Techno-economic assessment for robotics-driven inspection of floating offshore wind farms
Loading...
Files
Full Text E-thesis
Date
2025
Authors
Khalid, Omer
Journal Title
Journal ISSN
Volume Title
Publisher
University College Cork
Published Version
Abstract
The floating offshore wind farm (FOWF) industry is poised for substantial growth, necessitating efficient operations and maintenance (O&M) practices. There is an ever-evolving need to overcome operational challenges such as restricted weather windows, long-distance logistical strategies, and the need for cost-effective and feature-rich data acquisition. This thesis explores the integration of robotic systems into the FOWF-specific O&M activities from a techno-economic perspective, revealing several key insights. Robotic systems such as unmanned aerial vehicles (UAVs) and remotely operated vehicles (ROVs) can provide several benefits in terms of enhancing the O&M vector. These include improved safety and efficiency for longer duration missions and operability under harsh weather conditions, while advanced sensors and data acquisition technologies, such as thermographic cameras, provide feature-rich data as compared to the traditional manned
visual inspections. AI and data-driven approaches can improve resource management and asset availability through automated data gathering and retrieval, and modular designs of climbing robots and UAVs equipped with mission-specific sensors can further aid in carrying out various inspection tasks.
This thesis explores the use of the WOMBAT tool, and devises a cost estimation framework for an offshore multi-robot platform (MRP) inspecting a large-scale FOWF highlighting potential cost and inspection time reductions. Furthermore, key variables are identified that impact operational expenditure (OPEX) and time-to-completion, suggesting initial utilization of fewer MRPs to balance costs and the inspection duration. Furthermore, simulations incorporating unmanned surface vehicles (USVs), ROVs, and UAVs for FOWF inspections indicate long-term cost savings from early adoption of higher autonomy levels, with real options analysis (ROA) emphasizing flexible investment approaches to adapt to market dynamics. The ROA demonstrates the strategic advantage of adopting higher autonomy levels earlier in a project’s lifecycle, emphasizing the importance of flexible investment approaches in the face of market and technological un-
certainties.
The cost-benefit analysis has been complemented with assessing the technical feasibility of UAV-based automated detection of wind turbine blade damages. Performance evaluation using visible and thermal imaging shows significant benefits, with thermal imaging identifying deeper structural erosion on the blades and combined imaging modalities effectively assessing damage severity. Lastly, a model-based systems engineering (MBSE) framework for deploying robotics-driven FOWF inspections is presented. This framework integrates system requirements with software and hardware design, facilitating end-to-end traceability and coherence. Identifying potential deployment roadblocks, such as system requirements and architecture, along with prioritizing risk mitigation efforts through failure modes and effects analysis (FMEA), inculcates the importance of incorporating advanced robotic systems in the FOWF sector, in a holistic manner. This thesis supports the integration of these methodologies to enhance the integrity and reliability of the FOWF infrastructure, and hence, contributes towards the overall economical and environmental sustainability efforts.
Description
Keywords
Floating offshore wind farm , Robotics , Inspection , Cost modelling , Techno-economic assessment
Citation
Khalid, O. 2025. Techno-economic assessment for robotics-driven inspection of floating offshore wind farms. PhD Thesis, University College Cork.