A novel approach to address reliability concerns of wind turbines

A novel approach to address reliability concerns of wind turbines

Sorena ARTIN

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Abstract. Designing and manufacturing a system in the current industrial world cannot be accomplished without addressing safety related issues. For this purpose, system reliability is a powerful tool to ensure that failure probability of the system is below an accepted level while the system is operational. A commonly used approach to deal with these considerations is to define a performance function for the system in order to investigate its reliability. In this case, renewable energy systems (RESs) are not different. When a wind turbine, as a RES, is designed, its reliability cannot be ignored or underestimated. Therefore, stable and efficient models are needed to make sure that the turbine remains operational and is able to safely generate electricity power. In this paper, a new approach is proposed to set up a reliability analysis model for the wind turbines. The introduced model takes two important factors, i.e. the wind speed and the wind angle, and their probability distributions into account. These two factors are indeed considered as random variables to design a new system performance function and set up the new model in order to investigate wind turbine’s reliability.

Wind Turbines, Reliability Analysis, Random Variables, Renewable Energy

Published online 7/15/2024, 6 pages
Copyright © 2024 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: Sorena ARTIN, A novel approach to address reliability concerns of wind turbines, Materials Research Proceedings, Vol. 43, pp 82-87, 2024

DOI: https://doi.org/10.21741/9781644903216-11

The article was published as article 11 of the book Renewable Energy: Generation and Application

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

[1] B. Morawski; Global Wind, Solar Production Hit Highest Benchmarks Ever in 2021, But Coal Also Kept Pace; World Economy Forum (2022).
[2] S. Costello; Neighbourhood Dispute Erupts Over Man’s Backyard Wind Turbine; Nine News Australia (2022).
[3] J. Hill; Swedish Wind Turbine Collapses Days After Wind Farm Inauguration; Renew Economy (2022).
[4] S. Shakya; A self-monitoring and analysing system for solar power station using IoT and data mining algorithms. Journal of Soft Computing Paradigm, 3(2) (2021), 96-109. https://doi.org/10.36548/jscp.2021.2.004
[5] C. Vennila, A. Titus, T. Sri Sudha, U. Sreenivasulu, R. Pandu Ranga Reddy, K. Jamal, A. Belay; Forecasting Solar Energy Production Using Machine Learning; International Journal of Photoenergy, 7797488 (2022). https://doi.org/10.1155/2022/7797488
[6] H. Rezk, T. Sudhakar Babu, M. Al-Dhaifallah, H. Zeidan; A Robust Parameter Estimation Approach Based on Stochastic Fractal Search Optimization Algorithm Applied to Solar PV Parameters; Energy Reports, 7 (2021), 620-640. https://doi.org/10.1016/j.egyr.2021.01.024
[7] S. Artin; Reliability Enhancement of Solar Panels based on the Photocurrent Equality; 2023 Asia-Pacific Conference on Applied Mathematics and Statistics; Nanjing, China, June 2023.
[8] J. Deng, H. Li, J. Hu, Z. Liu; New Wind Speed Scenario Generation Method Based on Spatiotemporal Dependency Structure; Renewable Energy, 163 (2021), 1951-1962. https://doi.org/10.1016/j.renene.2020.10.132
[9] S. Okpokparoro, S. Sriramula; Uncertainty Modelling in Reliability Analysis of Floating Wind Turbine Support Structure; Renewable Energy, 165 (2021), 88-108. https://doi.org/10.1016/j.renene.2020.10.068
[10] D. Wilkie, C. Galasso; Gaussian Process Regression for Fatigue Reliability Analysis of Offshore Wind Turbines; Structural Safety, 88 (2021), 102020. https://doi.org/10.1016/j.strusafe.2020.102020
[11] C. Clark, B. DuPont; Reliability-Based Design Optimization in Offshore Renewable Energy Systems; Renewable and Sustainable Energy Reviews, 97 (2018), 390-400. https://doi.org/10.1016/j.rser.2018.08.030
[12] G. Tina, S. Gagliano, S. Raiti; Hybrid Solar/Wind Power System Probabilistic Modelling for Long-Term Performance Assessment; Solar Energy, 80 (2006), 578-588. https://doi.org/10.1016/j.solener.2005.03.013
[13] S. Eryilmaz, I. Bulanik, Y. Devrim; Reliability Based Modelling of Hybrid Solar/Wind Power System for Long Term Performance Assessment; Reliability Engineering and System Safety, 209 (2021), 107478. https://doi.org/10.1016/j.ress.2021.107478
[14] G. Ezzati, A. Rasouli; Evaluating System Reliability Using Linear-Exponential Distribution Function; International Journal of Advanced Statistics and Probability, 3(1) (2015), 15-24. https://doi.org/10.14419/ijasp.v3i1.3927
[15] M. Zarmai, C. Oduoza; Impact of Intermetallic Compound Thickness on Thermo-Mechanical Reliability of Solder Joints in Solar Cell Assembly; Microelectronics Reliability, 116 (2021), 114008. https://doi.org/10.1016/j.microrel.2020.114008
[16] S. Al Sanad, L. Wang, J. Parol, A. Kolios; Reliability-Based Design Optimization Framework for Wind Turbine Towers; Renewable Energy, 167 (2021), 942-953. https://doi.org/10.1016/j.renene.2020.12.022
[17] A. Askarzadeh, L. Coelho; A Novel Framework for Optimization of a Grid Independent Hybrid Renewable Energy System: A Case Study of Iran; Solar Energy, 112 (2015), 383-396. https://doi.org/10.1016/j.solener.2014.12.013
[18] B. Zhang, M. Wang, W. Su; Reliability Analysis of Power Systems Integrated with High-Penetration of Power Converters; IEEE Transactions on Power Systems, 36(3) (2021), 1998-2009. https://doi.org/10.1109/TPWRS.2020.3032579
[19] G. Ezzati; A Reliability-Based Design Optimization Model for Electricity Power Networks; Dynamics of Continuous, Discrete and Impulsive Systems, Series B: Applications & Algorithms, 22 (2015), 339-357.
[20] G. Ezzati, M. Mammadov, S. Kulkarni; Solving Reliability Analysis Problems in the Polar Space: International Journal of Applied Mathematical Research, 3(4) (2015), 353-365. https://doi.org/10.14419/ijamr.v3i4.3302
[21] S. Artin, S. Salimzadeh; A Conjugate Gradient Direction-Based Method to Evaluate Reliability Analysis Problems; IAENG International Journal of Applied Mathematics, 52(3) (2022), 659-666.
[22] G. Ochoa, J. Alvarez, M. Chamorro; Data Set on Wind Speed, Wind Direction and Wind Probability Distributions in Puerto Bolivar – Colombia; Data in Brief, 27 (2019). https://doi.org/10.1016/j.dib.2019.104753