# Development of Energy Storage Systems for High Penetration of Renewable Energy Grids
## 4 Frequency Regulation Technology Simulation
### Analysis of Frequency Regulation Technologies  
This paper discusses the evaluation of proposed strategies based on the simulation results. The comparison factors of the strategies include the RoCoF, frequency nadirs, frequency recovery, and system oscillation regulation. The capability of limiting the RoCoF is evaluated using the output power of the battery energy storage system when the fault occurs. The capability to mitigate frequency nadirs is evaluated based on the simulation results of N-1 events. The capability of frequency recovery is determined by the interval of the grid frequency nadir to the steady-state frequency. The capability of the system oscillation regulation is determined by the frequency regulation before a fault occurs. According to the simulation results of the light load scenario, the biggest frequency deviation is 0.496 Hz. The sReg strategy is best among RoCoF limitations. The simulation results of the steady-state frequency and energy of battery energy storage systems are shown in Table 7. The inertia energy is defined as the output power that the battery energy storage system provides in the 0.2 s after the N-1 event occurs. In the light load scenario, the energy of the battery energy storage system under the virtual inertia strategy is 13.40 MJ. In the peak load scenario, the energy of the battery energy storage system under the virtual inertia strategy is 10.73 MJ. The energy of the battery energy storage system under static regulation strategy is maximum at 25.83 MJ for the peak load scenario. Therefore, the virtual inertia strategy and the static regulation strategy have a better limiting capability for RoCoF compared to dReg 0.25 and dReg 0.5. In the light load scenario, the steady-state frequency under the static regulation strategy is 59.868 Hz, and the steady-state frequency under the dReg 0.25 strategy is 59.841 Hz. In the peak load scenario, the steady-state frequency under the dReg 0.25 strategy is 59.878 Hz, and the grid frequency under the static regulation strategy is not in the steady state. However, the steady-state frequency under the virtual inertia strategy decreases compared to the steady-state frequency without any strategy. The capability of system oscillation regulation is determined by the frequency of the deadband range. Before the fault occurs, the RoCoF is small, indicating that the output power of the virtual inertia strategy is small. The dReg 0.25 and dReg 0.5 strategies have droop gain, so the capability of the system oscillation under the dReg strategy is better than it is under the other strategies. A comparison of the proposed strategies under the battery energy storage system is shown in Table 8. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Strategy Name** & **Frequency Nadir (Hz)** & **Deviation (Hz)** \\ \hline None & 59.588 & 0 \\ dReg 0.5 & 59.726 & 0.138 \\ dReg 0.25 & 59.789 & 0.201 \\ sReg & 59.868 & 0.280 \\ Virtual inertia & 59.633 & 0.045 \\ Control @ H = 40 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Simulations of grid frequency for 2025 peak load scenario. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Strategy Name**} & \multicolumn{2}{c}{**Light Load Scenario**} & \multicolumn{2}{c}{**Peak Load Scenario**} \\ \cline{2-5}  & **Energy (M)** & \
\begin{tabular}{c} **Steady-State** \\ **Frequency (Hz)** \\ \end{tabular} & **Energy (M)** &
\begin{tabular}{c} **Steady-State** \\ **Frequency (Hz)** \\ \end{tabular} \\ \hline None & - & 59.705 & - & 59.816 \\ dReg 0.5 & 4.73 & 59.794 & 3.52 & 59.853 \\ dReg 0.25 & 7.92 & 59.841 & 6.00 & 59.878 \\ sReg & 2.23 & 59.868 & 25.83 & - \\ Virtual inertia & 13.40 & 59.687 & 10.73 & 59.815 \\ Control & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 7: The simulation results of steady-state frequency and energy of the battery energy storage system.