## 5 Conclusions  
In this paper, a robust control method has been designed for the coordinated control of LFC and SMES using the FOPD-FOPID controller. The DOSA algorithm, which has many advantages over other optimization algorithms, was used to adjust the parameters of the proposed controller. The proposed method in this paper is compared with other methods presented in the field of power system frequency control in the presence of wind turbines. The proposed method was able to improve the MFD and ST related to frequency deviations in the power system caused by load disturbances and wind turbine disturbances by 50% and 17%, respectively, compared to other methods presented in this field (frequency control). The proposed method has been able to improve the MFD and ST related to frequency deviations in the power system caused by load disturbances, wind turbine disturbances, and slight uncertainty of parameters (H = \(-\%\)25) by 45% and 18%, respectively (compared to other methods presented in the field of frequency control). The proposed method improved the MFD and ST related to frequency deviations in the power system caused by load disturbances, wind turbine disturbances, and extreme uncertainty of parameters (H = \(-\%\)50) by 45% and 18%, respectively (compared to other methods presented in the field of frequency control). To continue the work of this paper in the future, several suggestions can be made, including: (1) Combining the FOPD-FOPID controller with a neural network and using it in different parts of the power system, (2) Investigating the possibility of using the FOPD-FOPID controller in power systems Smart, (3) checking the performance of the FOPD-FOPID controller in case of faults in the power system and defects in other system components.  
F.A.: methodology, resources investigation, writing--original draft, conceptualization, methodology, visualization. M.E.: investigation, review and editing, conceptualization, formal analysis. M.H.M.: validation, supervision. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Australian Research Council, DP190102501.  
**Data Availability Statement:** Data are contained within the article.  
**Acknowledgments:** National Elites Foundation.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{2}{c}{**Controller**} & \multicolumn{1}{c}{**Scenario (1)**} & \multicolumn{1}{c}{**Scenario (2)**} & \multicolumn{1}{c}{**Scenario (3)**} & \multicolumn{1}{c}{**Scenario (4)**} \\ \hline \multirow{3}{*}{Proposed controller} & MO (Hz) & 0.0001 & 0.00035 & 0.00037 & 0.00038 \\ \cline{2-6}  & MU (Hz) & 0.0009 & 0.0007 & 0.00075 & 0.00079 \\ \cline{2-6}  & ST (s) & 4.2 & 3.55 & 3.76 & 3.93 \\ \hline \multirow{3}{*}{Controller 1} & MO (Hz) & 0.0004 & 0.0008 & 0.0009 & 0.0010 \\ \cline{2-6}  & MU (Hz) & 0.00184 & 0.00152 & 0.001631 & 0.001724 \\ \cline{2-6}  & ST (s) & 5.05 & 4.461 & 4.492 & 4.492 \\ \hline \multirow{3}{*}{Controller 2} & MO (Hz) & 0.00421 & 0.00341 & 0.0053 & 0.0092 \\ \cline{2-6}  & MU (Hz) & 0.01734 & 0.00816 & 0.01066 & 0.01578 \\ \cline{2-6}  & ST (s) & 19.03 & 21.24 & 24.53 & 25.22 \\ \hline \multirow{3}{*}{Controller 3} & MO (Hz) & 0.00643 & 0.00582 & 0.0127 & 0.0146 \\ \cline{2-6}  & MU (Hz) & 0.0214 & 0.01291 & 0.01708 & 0.01975 \\ \cline{2-6}  & ST (s) & 38.12 & 37.39 & 42.11 & 46.25 \\ \hline \multirow{3}{*}{Controller 4} & MO (Hz) & 0.0476 & 0.023 & 0.0367 & — \\ \cline{2-6}  & MU (Hz) & 0.04667 & 0.02565 & 0.03363 & — \\ \cline{1-1} \cline{2-6}  & ST (s) & 90.1 & 45.03 & 48.21 & — \\ \hline \hline \end{tabular}
\end{table}
Table 4: Performance results of different control methods for four scenarios.