影响因子：6.6
DOI码：10.1016/j.asoc.2025.113439
所属单位：哈尔滨工程大学船舶工程学院
发表刊物：Applied Soft Computing
刊物所在地：荷兰
项目来源：Key Research and Development Program of Hainan Province (ZDYF2023GXJS017); Natural Science Foundatio
关键字：Offshore wind farm; Operation and maintenance scheduling; Uncertainty; Artificial hummingbird algorithm; Chaotic mapping; Quantum computing
摘要：This paper investigates the offshore wind farm operation and maintenance (O&M) scheduling problem to minimize the total cost and carbon dioxide emission. Firstly, minimize the total cost of O&M and carbon emission from O&M vessels. Secondly, the trapezoidal fuzzy number is used to represent the uncertainty of the O&M vessel speed, the vessel carbon emission factor, and the wind speed in the sea area around a specific wind turbine. Meanwhile, constraints are determined regarding the frequency of vessel visits the turbines that need to be repaired, O&M personnel and spare parts, and a new fuzzy model for O&M scheduling of offshore wind farms is constructed. A new chaotic quantum artificial hummingbird algorithm (CQAHA) is used to improve the searching performance. In addition, the feasible integerization algorithm (FIA) is developed for determining the number of visiting turbines (M- DNVT), and eventually, a new O&M scheduling optimization method for offshore wind farms is proposed. Subsequently, the feasibility and superiority of the constructed solution method are tested based on the data from offshore wind farms in southern China. The results demonstrate that the proposed model can achieve an optimal scheduling solution in terms of cost and environmental protection. In the optimal solution, the total O&M cost and carbon emissions are reduced by 8.5 % and 4.7 %, respectively. Furthermore, the improved algorithm is more efficient, with smaller mean and standard deviation compared to the benchmark algorithm, while also achieving faster convergence.
备注：Key Research and Development Program of Hainan Province (ZDYF2023GXJS017); Natural Science Foundation of Heilongjiang Province of China (ZD2022E002); Key Research and Development Program of Heilongjiang Province (GA23A905); and National Natural Science Foundation of China (No.52371315).
合写作者：雷逸彰,杨忠仪,黄信博
第一作者：李明伟
论文类型：期刊论文
通讯作者：洪维强
论文编号：113439
学科门类：工学
文献类型：J
卷号：180
ISSN号：1568-4946
是否译文：否
发表时间：2025
收录刊物：SCI
发布期刊链接：https://www.sciencedirect.com/science/article/pii/S1568494625007501?via%3Dihub