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Blackstart strategies with grid forming offshore Type-IV wind turbines and BESS for effective system restoration

Year: 2026
Type: article
Abstract: The increasing penetration of converter-interfaced generation motivates restoration strategies that can establish and regulate voltage and frequency during blackstart. This paper evaluates blackstart of an offshore wind farm using grid-forming (GFM) Type-IV wind turbines and battery energy storage systems (BESS), and compares four energization methods: (i) offshore diesel generator (DG) at the offshore PCC, (ii) offshore GFM-BESS at the offshore PCC, (iii) WT-assisted start using WT-integrated GFM-BESS followed by sequential turbine energization, and (iv) onshore GFM-BESS initiating restoration from the onshore side. Detailed EMT simulations in PSCAD follow explicit staged energization sequences of cables, transformers, and loads, enabling a consistent cross-method assessment of transient behavior. As a key contribution, the paper introduces an objective benchmarking framework based on measurable restoration indicators and applies it to quantify voltage and frequency containment and transient stress across methods. Results show that placing GFM capability offshore or at the turbine level yields the most robust restoration trajectories, including successful operation without offshore damping load, whereas DG-based and onshore-initiated strategies exhibit higher sensitivity to corridor charging and resonance-driven transients. The findings provide quantitative guidance for selecting practical blackstart architectures for offshore wind power plants. • Proposes four blackstart strategies using offshore wind turbines and battery storage systems. • Develops PSCAD models to analyze energization sequences, voltage, and frequency stability. • Demonstrates offshore GFM-BESS and WT-BESS can restore grids even without auxiliary load. • Compares all methods, showing offshore BESS offers fastest and most stable restoration.
Language: English
Open Access status: gold
Estimated APC paid: $3,920
OpenAlex ID: W7154266990
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Cites: 20
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