کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5474113 | 1520645 | 2017 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Testing the robustness of optimal access vessel fleet selection for operation and maintenance of offshore wind farms
ترجمه فارسی عنوان
تست قابلیت اطمینان از انتخاب ناوگان ناوبری دسترسی بهینه برای بهره برداری و نگهداری از مزارع بادی دریایی
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی دریا (اقیانوس)
چکیده انگلیسی
Optimising the operation and maintenance (O&M) and logistics strategy of offshore wind farms implies the decision problem of selecting the vessel fleet for O&M. Different strategic decision support tools can be applied to this problem, but much uncertainty remains regarding both input data and modelling assumptions. This paper aims to investigate and ultimately reduce this uncertainty by comparing four simulation tools, one mathematical optimisation tool and one analytic spreadsheet-based tool applied to select the O&M access vessel fleet that minimizes the total O&M cost of a reference wind farm. The comparison shows that the tools generally agree on the optimal vessel fleet, but only partially agree on the relative ranking of the different vessel fleets in terms of total O&M cost. The robustness of the vessel fleet selection to various input data assumptions was tested, and the ranking was found to be particularly sensitive to the vessels' limiting significant wave height for turbine access. This is also the parameter with the greatest discrepancy between the tools, implying that accurate quantification and modelling of this parameter is crucial. The ranking is moderately sensitive to turbine failure rates and vessel day rates but less sensitive to electricity price and vessel transit speed.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ocean Engineering - Volume 145, 15 November 2017, Pages 334-343
Journal: Ocean Engineering - Volume 145, 15 November 2017, Pages 334-343
نویسندگان
Iver Bakken Sperstad, Magnus Stålhane, Iain Dinwoodie, Ole-Erik V. Endrerud, Rebecca Martin, Ethan Warner,