renewable energyFloating photovoltaic system
저자
  • 이정우(Dept. of Electrical Engineer, K-water, Korea) | Jeong-Woo Lee
  • 고아름(Research Institute of 60 Hertz Inc., Korea.) | A-Reum Ko
  • 김대호(Research Institute of 60 Hertz Inc., Korea.) | Dae-Ho Kim
  • 김시경(Dept. of Electrical and Electronic Engineering, Kongju National University, Korea.) | Si-Gyung Kim Corresponding author