Towards wind farm droop-inertia feasible region assessment: A state space transformation approach considering power system dynamics

•Data-driven state space transformation is developed to construct a frequency regulation capability assessment model.•Coordinated iteration framework exploits the frequency regulation capability and optimizes feasible region.•Alternative direction search method constructs feasible region in seconds. Increasing penetration of renewable resources integrated into power systems has necessitated frequency support from wind farms. Considering the complex interaction of wind turbines (WTs) and time-variant frequency dynamics of power systems, it is necessary to assess the primary frequency regulation (PFR) capability and construct feasible regions for wind farms. In order to cope with the challenges of incomplete parameters in physical-based methods and inadequate interpretability in existing data-driven methods, this paper develops a data-driven state space transformation model for wind farms to construct feasible regions of droop and inertia coefficients. Meanwhile, the optimal coefficients are determined by using an alternative direction search (ADS) scheme, which are utilized to construct approximate feasible region with high solution efficiency. Furthermore, a coordinated iteration framework between system operator and multiple wind farms is proposed to fully exploit the frequency support capability. The simulation results validate that the proposed method has the advantages of fast analytical solving, independence from physical parameters, and lower requirements of training data.