Recent large-scale blackouts, such as the Iberian system event, have highlighted the need for robust power system restoration strategies in systems with high shares of inverter-based generation. Offshore wind farms are increasingly being considered for restoration support, especially when combined with onshore battery energy storage systems. This work is developed as part of the SIF BLADE initiative, which focuses on demonstrating restoration from offshore wind.

Previous work carried out as part of the SIF BLADE initiative has assessed the required share of grid-forming and grid-following control using aggregated wind farm models. These approaches do not capture internal wind farm dynamics, including control interactions between turbines and the impact on plant equipment. This paper addresses that gap by representing the wind farm as a collection of individual wind turbine units, each operating either in grid-forming or grid-following mode. This work indicated that an optimal grid-forming penetration lies within a limited range, with both insufficient and excessive grid-forming capability leading to reduced stability. However, such representations do not capture internal wind farm dynamics, including interactions between individual turbines, control coupling, and the impact on plant components during restoration sequences.

Two grid-forming control strategies are considered: virtual synchronous machine and droop-based control, while grid-following units are represented using standard vector current control. For a wind farm with N turbines, the proportion of grid-forming units is varied to assess its impact on system behaviour during restoration. The study investigates whether the optimal share of grid-forming turbines during restoration aligns with that identified for normal operation, and how control strategy influences performance. The study also compares virtual synchronous machine and droop-based control in the context of restoration, assessing whether their differing dynamic characteristics lead to distinct stability limits and operational constraints.

The methodology combines small-signal and large-signal analysis. Small-signal stability is assessed using eigenvalue analysis and disk margins to quantify stability robustness across operating conditions. Large-signal behaviour is evaluated using electromagnetic transient simulations, including fault ride-through, energisation, and black start sequences representative of restoration. The analysis captures internal wind farm interactions and their impact on electrical equipment, including offshore transformers, HVAC export cables, and associated shunt reactors, with focus on transient overcurrents and control interactions between grid-forming units.

The work establishes how grid-forming penetration and control strategy influence stability margins, control interactions, and transient stresses on key plant components during restoration.