Evaluation of the long-term power generation mix: The case study of South Korea's energy policy

This paper presents a practical portfolio model for the long-term power generation mix problem. The proposed model optimizes the power generation mix by striking a trade-off between the expected cost of power generation and its variability. We use Monte Carlo simulation techniques to consider the uncertainty associated with future electricity demand, fuel prices and their correlations, and the capital costs of power plants. Unlike in the case of conventional power generation mix models, we employ CVaR (Conditional Value-at-Risk) in designing variability to consider events that are rare but enormously expensive. A comprehensive analysis on South Korea's generation policy using the portfolio model shows that a large annual cost is additionally charged to substitute a portion of nuclear energy with other alternatives. Nonetheless, if Korea has to reduce its dependency on nuclear energy because of undermined social receptivity from the Fukushima disaster, it turns out that LNG or coal could be a secure candidate from an economic perspective.