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Title: Testing the robustness of optimal access vessel fleet selection for operation and maintenance of offshore wind farms

Abstract

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. Our 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. Also the parameter with the greatest discrepancy between the tools, implies 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.

Authors:
 [1];  [2];  [3];  [4];  [5];  [6]
  1. SINTEF Energy Research, Trondheim (Norway)
  2. Norwegian Univ. of Science and Technology and SNITEF Ocean, Trondheim (Norway). Dept. of Industrial Economics and Technology Management
  3. Univ. of Strathclyde, Glasgow (United Kingdom)
  4. Univ. of Stavanger (Norway)
  5. EDF Energy R&D UK Centre, London (United Kingdom)
  6. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1411323
Report Number(s):
NREL/JA-6A20-65621
Journal ID: ISSN 0029-8018
Grant/Contract Number:
AC36-08GO28308
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Ocean Engineering
Additional Journal Information:
Journal Volume: 145; Journal Issue: C; Journal ID: ISSN 0029-8018
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; offshore wind; O&M; logistics; optimisation; simulation; sensitivity analysis

Citation Formats

Sperstad, Iver Bakken, Stålhane, Magnus, Dinwoodie, Iain, Endrerud, Ole-Erik V., Martin, Rebecca, and Warner, Ethan. Testing the robustness of optimal access vessel fleet selection for operation and maintenance of offshore wind farms. United States: N. p., 2017. Web. doi:10.1016/j.oceaneng.2017.09.009.
Sperstad, Iver Bakken, Stålhane, Magnus, Dinwoodie, Iain, Endrerud, Ole-Erik V., Martin, Rebecca, & Warner, Ethan. Testing the robustness of optimal access vessel fleet selection for operation and maintenance of offshore wind farms. United States. doi:10.1016/j.oceaneng.2017.09.009.
Sperstad, Iver Bakken, Stålhane, Magnus, Dinwoodie, Iain, Endrerud, Ole-Erik V., Martin, Rebecca, and Warner, Ethan. Sat . "Testing the robustness of optimal access vessel fleet selection for operation and maintenance of offshore wind farms". United States. doi:10.1016/j.oceaneng.2017.09.009. https://www.osti.gov/servlets/purl/1411323.
@article{osti_1411323,
title = {Testing the robustness of optimal access vessel fleet selection for operation and maintenance of offshore wind farms},
author = {Sperstad, Iver Bakken and Stålhane, Magnus and Dinwoodie, Iain and Endrerud, Ole-Erik V. and Martin, Rebecca and Warner, Ethan},
abstractNote = {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. Our 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. Also the parameter with the greatest discrepancy between the tools, implies 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.},
doi = {10.1016/j.oceaneng.2017.09.009},
journal = {Ocean Engineering},
number = C,
volume = 145,
place = {United States},
year = {Sat Sep 23 00:00:00 EDT 2017},
month = {Sat Sep 23 00:00:00 EDT 2017}
}

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