A metaheuristic solution method for optimizing vessel fleet size and mix for maintenance operations at offshore wind farms under uncertainty

被引:18
作者
Halvorsen-Weare, Elin Espeland [1 ]
Norstad, Inge [1 ]
Stalhane, Magnus [2 ]
Nonas, Lars Magne [1 ]
机构
[1] SINTEF Ocean, Dept Maritime, POB 4125 Valentinlyst, NO-7450 Trondheim, Norway
[2] NTNU, Dept Ind Econ & Technol Management, Alfred Getz Veg 3, NO-7491 Trondheim, Norway
来源
14TH DEEP SEA OFFSHORE WIND R&D CONFERENCE, EERA DEEPWIND'2017 | 2017年 / 137卷
关键词
offshore wind; operation and maintenance; operations research; fleet composition; decision support; metaheuristic;
D O I
10.1016/j.egypro.2017.10.382
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Maintenance operations at offshore wind farms are challenging due to the offshore element; maintenance technicians and spare parts need to be transported from an onshore port or offshore station to the individual wind farm components in need of maintenance. The vessel resources needed to support these maintenance tasks constitute a major part of the total maintenance costs, and hence up-keeping an optimal vessel fleet and corresponding deployment is essential to reduce cost-of-energy. This paper introduces a metaheuristic solution method to determine cost-efficient vessel fleets to support maintenance tasks at offshore wind farms under uncertainty. It considers weather conditions and failures leading to corrective maintenance tasks as stochastic parameters, and evaluates candidate solutions by a simulation program. The solution method has been incorporated in a decision support tool. Computational experiments, including comparison of results with an exact solution method, illustrate that the decision support tool can be used to provide near-optimal solutions within acceptable computational time. (C) 2017 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:531 / 538
页数:8
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