Where, P_aopt (t)=0.5ρπR^2 C_pmax v^3 is the optimal aerodynamic power and P_e (t) denotes electric power. Table 2 demonstrates that the proposed scheme has better electrical and aerodynamic efficiency. In other words, the presented HPM controller captures the maximum wind power and maximizemaximizes electrical power production. According to this table, the proposed HPM strategy has a lower maximum value and standard deviation of T_ls. Thus, the proposed HPM controller reduces the mechanical loads and mechanical stresses on the drive-traindrivetrain. By examining Table 2, maximum value and standard deviation of T_e are less for HPM controller compared to the NSSFE. This means that the proposed scheme extracts the maximum power from the wind using a small control input. Thus, the proposed HPM controller has better dynamic characteristics and outperformed NSSFE [1].