Fault detection and isolation benchmark for floating offshore wind farms

Abstract

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This paper presents a benchmark for fault detection and isolation (FDI) in floating offshore wind farms, addressing the lack of standardized evaluation frameworks for this emerging technology. Developed using the FOWLTY simulator, the benchmark models a wind farm with seven floating turbines based on the NREL 5MW reference turbine and DeepCWind platform. It incorporates ten diverse wind scenarios (5-23 m/s) and realistic fault conditions, including sensor and actuator faults with variable severity and timing. The benchmark provides sensor measurements with injected noise, actuator reference signals, and evaluation metrics such as false alarm rate (FAR), missed detection rate (MDR), and correct isolation rate. By offering a modular Simulink environment and customizable datasets, this work enables reproducible comparisons of FDI methods while highlighting the unique dynamics of floating offshore systems. The benchmark is publicly available to support research in fault detection and fault-tolerant control for offshore wind energy.

This work was not supported by any organization.

Peer Reviewed

Postprint (author's final draft)