## 6 Conclusions  
To solve the SSO problem, this paper proposes an optimized additional damping method for the rotor- and grid-side control system of the DFIG, which can suppress the SSO successfully under variable operating conditions. First, the impedance model of the DFIG is established. Subsequently, a joint optimization strategy with SDC on both the grid and the rotor sides is proposed. Finally, the model is verified. The verification results show the following:  
* An innovative optimization method based on coordinated control of the rotor and grid sides was proposed. Compared with the method of adding an SDC on only one side of the rotor or grid control system, the combined optimization effect was better, with an amplitude suppression rate reaching 85.99%, which can more effectively solve the SSO problem existing in the doubly fed wind power grid-connected system via series compensation.
* The genetic algorithm was used to optimize the design of the parameters of the SDC. Through the optimization algorithm, optimized suppression under all operating conditions can be achieved with different series compensation degrees, wind speeds, and numbers of wind turbines.
* The experimental module was established on the RTLAB platform to simulate the experimental effects under different operating conditions and conduct the simulation research. The experimental results are consistent with theoretical derivations, and the experimental conclusions provide a reference value for the setting of various parameter thresholds in engineering practice.  
In summary, the SSO suppression method for doubly fed wind turbines based on the GA proposed in this paper has a certain practical application value in addressing the challenges of power system stability and security, and also features both economy and convenience. It provides a guarantee for the safe and stable operation and efficient power transmission of wind farms and offers new ideas for the integration of artificial intelligence into new power systems.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Group** & **SDC Location** & \(\mathbf{K_{g}}\) & \(\mathbf{T_{g}}\) & \(\mathbf{K_{r}}\) & \(\mathbf{T_{r}}\) & \(\mathbf{\beta}\) \\ \hline \multirow{4}{*}{1} & GSC & \(-10\) & \(0.2\) & - & - & \(31.09\%\) \\ \cline{2-7}  & RSC & - & - & \(-30\) & \(0.2\) & \(21.77\%\) \\ \cline{2-7}  & GSC + RSC & \(-10\) & \(0.2\) & \(-30\) & \(0.2\) & \(37.14\%\) \\ \hline \multirow{4}{*}{2} & GSC & \(-25\) & \(0.5\) & - & - & \(58.88\%\) \\ \cline{2-7}  & RSC & - & - & \(-60\) & \(0.5\) & \(52.73\%\) \\ \cline{2-7}  & GSC + RSC & \(-25\) & \(0.5\) & \(-60\) & \(0.5\) & \(65.58\%\) \\ \hline \multirow{4}{*}{3} & GSC & \(-50\) & \(0.8\) & - & - & \(75.72\%\) \\ \cline{2-7}  & RSC & - & - & \(-70\) & \(0.8\) & \(56.27\%\) \\ \cline{2-7}  & GSC + RSC & \(-50\) & \(0.8\) & \(-70\) & \(0.8\) & \(78.22\%\) \\ \hline \multirow{4}{*}{4} & GSC & \(-64\) & \(0.95\) & - & - & \(83.31\%\) \\ \cline{2-7}  & RSC & - & - & \(-100\) & \(0.95\) & \(73.35\%\) \\ \cline{2-7}  & GSC + RSC & \(-64\) & \(0.95\) & \(-100\) & \(0.95\) & \(85.99\%\) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Comparison of the effects of different SDC addition positions.