## 3 Methodology and Simulation Framework
### Simulation Design and Input Data
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Category**} & **Installed Capacity** & **Average Generation** & **Average Annual** \\  & **(MW)** & **Costs (KRW/kWh)** & **Maintenance Days** \\ \hline Nuclear & 25,782 & 6.37 & 70 \\ \hline Coal & 37,934 & 101.11 & 42 \\ \hline LNG & 49,061 & 180.01 & 28 \\ \hline Oil & 112 & 330.18 & 42 \\ \hline Hydropower & 1484 & 0 & 0 \\ \hline Pumped Storage & 4700 & 0 & 35 \\ \hline Solar PV & 26,652 & 0 & 0 \\ \hline Wind & 2214 & 0 & 0 \\ \hline Other Renewables & 2448 & 0 & 0 \\ \hline \hline \end{tabular} Note: KRW denotes Korean Won. As of 6 September 2024, 1 USD = 1335.90 KRW [40].  
\end{table} 
Table 3: Summary of generator data. The proposed modeling approach accommodated seven proposed pricing schemes while maintaining a consistent underlying system representation. In nodal pricing, the system representation remained unchanged, thereby preserving the detailed node-level granularity. For zonal and uniform pricing, the generators and loads were aggregated according to their respective zones, and the transmission capacity connecting different bidding zones was represented by the sum of the thermal limits of all transmission lines crossing from one zone to the other [31]. Because of this zonal aggregation, only interzonal power flows were considered, whereas intrazonal power flows were omitted from the model [42]. In addition to these general modeling approaches, each pricing scheme had specific assumptions and modeling considerations, as follows. 1. Nodal (LMP) and Nodal (ELMP): As explained in Section 2, Nodal (LMP) and Nodal (ELMP) refer to the results of the SCED and SCED-pricing, respectively, following SCUC execution. In our study, for the SCUC, all transmission lines were considered watchlist transmission sets. The MIP gap tolerance for SCUC was set at 0.1% as per the MISO market rules [36], compared to the typical 0.0001%. The DC-OPF for nodal pricing employed a distributed slack bus model. 2. Nodal (ELMP): While MISO considers generators capable of starting within 1 h or less with a minimum run time of 1 h or less as FSRs, such resources are scarce in the Korean electricity market. Therefore, this study expanded the FSR qualification to resources with a minimum runtime of 4 h or less for a Nodal (ELMP) scheme simulation. 3. 5-Zonal (FBMC, ZMP): For the 5-Zonal (FBMC, ZMP), the characteristics of the transmission lines connecting different zones were estimated. Specifically, their resistance and reactance were calculated using PSS/E-based system reduction techniques. 4. Bidding strategy: The current Korean electricity market operates on a cost-based pool system, wherein generators are required for bidding based on marginal costs. However, under pricing mechanisms, such as ZMP, LMP, and ELMP, generators generally submit price bids that are at least sufficient to recover the opportunity costs associated with invested capital, such as the time value of money during the production period. In this study, for schemes adopting ZMP, LMP, and ELMP mechanisms, we assumed a weighted average cost of capital (WACC) of 5.5% and a 3-month capital