Session: Session 3. Integrity Management of Critical Systems

Paper Number: 118871

118871 - A Generalized Advanced Digital Technologies Framework for Fixed Foundation Offshore Wind Applications 

With the recent surge in installed offshore wind capacity around the world and the ever increasing global aspirations for increasing offshore wind deployment, there are numerous efforts focusing on reducing the levelized cost of energy (LCOE) for offshore wind systems, mainly concentrating on reduction of the upfront capital expenditures.  In contrast, this paper will explore a generalized framework to support advanced digital technology applications, such as structural health monitoring (SHM) and condition-based maintenance (CBM), with respect to the operations and maintenance of offshore wind assets to sustain the expected LCOE and increase the efficiency of operational expenditures.  Specifically, this paper will focus on fixed bottom offshore wind installations and look to address additional requirements and challenges with floating offshore wind installations in a future publication. 

This paper will review lessons learned from the offshore oil and gas and the electric power generation industries to demonstrate the relevance of a generalized framework for multiple operations and maintenance applications and to support the implementation of advanced digital applications.  The key challenges to overcome in implementation strategies, such as data types and intervals, data governance policies, cyber-security considerations, and data management practices, will be illustrated through industry relevant examples and references to specific applications. 

The fundamental asset classes for an offshore wind farm and advanced sensing technologies for them will be reviewed.  Such assets include: the rotor nacelle assembly (RNA) including blades as separate assets, substructures and foundations, offshore substations, and cable systems including array and export cables.  Parallels will be drawn to success in the oil and gas industry where the American Petroleum Institute (API) has developed integrity management recommended practices to support the operations and maintenance of risers, moorings, structures, etc., as well as several other efforts in the electrical power generation space focused on thermal generation assets. 

The generalized framework will present a relational input and output bow-tie concept and outline specific industry needs to support implementation and broader industry adoption.  The purpose of the generalized framework is to build the foundational understanding of the potential data types from each asset, interdependencies in data and information between assets, and information available within the data for decision making to enable the layering of higher level advanced digital applications on top of the framework to enable increased understanding of the asset’s performance and reliability. 

Multiple digital technology applications will be reviewed, including applications of machine learning and artificial intelligence in support of information extraction, data consolidation and autonomous decision making, methods for sensor reduction through shared data and extrapolation, and the potential applications for digital twins within the offshore wind space.  The paper will draw parallels and references to successes in other industries that have been able to develop common frameworks to achieve positive results.  Specific applications of these advanced digital technologies will be illustrated through the ongoing research and development on machine learning applications to blade inspection and advanced structural health monitoring techniques for fixed bottom foundations. 

Finally, the paper will address potential pathways forward through standardization efforts and industry collaboration to realize the benefits of common frameworks to support the offshore wind industry in the transition to large scale operations. 

Presenting Author: William Walker Stress Engineering Services Inc.

Presenting Author Biography: Experienced professional with a demonstrated history of design and analysis for offshore structures and systems, including oil and gas and offshore wind applications. His skills are focused, but not limited to finite element analysis, strength analysis and fatigue analysis, including strengths in data analysis for condition and health monitoring. Experience with industry accepted software including MATLAB, ABAQUS and ANSYS. He holds B.S., M.S., and Ph.D. degrees, all in aerospace engineering and all from Virginia Tech.