# Research on Power Cyber-Physical Cross-Domain Attack Paths Based on Graph Knowledge
## 4 Experimental Simulation Analysis  
This article uses IEEE-RTS79 and IEEE-RTS96 system models to carry out experimental simulation analysis. The IEEE RTS79 and RTS96 systems are power system reliability testing systems that can simulate the physical power grid in physical space and are commonly used to analyze, test, and evaluate the reliability of power systems. This paper used this system to verify the impact of attack risks on the operation of the power grid's physical space system after being propagated across space via cyber-physical cross-domain attack paths. The IEEE-RTS79 system consists of a total of 24 nodes and 38 transmission lines, with 32 conventional generating units and a total installed capacity of 3405 MW. The load data is a time series curve composed of the hourly average load, the peak load is 2850 MW, and the load demand of each node is completely positively correlated [25]. The remaining necessary parameters and IEEE-RTS96 system parameters can be directly obtained by consulting the literature [26; 27; 28]. At the same time, in order to describe the operating status of the power grid physical space system, the system load rate, line average load rate, and line load fluctuation coefficient are respectively defined as Formulas (13)-(15). \[\eta_{1}=\frac{\mathrm{P}_{Lnow}}{P_{Lmax}} \tag{13}\]  
\[\eta_{2}=\frac{\sum\limits_{i\in I_{1}}F_{i0}}{\sum\limits_{i\in I_{1}}F_{imax}} \tag{14}\]  
\[\eta_{3}=\sqrt{\sum\limits_{i\in I_{1}}\biggl{(}\frac{F_{i0}}{F_{imax}}-\eta_{ 2}\biggr{)}^{2}} \tag{15}\] \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c} \hline \hline
**Attack Path** & **Risk** & **Attack Path** & **Risk** & **Attack Path** & **Risk** & **Attack Path** & **Risk** & **Attack Path** & **Risk** \\ \hline \(<\)1,v6,v11,v17\(>\) & 2.73 p & \(<\)v1,v7,v14,v17\(>\) & 2.85 p & \(<\)v2,v4,v15,v17\(>\) & 2.68 & \(<\)v2,v8,v13,v17\(>\) & 1.62 p \\ \(<\)v1,v6,v11,v17\(>\) & 2.73 p & \(<\)v1,v7,v15,v17\(>\) & 3.71 p & \(<\)v2,v4,v16,v17\(>\) & 2.11 & \(<\)v2,v8,v14,v17\(>\) & 2.11 p \\ \(<\)v1,v6,v12,v17\(>\) & 2.97 p & \(<\)v1,v7,v16,v17\(>\) & 2.84 p & \(<\)v2,v5,v11,v17\(>\) & 2.68 & \(<\)v2,v8,v15,v17\(>\) & 1.62 p \\ \(<\)v1,v6,v13,v17\(>\) & 1.66 & \(<\)v1,v10,v11,v17\(>\) & 3.9 p & \(<\)v2,v5,v12,v17\(>\) & 2.11 & \(<\)v2,v8,v16,v17\(>\) & 2.28 p \\ \(<\)v1,v6,v14,v17\(>\) & 1.66 & \(<\)v1,v10,v13,v17\(>\) & 2.85 p & \(<\)v2,v5,v13,v17\(>\) & 3.12 & \(<\)v2,v9,v11,v17\(>\) & 1.62 p \\ \(<\)v1,v6,v15,v17\(>\) & 1.9 & \(<\)v1,v10,v15,v17\(>\) & 3.71 p & \(<\)v2,v5,v14,v17\(>\) & 2.33 & \(<\)v2,v9,v12,v17\(>\) & 2.11 p \\ \(<\)v1,v6,v16,v17\(>\) & 1.77 & \(<\)v2,v4,v11,v17\(>\) & 2.84 p & \(<\)v2,v5,v15,v17\(>\) & 2.49 & \(<\)v2,v9,v13,v17\(>\) & 1.63 p \\ \(<\)v1,v7,v11,v17\(>\) & 1.86 & \(<\)v2,v4,v12,v17\(>\) & 3.71 p & \(<\)v2,v5,v16,v17\(>\) & 1.59 p & \(<\)v2,v9,v14,v17\(>\) & 2.11 p \\ \(<\)v1,v7,v12,v17\(>\) & 2.51 p & \(<\)v2,v4,v13,v17\(>\) & 2.85 p & \(<\)v2,v8,v11,v17\(>\) & 1.59 p & \(<\)v2,v9,v15,v17\(>\) & 1.62 p \\ \(<\)v1,v7,v13,v17\(>\) & 3.63 p & \(<\)v2,v4,v14,v17\(>\) & 2.21 & \(<\)v2,v8,v12,v17\(>\) & 1.78 p & \(<\)v2,v9,v16,v17\(>\) & 2.28 p \\ \hline \end{tabular}
\end{table} 
Table 4: Attack path hazard assessment results.