Details

Title

Optimization of periodic maintenance for wind turbines based on stochastic degradation model

Journal title

Archives of Electrical Engineering

Yearbook

2021

Volume

vol. 70

Issue

No 3

Affiliation

Su, Hongsheng : Lanzhou Jiaotong University, China ; Duan, Xuping : Lanzhou Jiaotong University, China ; Wang, Dantong : Lanzhou Jiaotong University, China

Authors

Keywords

availability ; maintenance optimization ; stochastic differential equation ; update process ; wind turbine

Divisions of PAS

Nauki Techniczne

Coverage

585-599

Publisher

Polish Academy of Sciences

Bibliography

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[2] Su C., Hu Z.Y., Reliability assessment for Chinese domestic wind turbines based on data mining techniques, Wind Energy, vol. 21, no. 3, pp. 198–209 (2018).
[3] Zhao Hongshan, Zhang Jianping, Gao Duo et al., A condition based opportunistic maintenance strategy for wind turbine, Proceedings of the CSEE, vol. 35, no. 15, pp. 3851–3858 (2015).
[4] ChengYujing, Optimization maintenance research of wind turbines pitch system based on opportunistic maintenance strategy, Shanghai, Shang Hai Dianji University (2013).
[5] Li Hui, Yang Chao, Li Xuewei et al., Conditions characteristic parameters mining and outlier identification for electric pitch system of wind turbine, Proceedings of the CSEE, vol. 34, no. 12, pp. 1922–1930 (2014).
[6] Besnard F., Bertling L., An approach for condition-based maintenance optimization applied to wind turbine blades, IEEE Transactions on Sustainable Energy, vol. 1, no. 2, pp. 77–83 (2010).
[7] Liu Lujie, FuYang,Ma Shiwei et al., Maintenance strategy for offshore wind turbine based on condition monitoring and prediction, Power System Technology, vol. 39, no. 11, pp. 3292–3297 (2015).
[8] Suprasad V., Amari Leland Mclaughlin, Hoang Pham, Cost-effective condition-based maintenance using Markov decision processes, Reliability and Maintainability Symposium, pp. 464–469 (2006).
[9] Zhao Hongshan, Zhang Jianping, Gao Duo et al., A condition based opportunistic maintenance strategy for wind turbine under imperfect maintenance, Proceedings of the CSEE, vol. 36, no. 3, pp. 3851–3858 (2016).
[10] Li Dazi, Feng Yuanyuan, Liu Zhan et al., Reliability modeling and maintenance strategy optimization for wind power generation sets, Power System Technology, vol. 35, no. 9, pp. 122–127 (2011).
[11] Fu Yang, Xu Weixin, Liu Lujie et al., Optimization of preventive opportunistic maintenance strategy for offshore wind turbine considering weather conditions, Proceedings of the CSEE, vol. 38, no. 20, pp. 5947–5956 (2018).
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[14] Elwany A.H., Gebraeel N.Z., Sensor-driven prognostic models for equipment replacement and spare parts inventory, IIE Transactions, vol. 40, no. 7, pp. 629–639 (2008).
[15] Liu Haiqing, Lin Weijian, Li Yuancheng, Ultra-short-term wind power prediction based on copula function and bivariate EMD decomposition algorithm, Archives of Electrical Engineering, vol. 69, no. 2, pp. 271–286 (2020).
[16] Wang Shaohua, Zhang Yaohui et al., Optimal condition-based maintenance decision-making method of multi-component system based on simulation, Acta Armamentarii, vol. 38, no. 3, pp. 568–575 (2017).
[17] Liu Junqiang, Xie Jianwei et al., Residual lifetime prediction for aeroengines based on wiener process with random effect, Acta Aeronautica et Astronautica Sinica, vol. 36, no. 2, pp. 564–574 (2015).
[18] Palmer T.N., A nonlinear dynamical perspective on model error; A proposal for non-local stochasticdynamic parametrization in weather and climate prediction models, Quarterly Journal of the Royal Meteorological Society, vol. 127, no. 572, pp. 279–304 (2010).
[19] Gong Guanglu, Qian Minping, Application of stochastic process tutorial and its stochastic models in algorithms and intelligent computing, Beijing, Tsinghua University Press (2004).
[20] Rausand M., System Reliability Theory: Models, Statistical Methods, and Applications, 2nd Edition, Statistical methods in reliability theory and practice, E. Horwood (2004).
[21] Su Hongsheng, Control strategy on preventive maintenance of repairable device, Journal of Zhejiang University (Engineering Science), vol. 44, no. 7, pp. 1308–1314 (2010).

Date

2021.08.18

Type

Article

Identifier

DOI: 10.24425/aee.2021.137575
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