It is necessary to predict peak load accurately in order to supply electric power and operate the power system stably. Especially,it is more important to predict peak load accurately in winter and summer because peak load is higher than other seasons....
It is necessary to predict peak load accurately in order to supply electric power and operate the power system stably. Especially,it is more important to predict peak load accurately in winter and summer because peak load is higher than other seasons. If peakload is predicted to be higher than actual peak load, the start-up costs of power plants would increase. It causes economic loss to thecompany. On the other hand, if the peak load is predicted to be lower than the actual peak load, blackout may occur due to a lackof power plants capable of generating electricity. Economic losses and blackouts can be prevented by minimizing the prediction errorof the peak load. In this paper, the latest deep learning model such as TCN is used to minimize the prediction error of peak load. Evenif the same deep learning model is used, there is a difference in performance depending on the hyper-parameters. So, I propose methodsfor optimizing hyper-parameters of TCN for predicting the peak load. Data from 2006 to 2021 were input into the model and trained,and prediction error was tested using data in 2022. It was confirmed that the performance of the deep learning model optimized bythe methods proposed in this study is superior to other deep learning models.