Effective balancing of preventive maintenance cost and energy loss to improve wind turbine performance

YASSINE EDDOUH; Abdelmajid Daya; Rabie El Otmani

doi:10.51646/jsesd.v15iMME.392

Authors

YASSINE EDDOUH Sciences for Energy Laboratory LabSIPE, ENSAJ, Chouaib Doukkali University https://orcid.org/0000-0003-2510-3201
Abdelmajid Daya Department of Physics, Laboratory of M3ER, FSTE, Moulay Ismail University of Meknes, Morocco
Rabie El Otmani Sciences for Energy Laboratory LabSIPE, ENSAJ, Chouaib Doukkali University, El Jadida, Morocco https://orcid.org/0000-0002-8181-6233

DOI:

https://doi.org/10.51646/jsesd.v15iMME.392

Abstract

Sustainable energy depends on the reliability and efficiency of wind turbines, making preventive maintenance a vital factor in ensuring their optimal performance. This paper introduces an innovative methodology utilizing Monte Carlo simulation to optimize maintenance intervals, focusing on a balanced approach that reduces both maintenance costs and energy losses. It advocates for a grouped maintenance strategy, demonstrating its superior impact on production efficiency compared to individualized approaches. Through an analysis of cost distribution and energy losses, the research establishes an optimized equilibrium for preventive maintenance, verified through a numerical case study of wind turbine with 2MW. This example shows a 3.20% increase in energy production, emphasizing the effectiveness of the proposed strategy in maximizing both cost-effectiveness and energy efficiency. By balancing these factors, the framework contributes to advancements in sustainable energy solutions, offering a promising path toward enhanced wind turbine reliability and greater operational efficiencies, ultimately facilitating a smoother transition to sustainable energy worldwide.

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References

G. Luderer et al., "The role of renewable energy in climate stabilization: results from the EMF27 scenarios," Climatic change, vol. 123, no. 3, pp. 427-441, 2014.

O. A. Adelekan et al., "Energy transition policies: a global review of shifts towards renewable sources," Engineering Science & Technology Journal, vol. 5, no. 2, pp. 272-287, 2024.

S.-H. Ding and S. Kamaruddin, "Maintenance policy optimization—literature review and directions," The International Journal of Advanced Manufacturing Technology, vol. 76, no. 5, pp. 1263-1283, 2015.

E. Singh, S. S. Afshari, and X. Liang, "Wind turbine optimal preventive maintenance scheduling using fibonacci search and genetic algorithm," Journal of Dynamics, Monitoring and Diagnostics, vol. 2, no. 3, pp. 157-169, 2023.

Y. Eddouh, A. Daya, R. Elotmani, and A. Touache, "Age replacement and inspection models for estimating optimal maintenance cost: numerical performance comparisons with a case study from chemical industries," International Journal of System Assurance Engineering and Management, vol. 14, no. 4, pp. 1354-1369, 2023.

A. A. Eladl et al., "A comprehensive review on wind power spillage: Reasons, minimization techniques, real applications, challenges, and future trends," Electric Power Systems Research, vol. 226, p. 109915, 2024.

A. P. Gonzalo, T. Benmessaoud, M. Entezami, and F. P. G. Márquez, "Optimal maintenance management of offshore wind turbines by minimizing the costs," Sustainable Energy Technologies and Assessments, vol. 52, p. 102230, 2022.

T. N. Schouten, R. Dekker, M. Hekimoğlu, and A. S. Eruguz, "Maintenance optimization for a single wind turbine component under time-varying costs," European Journal of operational research, vol. 300, no. 3, pp. 979-991, 2022.

Q. Yu, P. Bangalore, S. Fogelström, and S. Sagitov, "Optimal preventive maintenance scheduling for wind turbines under condition monitoring," Energies, vol. 17, no. 2, p. 280, 2024.

R. Zheng, Y. Zhou, and Y. Zhang, "Optimal preventive maintenance for wind turbines considering the effects of wind speed," Wind Energy, vol. 23, no. 11, pp. 1987-2003, 2020.

Y. S. Duarte, J. Szpytko, and A. M. del Castillo Serpa, "Monte Carlo simulation model to coordinate the preventive maintenance scheduling of generating units in isolated distributed Power Systems," Electric Power Systems Research, vol. 182, p. 106237, 2020.

C. D. Dao, B. Kazemtabrizi, C. J. Crabtree, and P. J. Tavner, "Integrated condition‐based maintenance modelling and optimisation for offshore wind turbines," Wind Energy, vol. 24, no. 11, pp. 1180-1198, 2021.

H. Su, X. Duan, and D. Wang, "Optimization of periodic maintenance for wind turbines based on stochastic degradation model," Archives of Electrical Engineering, vol. 70, no. 3, pp. 585-599, 2021.

S. Vittal and M. Teboul, "Performance and reliability analysis of wind turbines using Monte Carlo methods based on system transport theory," in 46th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, 2005, p. 2218.

C. A. Irawan, M. Eskandarpour, D. Ouelhadj, and D. Jones, "Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm," European Journal of operational research, vol. 289, no. 3, pp. 912-926, 2021.

D. Biazar, H. Khaloozadeh, and M. Siahi, "Evaluating the effect of wind turbine faults on power using the Monte Carlo method," Wind Energy, vol. 25, no. 5, pp. 935-951, 2022.

D. Wang, Y. Liu, X. Cao, Y. Jiang, and P. Ding, "A research on the Monte Carlo simulation based on-condition maintenance strategy for wind turbines," in 2020 Chinese Control And Decision Conference (CCDC), 2020: IEEE, pp. 4016-4020.

M. Daoudi, A. A. S. Mou, and L. Ait Naceur, "Analysis of the first onshore wind farm installation near the Morocco-United Kingdom green energy export project," Scientific African, vol. 17, p. e01388, 2022.

S. Sheng and R. O’Connor, "Reliability of wind turbines," in Wind energy engineering: Elsevier, 2023, pp. 195-211.

N. Conroy, J. Deane, and B. P. Ó. Gallachóir, "Wind turbine availability: Should it be time or energy based?–A case study in Ireland," Renewable Energy, vol. 36, no. 11, pp. 2967-2971, 2011.

M. Shafiee and M. Finkelstein, "An optimal age-based group maintenance policy for multi-unit degrading systems," Reliability engineering & system safety, vol. 134, pp. 230-238, 2015.