Stability Improvement of Grid-Connected DFIG Wind Farm With STATCOM Compensated Power Network Using RL-Based Coordinated Transient Controller

This paper focuses on improving the stability of a power network (PN) with an embedded DFIG-based wind farm (DWF) using the power system stabilizer (PSS) and STATCOM. The stability of the rotor angle (RAS) is improved by determining the optimal PSS type based on the minimum value of the sum of the maximum deviations of the rotor angle (SMRAD). The optimum allocation of DWF through an artificial neural network (ANN) reduces the power loss. The voltage stability (VS) is improved by the optimal allocation of STATCOM, considering the VS index and the voltage enhancement index. Moreover, a novel reinforcement learning-based coordinated transient controller (RL-CTC) is proposed for regulating the reactive power compensation between DWF and STATCOM to augment the voltage and rotor angle stability (VRAS). The deep deterministic policy gradient agent approach is used to maximize performance for the RL-CTC tuning process. The dynamic efficacy of the RL-CTC is analyzed against several voltage disturbances with different combinations of PSS, DWF, and STATCOM using the IEEE-9 bus system. The results presented in the paper show that the proposed strategy enhances the system’s overall stability by improving the RAS, and zero, low, and high voltage ride through capabilities. The suggested strategy can be used to optimize PSS and STATCOM parameters to solve VRAS issues in a PN integrated with renewable generation.