ASPECTS REGARDING OPERATION PREDICTABILITY OF WIND TURBINES

Valeriu DULGHERU, Marin GUȚU, Sergiu ZAPOROJAN, Eugeniu MUNTEANU

Abstract


As the wind turbine blades are one of the most difficult parts to monitor, it reliability is vital in the operation and maintenance of a wind turbine.  A possible way to intelligently monitor the condition of the blade is to acquire and process data on the current strains inside the blade structure. The aim of the work is determination of the critical areas via simulations. In those areas is proposed to integrate micro-wire strain sensors. A typical mega-watt wind turbine (≈1.5 MW) was considered for simulations under various boundary conditions. The maximum equivalent stress in the blade (≈ 48 MPa) occurs at the wind speed of 16 m/s. The extreme strain values (0.00032 and 0.00062) occurred at locations ≈ 0.18 and 0.7 of the rotor radius.

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References


Mishnaevsky, L. Jr. Root Causes and Mechanisms of Failure of Wind Turbine Blades: Overview. Materials 2022; 23 p.

Chen, X. Fracture of wind turbine blades in operation - Part I: A comprehensive forensic investigation. Wind Energy 2018; 21: 1046– 1063.

McGugan, M., Mishnaevsky L. Jr. Damage Mechanism Based Appr,oach to the Structural Health Monitoring of Wind Turbine Blades. Coatings 2020, 10, 1223.

Bladena Report, Cost and Risk Tool for Interim and Preventive Repair (CORTIR) EUDP; Bladena, Denmark: 2021. 302p. EUDP Project 64018-0507–Final Report.

Robinson, C.M.E. Study and Development of a Methodology for the Estimation of the Risk and Harm to Persons from Wind Turbines. MMI Engineering Ltd.; London, UK: 2013. 86 p.

Kelele, H. K. et all. Catchment Based Aerodynamic Performance Analysis of Small Wind Turbine Using a Single Blade Concept for a Low Cost of Energy. Energies 2020, 13, 5838.

Lachance-Barrett, S., Keith A., Fluent - Wind Turbine Blade FSI (Part 1). Fluent Learning Modules. https://confluence.cornell.edu/

Benbouzid, M., Berghout T., Sarma N., Djurovic S., Wu Y., Ma X. Intelligent Condition Monitoring of Wind Power Systems: State of the Art Review. Energies 2021, 14, 5967.

Lowenhar, E. P., Bradshaw T., Cole P. T. Wind turbine blade monitoring systems. US Patent 11168668B2/09.11.2021.

News Mistras receives patent on its innovative Sensoria wind blade monitoring technology, https://www.jeccomposites.com/news/

Flaherty, N. Solid state battery for wind turbine blade monitor, https://www.eenewseurope.com

Márquez, F. P. G., Tobias A. M., Pérez J. M. P., Papaelias M. Condition monitoring of wind turbines: Techniques and methods. Renewable Energy 2012, 46, pp. 169–178.

Praslicka, D., Blazek J., Smelko M., Hudak J., Cverha A., Mikita I., Varga R., Zhukov A. Possibilities of Measuring Stress and Health Monitoring in Materials Using Contact-Less Sensor Based on Magnetic Microwires. IEEE Transactions on Magnetics, vol. 49, no. 1, 2013, pp. 128-131.

Aksenov, O. I., Fuks A. A., Aronin A. S. Mechanical stress measurement sensor based on micro-wires with positive magnetostriction. RU 2746765 C9. Bul. № 16/07.06.2021.

Larin V., Zaporojan S., Munteanu E. et al. Non-contact strain sensor. Application for Invention patent, nr. 7029. Nr. depozit a2022 0020, data depozit 2022.04.19.

Munteanu, E.; Zaporojan, S.; Dulgheru, V.; Slavescu, R.R.; Larin, V.; Rabei, I. Intelligent Condition Monitoring of Wind Turbine Blades: A preliminary approach. In: Proceedings of the IEEE 18th International Conference on Intelligent Computer Communication and Processing (ICCP), September 22-24, 2022, Cluj-Napoca, Romania, pp. 9-16.

Dulgheru, V.; Zaporojan, S.; Larin, V.; Manoli, I.; Munteanu, E.; Rabei, I. Method and device for predictive monitoring of the state of the wind turbine and implementation of countermeasures. Decision to grant the short-term patent, nr. 10247 din 2023.04.12.


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