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.

• 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