An innovative OANF-IPFC based on MOGWO to enhance participation of DFIG-based wind turbine in interconnected reconstructed power system An innovative OANF-IPFC based on MOGWO to enhance participation of DFIG-based wind turbine

Despite the affordability and popularity of doubly fed induction generator (DFIG) among the variable-speed wind turbines, it cannot follow the inertia response caused by the load perturbations and the imposed frequency fluctuations in the power system. Considering the growing participation of wind power generation, DFIG with no virtual inertia control cannot play a functional role in the frequency stability of traditional power systems. At the outset, a new inertia control strategy is proposed for DFIG to participate in system frequency control via absorption or disposal of kinetic energy based on active power control. Then after that, interline power flow controller (IPFC) known as an adaptable and complex compensator is introduced to simultaneously regulate and control the power flow of multiple lines during the large penetration of DFIGs. To enhance the damping capability of IPFC, this paper has suggested a novel optimal adaptive neuro-fuzzy (OANF). The frequency and tie-line power deviations as two prominent stability benchmarks have been considered and analysed to appraise the damping capability of the suggested controller in the affected interconnected power system. The dynamic stability problem has been formulated based on multi-objective grey wolf optimizer to optimally tune OANF-based IPFC towards simultaneous suppression of the abovementioned benchmarks. The accurate fuzzy membership functions and rules of OANF-based IPFC have been extracted during the severe perturbation in two interconnected reconstructed power systems. Eventually, the simulation results extracted from both the three-area and five-area interconnected power systems have primarily validated the inertia control-based DFIG and subsidiarily OANF-IPFC to effectively suppress the low-frequency oscillations.