Maximizing Wind Turbine Efficiency: Monte Carlo Simulation Based on Cost and Energy Loss Analysis for Optimal Preventive Maintenance

• Autorzy: Eddouh Yassine , Daya Abdelmajid , El Otmani Rabie , Touache Abdelhamid

Identyfikatory

DOI

10.24425/mper.2024.149994

• Języki publikacji: EN

Abstrakty

EN

In response to the urgent need for sustainable energy, this study addresses a critical challenge in wind turbine optimization. It focuses on developing a nuanced preventive maintenance strategy to minimize costs and mitigate energy losses. Within this framework, our paper introduces a novel approach employing a Monte Carlo simulation to identify the optimal preventive maintenance frequency, striking a balance between cost efficiency and energy loss mitigation. The results show, that grouped maintenance approach, pinpointing an optimal frequency of 93 months. This strategic configuration minimizes costs to $9997 while concurrently maintaining an average energy loss of 32.014 MWh, resulting in a notable 4.29% increase in total energy production. Variability analysis reveals that increasing maintenance frequency reduces cost fluctuations, while energy loss remains relatively stable. These findings elucidate the interplay among preventive maintenance strategies, cost, and reliability in the realm of wind turbine performance optimization .

Słowa kluczowe

EN

wind turbine; preventive maintenance; optimization; Monte Carlo; reliability; production process

• Wydawca: Production Engineering Committee of the Polish Academy of Sciences ; Polish Association for Production Management
• Czasopismo: Management and Production Engineering Review
• Rocznik: 2024
• Tom: Vol. 15, No. 1
• Strony: 111--125
• Opis fizyczny: Bibliogr. 29 poz., rys., tab., wykr.

Twórcy

autor

Eddouh Yassine

• Sciences for En- ergy Laboratory LabSIPE, ENSAJ Chouaib Doukkali University, El Jadida, Morocco

autor

Daya Abdelmajid

• Department of Physics, Laboratory of M3ER, FSTE, Moulay Ismail University, Morocco

autor

El Otmani Rabie

• Sciences for Energy Laboratory LabSIPE, ENSAJ, Chouaib Doukkali University, Morocco

autor

Touache Abdelhamid

• Mechanical Engineering Laboratory, Sidi Mohamed Ben Abdellah University, Morocco

Bibliografia

• Abdusamad, K. (2018). Wind energy reliability analysis based on Monte Carlo simulation method. DOI: 10.21467/proceedings.4.41.
• Ali Elfarra, M., & Kaya, M. (2021). Estimation of electricity cost of wind energy using Monte Carlo simulations based on nonparametric and parametric probability density functions. Alexandria Engineering Journal, 60 (4), 3631–3640. DOI: 10.1016/j.aej.2021.02.027.
• Azizi, M., & Jahangirian, A. (2020). Multi-site aerodynamic optimization of wind turbine blades for maximum annual energy production in East Iran. Energy Science & Engineering, 8 (6), 2169–2186.
• Benmessaoud, T., Mohammedi, K., & Smaili, Y. (2013). Influence of maintenance on the performance of a wind farm. Przegląd Elektrotechniczny, 89 (03a), 174–178.
• Biazar, D., Khaloozadeh, H., & Siahi, M. (2022). Evaluating the effect of wind turbine faults on power using the Monte Carlo method. Wind Energy, 25 (5), 935–951. DOI: 10.1002/we.2708.
• Dao, C.D., Kazemtabrizi, B., & Crabtree, C.J. (2020). Offshore wind turbine reliability and operational simulation under uncertainties. Wind Energy, 23 (10), 1919–1938. DOI: 10.1002/we.2526.
• Dao, C.D., Kazemtabrizi, B., Crabtree, C.J., & Tavner, P.J. (2021). Integrated condition-based maintenance modelling and optimisation for offshore wind turbines. Wind Energy, 24 (11), 1180–1198. DOI: 10.1002/we.2625.
• Daoudi, M., Mou, A.A.S., & Naceur, L.A. (2022). Analysis of the first onshore wind farm installation near the Morocco-United Kingdom green energy export project. Scientific African, 17, e01388. DOI: 10.1016/j.sciaf.2022.e01388.
• De Jonge, B., & Scarf, P.A. (2020). A review on maintenance optimization. European Journal of operational research, 285 (3), 805–824. DOI: 10.1016/j.ejor.2019.09.047.
• Ding, S.-H., & Kamaruddin, S. (2015). Maintenance policy optimization – literature review and directions. The International Journal of Advanced Manufacturing Technology, 76, 1263–1283. DOI: 10.1007/s00170-014-6341-2.
• Dorvlo, A.S. (2002). Estimating wind speed distribution. Energy Conversion and Management, 43 (17), 2311–2318. DOI: 10.1016/S0196-8904(01)00182-0.
• Duarte, Y.S., Szpytko, J., & del Castillo Serpa, A.M. (2020). Monte Carlo simulation model to coordinate the preventive maintenance scheduling of generating units in isolated distributed Power Systems. Electric Power Systems Research, 182, 106237. DOI: 10.1016/j.epsr.2020.106237.
• Dubi, A. (1998). Analytic approach & Monte Carlo methods for realistic systems analysis. Mathematics and Computers in Simulation, 47 (2–5), 243–269. DOI: 10.1016/S0378-4754(98)00122-0.
• Dui, H., Zhang, Y., & Zhang, Y.-A. (2023). Grouping Maintenance Policy for Improving Reliability of Wind Turbine Systems Considering Variable Cost. Mathematics, 11 (8), 1954. DOI: 10.3390/math11081954.
• Gonzalo, A.P., Benmessaoud, T., Entezami, M., & Márquez, F.P.G. (2022). Optimal maintenance management of offshore wind turbines by minimizing the costs. Sustainable Energy Technologies and Assessments, 52, 102230. DOI: 10.1016/j.seta.2022.102230.
• Hajej, Z., Nidhal, R., Anis, C., & Bouzoubaa, M. (2020). An optimal integrated production and maintenance strategy for a multi-wind turbines system. International Journal of Production Research, 58 (21), 6417– 6440. DOI: 10.1080/00207543.2019.1680897.
• Hofmann, M., & Sperstad, I.B. (2013). NOWIcob–A tool for reducing the maintenance costs of offshore wind farms. Energy Procedia, 35, 177–186. DOI: 10.1016/j.egypro.2013.07.171
• Irawan, C.A., Eskandarpour, M., Ouelhadj, D., & Jones, D. (2021). Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm. European Journal of operational research, 289 (3), 912–926. DOI: 10.1016/j.ejor.2019.08.032.
• Lu, Y., Sun, L., & Xue, Y. (2021). Research on a Comprehensive Maintenance Optimization Strategy for an Offshore Wind Farm. Energies, 14 (4), 965. DOI: 10.3390/en14040965.
• Luderer, G., Krey, V., Calvin, K., Merrick, J., Mima, S., Pietzcker, R., Van Vliet, J., & Wada, K. (2013). The role of renewable energy in climate stabilization: results from the EMF27 scenarios. Climatic change, 123 (3–4), 427–441. DOI: 10.1007/s10584-013-0924-z.
• Marmidis, G., Lazarou, S., & Pyrgioti, E. (2008). Optimal placement of wind turbines in a wind park using Monte Carlo simulation. Renewable Energy, 33 (7), 1455–1460. DOI: 10.1016/j.renene.2007.09.004.
• Schouten, T.N., Dekker, R., Hekimoğlu, M., & Eruguz, A.S. (2022). Maintenance optimization for a single wind turbine component under time-varying costs. European Journal of operational research, 300(3), 979-991. DOI: 10.1016/j.ejor.2021.09.004.
• Shafiee, M., & Finkelstein, M. (2015). An optimal agebased group maintenance policy for multi-unit degrading systems. Reliability engineering & system safety, 134, 230–238. DOI: 10.1016/j.ress.2014.09.016.
• Singh, E., Afshari, S.S., & Liang, X. (2023). Wind Turbine Optimal Preventive Maintenance Scheduling Using Fibonacci Search and Genetic Algorithm. Journal of Dynamics, Monitoring and Diagnostics. DOI: 10.37965/jdmd.2023.158.
• Su, H., Duan, X., & Wang, D. (2021). Optimization of periodic maintenance for wind turbines based on stochastic degradation model. Archives of Electrical Engineering, vol. 70 (3), 585–599. DOI: 10.24425/aee.2021.137575.
• Vittal, S., & Teboul, M. (2005). Performance and reliability analysis of wind turbines using Monte Carlo methods based on system transport theory. 46th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference,
• Wang, D., Liu, Y., Cao, X., Jiang, Y., & Ding, P. (2020). A research on the Monte Carlo simulation based on-condition maintenance strategy for wind turbines. 2020 Chinese Control And Decision Conference (CCDC),
• Yu, Q., Bangalore, P., Fogelström, S., & Sagitov, S. (2021). Optimal preventive maintenance scheduling for wind turbines under condition monitoring. arXiv preprint arXiv:2104.04460. DOI: 10.48550/arXiv.2104.04460.
• Zheng, R., Zhou, Y., & Zhang, Y. (2020). Optimal preventive maintenance for wind turbines considering the effects of wind speed. Wind Energy, 23 (11), 1987–2003. DOI: 10.1002/we.2541.