SOPF-Based Adaptive Droop Control for Hybrid AC–HVDC Grids Under Offshore Wind Uncertainty

Abstract

The integration of massive offshore wind into hybrid AC-HVDC grids demands robust DC voltage regulation, yet conventional fixed-gain droop controllers struggle under severe stochastic volatility. This paper bridges the gap between system-level dispatch and converter-level control by proposing a Stochastic Optimal Power Flow (SOPF)-based adaptive droop framework. Rather than relying on heuristic or reactive tuning, wind forecast uncertainty is modeled using a zone-wise Beta distribution that accurately captures the heteroscedastic nature of wind errors across low, mid, and high-power regimes. By leveraging Polynomial Chaos Expansion (PCE) within a chance-constrained SOPF, the system’s stochastic states are formulated analytically. Crucially, the adaptive droop gain is extracted directly from the first-order PCE coefficients through a sensitivity analysis, transferring the probabilistic voltage-security information of the stochastic dispatch to the local converter control. Validation on a 4-terminal AC-HVDC system demonstrates that scenario-adaptive gains significantly outperform standard fixed-coefficient approaches, effectively minimizing active-power tracking errors during extreme wind disturbances.