粒子群优化
海上风力发电
重组
海洋工程
海底管道
环境科学
工程类
计算机科学
业务
涡轮机
数学优化
机械工程
财务
数学
岩土工程
作者
Yuanhang Qi,Haoyu Luo,Gewen Huang,Peng Hou,Rongsen Jin,Yuhui Luo
出处
期刊:Biomimetics
[Multidisciplinary Digital Publishing Institute]
日期:2024-09-05
卷期号:9 (9): 536-536
标识
DOI:10.3390/biomimetics9090536
摘要
As the capacity of individual offshore wind turbines increases, prolonged downtime (due to maintenance or faults) will result in significant economic losses. This necessitates enhancing the efficiency of vessel operation and maintenance (O&M) to reduce O&M costs. Existing research mostly focuses on planning O&M schemes for individual vessels. However, there exists a research gap in the scientific scheduling for state-of-the-art O&M vessels. To bridge this gap, this paper considers the use of an advanced O&M vessel in the O&M process, taking into account the downtime costs associated with wind turbine maintenance and repair incidents. A mathematical model is constructed with the objective of minimizing overall O&M expenditure. Building upon this formulation, this paper introduces a novel restructuring particle swarm optimization which is tailed with a bespoke encoding and decoding strategy, designed to yield an optimized solution that aligns with the intricate demands of the problem at hand. The simulation results indicate that the proposed method can achieve significant savings of 28.85% in O&M costs. The outcomes demonstrate the algorithm's proficiency in tackling the model efficiently and effectively.
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