OPTIMIZATION OF MAINTENANCE SCHEME FOR OFFSHORE WIND TURBINES CONSIDERING TIME WINDOW

Lyu Zhiwei; Wang Yong; Deng Qirong

doi:10.19912/j.0254-0096.tynxb.2021-0443

PDF(1609 KB)

Acta Energiae Solaris Sinica ›› 2022, Vol. 43 ›› Issue (10) : 177-185. DOI: 10.19912/j.0254-0096.tynxb.2021-0443

OPTIMIZATION OF MAINTENANCE SCHEME FOR OFFSHORE WIND TURBINES CONSIDERING TIME WINDOW

Lyu Zhiwei¹, Wang Yong^1,2, Deng Qirong¹

Author information +

History +

Abstract

It is the key to ensure the economic benefits of offshore wind power on reducing maintenance costs. Optimization maintenance scheme plays a dual role in reducing the maintenance costs of offshore wind turbines and increasing power generation. According to the reliability model of wind turbine components, the time window corresponding to the best maintenance opportunity for each wind turbine unit is calculated. Considering the economic losses due to premature maintenance and post-failure maintenance, an optimization model for offshore wind turbine maintenance considering time window constraints is established. Then, an improved genetic algorithm based on parameter optimization is designed to calculate the optimal maintenance scheme. Finally, a wind turbine maintenance case in an offshore wind farm is used to verify the model and algorithm. The results show that the maintenance scheme considering time window constraints can greatly improve the economic benefits of offshore wind power, and the improved genetic algorithm has stronger optimization ability than the traditional genetic algorithm.

Key words

offshore wind power / genetic algorithms / particle swarm optimization（PSO） / optimization of maintenance scheme / time window

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Lyu Zhiwei, Wang Yong, Deng Qirong. OPTIMIZATION OF MAINTENANCE SCHEME FOR OFFSHORE WIND TURBINES CONSIDERING TIME WINDOW[J]. Acta Energiae Solaris Sinica. 2022, 43(10): 177-185 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0443

References

[1] 刘永前, 马远驰, 陶涛. 海上风电场维护管理技术研究现状与展望[J]. 全球能源互联网, 2019, 2(2): 127-137.
LIU Y Q, MA Y C, TAO T.Research status and prospect of offshore wind farm maintenance management technology[J]. Journal of global energy interconnection, 2019, 2(2): 127-137.
[2] DAI L J, STÅLHANE M, UTNE I B. Routing and scheduling of maintenance fleet for offshore wind farms[J]. Wind engineering, 2015, 39(1): 15-30.
[3] ZHANG Z Y.Scheduling and routing optimization of maintenance fleet for offshore wind farms using Duo-ACO[J]. Advanced materials research, 2014, 3481: 294-301.
[4] STÅLHANE M, HVATTUM L M, SKAAR V. Optimization of routing and scheduling of vessels to perform maintenance at offshore wind farms[J]. Energy procedia, 2015, 80: 92-99.
[5] DAWID R, MCMILLAN D, REVIE M.Heuristic algorithm for the problem of vessel routing optimisation for offshore wind farms[J]. The journal of engineering, 2017, 2017(13): 1159-1163.
[6] IRAWAN C I, OUELHADJ D, JONES D, et al.Optimisation of maintenance routing and scheduling for offshore wind farms[J]. European journal of operational research, 2017, 256(1): 76-89.
[7] FAN D M, REN Y, FENG Q, et al.A hybrid heuristic optimization of maintenance routing and scheduling for offshore wind farms[J]. Journal of loss prevention in the process industries, 2019, 62: 103949.
[8] 张琛, 郭盛, 高伟, 等. 基于可靠度的风电机组机会维修策略[J]. 广东电力, 2016, 29(2): 40-44.
ZHANG C, GUO S, GAO W, et al.Reliability based maintenance strategy for wind turbines[J]. Guangdong electric power, 2016, 29(2): 40-44.
[9] 李帅. 基于机会的海上风电机组维修策略模型研究[D]. 北京: 华北电力大学, 2019.
LI S.Study on maintenance strategy model of offshore wind turbine based on opportunity[D]. Beijing: North China Electric Power University, 2019.
[10] 黄海悦. 基于零件可靠度的海上风电机组机会维护策略[D]. 北京: 华北电力大学, 2018.
HUANG H Y.Offshore wind turbine maintenance strategy based on component reliability[D]. Beijing: North China Electric Power University, 2018.
[11] 赵洪山, 张路朋. 基于可靠度的风电机组预防性机会维修策略[J]. 中国电机工程学报, 2014, 34(22): 3777-3783.
ZHANG H S, ZHANG L P.Reliability based preventive opportunity maintenance strategy for wind turbines[J]. Proceedings of the CSEE, 2014, 34(22): 3777-3783.
[12] KANG J C, GUEDES S C.An opportunistic maintenance policy for offshore wind farms[J]. Ocean engineering, 2020, 216: 108075.
[13] 于莹莹, 陈燕, 李桃迎. 改进的遗传算法求解旅行商问题[J]. 控制与决策, 2014, 29(8): 1483-1488.
YU Y Y, CHEN Y, LI T Y.Improved genetic algorithm to solve traveling salesman problem[J]. Control and decision, 2014, 29(8): 1483-1488.
[14] SINGH V, GANAPATHY L, PUNDIR A K.An improved genetic algorithm for solving multi depot vehicle routing problems[J]. International journal of information systems and supply chain management, 2019, 12(4): 1-26.
[15] AL-FURHUD M A, AHMED Z H. Experimental study of a hybrid genetic algorithm for the multiple travelling salesman problem[J]. Mathematical problems in engineering, 2020, 2020: 1-13.