A significant amount of operation and maintenance (O&M) data are being generated daily from offshore wind farms, including a variety of monitoring systems, maintenance reports and environmental sources. The challenge with having a wide variety of data sources with different temporal and format characteristics, is that a significant effort is required to identify evidence that supports a root cause analysis (RCA) of a turbine fault. In addition, the organization of the O&M data flow does not lend itself to support easy reporting of the O&M key performance indicators. Since the offshore wind industry is growing rapidly, there is a need to better understand and manage the O&M data generated. This paper demonstrates a novel integrated data management system that combines all the O&M data from an offshore wind farm and proves that the proposed RCA framework, based on this integrated platform, can lower O&M costs, by reducing the number of visits to the turbines. It also provides failure rates for subassemblies and looks at the failure distribution within the wind farm. The results of the paper will be of interest to offshore wind farm developers and operators to streamline and optimize O&M planning and activities for their assets.
An Integrated Data Management Approach for Offshore Wind Turbine Failure Root Cause Analysis
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Koltsidopoulos Papatzimos, A, Dawood, T, & Thies, PR. "An Integrated Data Management Approach for Offshore Wind Turbine Failure Root Cause Analysis." Proceedings of the ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering. Volume 3B: Structures, Safety and Reliability. Trondheim, Norway. June 25–30, 2017. V03BT02A012. ASME. https://doi.org/10.1115/OMAE2017-62279
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