## 5 Model Application
For the power network, the resulting loads for a time window of 24 h are obtained by multiplying the initial loads by the relative profile depicted in Figure 5 (right plot). All 14 GFPPs in the power grid are physically interconnected to the gas network. Furthermore, we assume additional interconnections between the gas and power network at two compressor stations, at the LNG terminal and at the UGS facility, which are supplied with power from the electric grid. The integrated gas and power network with 18 physically interconnected facilities is illustrated in Figure 4. Additional input parameters for the gas simulator are given in Table 6.  
Applying the simulation tool SAInt on the presented sample network, some preliminary observations on cascading outage contingency analysis can be made. Initially, a base case scenario (scenario 0) with no supply disruption in any of the two interlinked networks is introduced. In the base case scenario, we capture the behavior of the networks at normal operation. Then, we compare the base case scenario with two scenarios, where we introduce a number of disruption events and simulate the reaction of the system to these events. The simulated grid is generated with a time resolution of 900 (s) and all scenarios are simulated for one gas day from 06:00 to 06:00 (For the case study, we chose a simulation time of one operating day (24 h) with a time resolution of 15 min for the gas model and a time resolution of one hour for the power model, in order to keep the size of input data and information at a moderate level for the results discussion. However, the framework is designed to allow an extension and adaptation of the time window and resolution depending on if a short or long term study of a contingency scenario is of interest.) It should be noted that although it is possible to change the status of the failed components (repairing and restoration can be modeled) within the \begin{table}
\begin{tabular}{l c c c} \hline
**Parameter** & **Symbol** & **Value** & **Unit** \\ \hline time step & \(\Delta t\) & 900 & (s) \\ total simulation time & \(t_{max}\) & 24 & (h) \\ gas temperature & \(T\) & 288.15 & (K) \\ dynamic viscosity & \(\eta\) & \(1.1\times 10^{-5}\) & (kg/m\(\cdot\)s) \\ pipe roughness & \(k\) & 0.012 & (mm) \\ reference pressure & \(p_{n}\) & 1.01325 & (bar) \\ reference temperature & \(T_{n}\) & 273.15 & (K) \\ relative density & \(d\) & 0.6 & (-) \\ gross calorific value & \(GCV\) & 41.215 & (MJ/sm\({}^{3}\)) \\ \hline \end{tabular}
\end{table} 
Table 6: Input data for the gas simulator. Figure 5: Load profiles gas (**left** side) and power (**right** side) networks. simulation, the scenarios that are presented in this study do not take into account the repairing activity in order to analyze system capabilities in worst-cases. While the first scenario involves a disruption of several supply points in the gas network, the second scenario includes supply disruptions triggered by the power network. In scenario 1, we assume a reduced regasification rate for the LNG terminal from maximum via a ramp-down between 06:00 and 07:00 (see Figure 6), which corresponds to an expected 7-day delay in cargo. In addition, we assume a supply disruption at the production field causing a ramp down of the supply between 08:00 and 9:00 (see Figure 6). Furthermore, a 30% supply reduction at CBI station at time 14:00 is implemented via a ramp-down between 14:00 and 15:00 (see Figure 6). Scenario 2 is related to power network contingencies and initial contingency set consist of the loss of major lignite power plant with 1157 (MW) operational capacity at 07:00 and 70% lack of power generation from wind turbines at 06:00 (see Figure 6). In the following, we discuss the simulation results for the three scenarios (The simulation results and conclusions are based on the input data chosen for the sample network. While some data were provided by the TSOs, others were not available (e.g., pipe roughness, gas temperature, line properties etc.) and were therefore estimated using typical values.