Optimal external opportunistic maintenance for wind turbines considering wind speed

被引:3
|
作者
Wang, Jinhe [1 ,2 ,3 ]
Xia, Yuqiang [1 ]
Qin, Yapeng [1 ]
Zhang, Xiaohong [1 ,2 ]
机构
[1] Taiyuan Univ Sci & Technol, Sch Econ & Management, Taiyuan, Peoples R China
[2] Taiyuan Univ Sci & Technol, Div Ind & Syst Engn, Taiyuan, Peoples R China
[3] Taiyuan Univ Sci & Technol, Div Ind & Syst Engn, 66,WaLiu Rd, Taiyuan 030024, Shanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
Condition-based maintenance; external opportunistic maintenance; genetic algorithm; wind speed variability; wind turbine; OPTIMIZATION; SYSTEMS; POLICY; FARM; COMPONENTS; STRATEGY; MODEL; COST;
D O I
10.1080/15435075.2023.2281335
中图分类号
O414.1 [热力学];
学科分类号
摘要
A novel optimal opportunistic maintenance strategy for wind turbines considering wind speed as a stochastic process is proposed in this paper. Under this strategy, periodic preventive maintenance is conducted to reduce the probability of downtime due to failure, whereas external opportunities are leveraged to reduce the cost of preventive maintenance. This combined maintenance approach can also reduce costs associated with the wind turbine lifecycle. The formulated expected costs per unit time considered two scenarios, i.e. regular operation and energy generation interruption, to obtain the optimal solution via a genetic algorithm. Furthermore, we illustrated the economic advantages of the proposed strategy by comparing various maintenance strategies, as well as a sensitivity analysis to determine the effects of the different parameters in the proposed model. Experimental results demonstrate that the proposed opportunistic maintenance strategy is more cost-effective for wind turbines than comparable methods, with an optimal solution that varies according to variations in wind speed.
引用
收藏
页码:2022 / 2041
页数:20
相关论文
共 50 条
  • [31] Framework for Managing Maintenance of Wind Farms Based on a Clustering Approach and Dynamic Opportunistic Maintenance
    Izquierdo, Juan
    Crespo Marquez, Adolfo
    Uribetxebarria, Jone
    Erguido, Asier
    ENERGIES, 2019, 12 (11)
  • [32] Self-adaptive optimized maintenance of offshore wind turbines by intelligent Petri nets
    Saleh, Ali
    Chiachio, Manuel
    Fernandez Salas, Juan
    Kolios, Athanasios
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2023, 231
  • [33] RELIABILITY ASSESSMENT FOR WIND TURBINES CONSIDERING THE INFLUENCE OF WIND SPEED USING BAYESIAN NETWORK
    Su, Chun
    Fu, Ye-qun
    EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY, 2014, 16 (01): : 1 - 8
  • [34] Optimal placement of wind turbines within a wind farm considering multi-directional wind speed using two-stage genetic algorithm
    A. S. O. Ogunjuyigbe
    T. R. Ayodele
    O. D. Bamgboje
    Frontiers in Energy, 2021, 15 : 240 - 255
  • [35] Optimal placement of wind turbines within a wind farm considering multi-directional wind speed using two-stage genetic algorithm
    Ogunjuyigbe, A. S. O.
    Ayodele, T. R.
    Bamgboje, O. D.
    FRONTIERS IN ENERGY, 2021, 15 (01) : 240 - 255
  • [36] Virtual Wind Speed Sensor for Wind Turbines
    Kusiak, Andrew
    Zheng, Haiyang
    Zhang, Zijun
    JOURNAL OF ENERGY ENGINEERING, 2011, 137 (02) : 59 - 69
  • [37] Optimal Wind Capacity Integration Considering the Possibilistic Uncertainty of Wind Resources
    Sun, Can
    Xie, Min
    Bie, Zhaohong
    Jiang, Jiangfeng
    Song, Xiaobo
    2015 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT ASIA), 2015,
  • [38] Opportunistic maintenance for wind farms considering multi-level imperfect maintenance thresholds
    Ding, Fangfang
    Tian, Zhigang
    RENEWABLE ENERGY, 2012, 45 : 175 - 182
  • [39] Optimal Power and Cost on Placement of Wind Turbines using Firefly Algorithm
    Hendrawati, Dwiana
    Soeprijanto, Adi
    Ashari, Mochamad
    2015 INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY ENGINEERING AND APPLICATION (ICSEEA), 2015, : 59 - 64
  • [40] Aerodynamic characteristics of wind turbines considering the inhomogeneity and periodic incentive of wake effects
    Gao, Xiaoxia
    Zhou, Kuncheng
    Liu, Runze
    Ma, Wanli
    Gong, Xiaoyu
    Zhu, Xiaoxun
    Wang, Yu
    Zhao, Fei
    ENERGY, 2024, 310