음수 가격이 존재하는 제주 전력 시장에서의가상발전소 최적 입찰 결정 모형

With the rapid expansion of renewable energy in recent years, the existing electricity market has been increasingly exposed to greater volatility and uncertainty. Consequently, relying solely on the day-ahead market has been criticized for its limited ability to effectively respond to real-time supply-demand fluctuations. Against this backdrop, the Korea Power Exchange introduced a dual-market system in the Jeju region, in which a real-time market operates alongside the day-ahead market, and granted bidding rights to renewable energy resources. This institutional change has created the need to explore bidding strategies that can maximize profits within this market structure. To address this, this study models the Jeju power market as a three-stage stochastic programming problem. Probability distributions are constructed for key sources of uncertainty—such as electricity prices and renewable energy output—and methods for generating scenarios for use in stochastic programming are presented. Numerical experiments using data from the Jeju pilot power market demonstrate that the proposed model outperforms a deterministic optimization model based solely on forecast values in terms of profitability, while also exhibiting practical computational efficiency. These findings suggest that the proposed methodology is applicable in real-world operations under uncertainty and is expected to contribute to enhancing the flexibility and stability of future power markets.