Browsing by Author "Hadjoudj, Yannis"

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    Improving O&M decision tools for offshore wind farm vessel routing by incorporating weather uncertainty
    (Institution of Engineering and Technology (IET), 2023-02-24) Hadjoudj, Yannis; Pandit, Ravi Kumar
    The growth of offshore wind farms depends significantly on how well offshore wind turbines (OWTs) are operated and maintained in the long term. The operation and maintenance (O&M) activities for offshore wind are relatively more challenging due to uncertain environmental conditions than onshore and due to this, vessel routing for offshore on-site repair is remain complex and unreliable. Here, an improved data-driven decision tool is proposed to robust the vessel routing for O&M tasks under numerous environmental conditions. A novel data-driven technique based on operational datasets is presented to incorporate weather uncertainties, such as wind speed, wave period and wave height (significantly influence offshore crew repair works), into the O&M decision-making process. Results show: (1) The inclusion of weather conditions improves the O&M model uncertainty and accuracy, (2) the implementation of a model allowing weather conditions to evolve has been added to vary the probabilities of successful transfers throughout the day, and (3) the reduction of risk of transfer failure by 15%. These conclusions are further supported by the performance error metrics and uncertainty calculations. Last but not least, by generating a variety of policies for consideration, this tool gave wind turbine operators a systematic and transparent way to evaluate trade-offs and enable choices pertaining to offshore O&M. The full paper highlights the strengths and weaknesses of the proposed technique for offshore vessel routing as well as how the environmental conditions affect them.
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    ItemOpen Access
    A review on data-centric decision tools for offshore wind operation and maintenance activities: challenges and opportunities
    (Wiley, 2022-12-13) Hadjoudj, Yannis; Pandit, Ravi
    This paper reviews state-of-the-art numerical tools for the operation and maintenance (O&M) of offshore wind farms, focusing on decision support models for maintenance scheduling and the consideration of human and environmental uncertainty. In this review, various factors that can influence the successful conduct of maintenance operations will be examined and special attention will be paid to the most significant ones. Data-driven technologies for improved offshore asset management are also examined and the most used data-driven methods for modelling and optimising turbine operation and maintenance are presented. A focus will be placed on the choice of maintenance strategy, which is the basis for the planning of operations and thus the optimisation problem discussed. As offshore maintenance is a complex operation whose efficiency and safety depend on human and environmental factors, special attention will be paid to the planning strategy that minimises the risks involved while maximising efficiency by considering these factors. The choice of planning technique for turbine maintenance and better consideration of uncertainties are crucial areas of improvement as they can lead to better overall efficiency, higher profit margins, better safety, and improved sustainability of offshore wind farms. The paper covers the application of digital technologies for offshore wind O&M planning and the associated challenges. The paper also highlights the various environmental and human factors to be considered for the operation and maintenance of wind turbines.