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J. Mar. Sci. Eng. 2017, 5(2), 20; doi:10.3390/jmse5020020

Improved Methodology of Weather Window Prediction for Offshore Operations Based on Probabilities of Operation Failure

Department of Civil Engineering, Aalborg University, Thomas Mans Vej 23, 9000 Aalborg, Denmark
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Academic Editor: Simon Watson
Received: 8 December 2016 / Revised: 28 March 2017 / Accepted: 10 April 2017 / Published: 2 May 2017
(This article belongs to the Special Issue Offshore Wind Energy)
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Abstract

The offshore wind industry is building and planning new wind farms further offshore due to increasing demand on sustainable energy production and already occupied prime resource locations closer to shore. Costs of operation and maintenance, transport and installation of offshore wind turbines already contribute significantly to the cost of produced electricity and will continue to increase, due to moving further offshore, if the current techniques of predicting offshore wind farm accessibility are to stay the same. The majority of offshore operations are carried out by specialized ships that must be hired for the duration of the operation. Therefore, offshore wind farm accessibility and costs of offshore activities are primarily driven by the expected number of operational hours offshore and waiting times for weather windows, suitable for offshore operations. Having more reliable weather window estimates would result in better wind farm accessibility predictions and, as a consequence, potentially reduce the cost of offshore wind energy. This paper presents an updated methodology of weather window prediction that uses physical offshore vessel and equipment responses to establish the expected probabilities of operation failure, which, in turn, can be compared to maximum allowable probability of failure to obtain weather windows suitable for operation. Two case studies were performed to evaluate the feasibility of the improved methodology, and the results indicated that it produced consistent and improved results. In fact, the updated methodology predicts 57% and 47% more operational hours during the test period when compared to standard alpha-factor and the original methodologies. View Full-Text
Keywords: offshore; wind turbine; marine operations; transportation; installation; risk; probability; weather window; FORM; decision support offshore; wind turbine; marine operations; transportation; installation; risk; probability; weather window; FORM; decision support
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Gintautas, T.; Sørensen, J.D. Improved Methodology of Weather Window Prediction for Offshore Operations Based on Probabilities of Operation Failure. J. Mar. Sci. Eng. 2017, 5, 20.

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