Optimized design of patrol path for offshore wind farms based on genetic algorithm and particle swarm optimization with traveling salesman problem

被引:3
|
作者
Kou, Lei [1 ]
Wan, Junhe [1 ]
Liu, Hailin [1 ]
Ke, Wende [2 ]
Li, Hui [1 ]
Chen, Jie [1 ]
Yu, Zhen [1 ]
Yuan, Quande [3 ]
机构
[1] Shandong Acad Sci, Qilu Univ Technol, Inst Oceanog Instrumentat, Qingdao, Peoples R China
[2] Southern Univ Sci & Technol, Dept Mech & Energy Engn, Shenzhen, Peoples R China
[3] Changchun Inst Technol, Sch Comp Technol & Engn, Changchun, Peoples R China
来源
关键词
genetic algorithm; particle swarm optimization; patrol path; smart offshore wind farm; traveling salesman problem; TURBINES;
D O I
10.1002/cpe.7907
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
With the rapid expansion of global offshore wind power market, the research on improving the full life cycle income and reducing the construction and operation and maintenance costs has attracted the attention of scholars in the industry. In view of the different aging degree and maintenance cycle of wind turbines, this paper studies the optimized design of patrol path for offshore wind farms based on genetic algorithm (GA) and particle swarm optimization (PSO) with traveling salesman problem (TSP). Firstly, the problem of patrol routing planning in offshore wind farms is described as the traveling salesman problem of shortest route optimization. Secondly, the GA and PSO algorithms are simulated and verified separately, and the patrol path distance is taken as the objective function. Finally, through simulation experiments, the optimized patrol path performances of PSO and GA are compared, which can help to find a shortest route and reduce the operation and maintenance costs.
引用
收藏
页数:11
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