| Title |
A Short-Term Forecasting Method for Korean REC Spot Market Price Using AI-based Statistical Methodologies |
| Authors |
이성희(Sung-Hee Lee) ; 이우남(Woo-Nam Lee) ; 심상우(Sang Woo Shim) ; 원종집(Jong Jip Won) ; 양유정(Yu Jeong Yang) ; 박종배(Jong-Bae Park) |
| DOI |
https://doi.org/10.5370/KIEE.2023.72.9.967 |
| Keywords |
Renewable Portfolio Standard(RPS); Renewable Energy Certificate(REC); Auto Encoder; Cyclic Pattern; Ensemble |
| Abstract |
In order to respond to climate change, the need for the use of renewable energy is increasing, and as a result, generation companies are obliged to provide part of the generation amount as renewable energy through the RPS system. The mandatory share in RPS system will continue to increase, and it is essential to increase the amount of generation through renewable energy. Purchasing REC is a common way to fulfill obligation because of difficulties for installing power generation facilities to generate renewable energy.
However, in order to purchase REC through a long-term contract, information on future REC prices is essential, and future REC prices can only be identified through forecasting. Therefore, this paper presents a method for forecasting REC prices. The feature for forecasting was configured to consider factors such as renewable energy-related policies, and the stability of the predicted value was presented by using forecasting models with various characteristics. |