Morris-Based Optimization of Battery Energy Storage System Control Parameters Under High Wind Energy Penetration

As wind penetration rises, the share of synchronous generation declines, reducing system inertia and increasing uncertainty in frequency stability; wind-output disturbances, power-electronic control characteristics, and stochastic load variations can further amplify frequency deviations caused by power imbalance. To improve frequency security under high wind penetration, this study optimizes BESS control parameters and evaluates their impact on system dynamic stability using a PSS®E V34 dynamic model of the IEEE New England 39-bus system that includes three wind turbines and two BESS units under four disturbance scenarios: (i) derating one turbine to 50%, (ii) tripping one turbine, (iii) derating all three turbines to 50%, and (iv) an N-1 contingency corresponding to the tripping of the largest conventional generator in the system. Morris sensitivity analysis is first applied to identify key parameters affecting frequency response and reduce the optimization dimension, and the selected parameters are then tuned using an improved genetic algorithm (IGA) and grey wolf optimization (GWO). Simulation results show the minimum frequency improves from 59.957 Hz (baseline) to 59.961 Hz with IGA and to 59.966 Hz with GWO, while the maximum equivalent power-angle difference in the BESS unit relative to the center of inertia decreases from 266.3° to 250.1° (IGA) and 251.2° (GWO), indicating that the proposed approach strengthens BESS frequency support and enhances dynamic stability under various wind-power and N-1 contingency disturbance conditions.