Reliability assessment of wind energy islands from a probabilistic design perspective

High reliability is critical for the operation of large-scale offshore infrastructures, such as energy islands. This paper presents a probabilistic reliability assessment framework for a 3 GW energy island in the Baltic Sea, integrating Fault Tree Analysis (FTA), Monte Carlo Simulations (MCS), and Power Transfer Analysis (PTA). While the island design follows the deterministic N−1 criterion, the probabilistic approach provides deeper insight into component-level vulnerabilities, island-wide resilience, and reliability perspectives of individual mainlands. Results indicate that Wind Turbines (WTs) and Double Bus Single Breakers (DBSBs) contribute most to energy losses, even though the overall system exhibits nearly perfect time availability. Production availability across the island remains high (99.98%), but individual mainlands experience uneven reliability due to asymmetries in transmission paths. Sensitivity analysis demonstrates that enhancing turbine repair rates and adding redundancy in Offshore Substations (OSSs) substantially reduces energy losses, whereas reductions in OSS redundancy lead to disproportionate penalties. The findings confirm that, although compliance with the N−1 criterion ensures basic reliability, probabilistic assessment provides additional insights for optimising investment decisions and designing more robust offshore grid infrastructures.