RESEARCH ON REMOTE MONITORING SYSYTEM OF WIND TURBINE DRIVEN BY DIGITIAL

Bao Shenghui; Sun Wenlei; Liu Han; Jiang Lun; Wang Bingkai; Wang Yi

doi:10.19912/j.0254-0096.tynxb.2023-1372

PDF(2578 KB)

Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (1) : 78-87. DOI: 10.19912/j.0254-0096.tynxb.2023-1372

RESEARCH ON REMOTE MONITORING SYSYTEM OF WIND TURBINE DRIVEN BY DIGITIAL

Bao Shenghui, Sun Wenlei, Liu Han, Jiang Lun, Wang Bingkai, Wang Yi

Author information +

History +

Abstract

As the essential equipment in the field of renewable energy, wind turbines are prone to failures during operation due to long-term operation in harsh environments conditions. Therefore, it is very necessary to monitor and maintain them in the whole life cycle operation. Aiming at the low visualization level of the current wind turbine monitoring system and the inability to transmit data remotely in real time, a framework of digital twin-driven system for remotely monitoring wind turbines, which is consists of six critical modules, is proposed. Subsequently, this system has been developed via multiple technologies including entity modeling, model lightweighting, construction of behavior rule model and dynamic model, remote real-time data transmission, and visualization in Unity3D engine. Finally, the feasibility and effectiveness of the system for realizing the remote intelligent monitoring of wind turbines with real-time dynamic status monitoring, fault alarm and human-computer interaction are verified via experiments.

Key words

wind turbines / monitoring / visualization / digital twins / twin model / condition monitoring

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Bao Shenghui, Sun Wenlei, Liu Han, Jiang Lun, Wang Bingkai, Wang Yi. RESEARCH ON REMOTE MONITORING SYSYTEM OF WIND TURBINE DRIVEN BY DIGITIAL[J]. Acta Energiae Solaris Sinica. 2025, 46(1): 78-87 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1372

References

[1] DAO P B.On Wilcoxon rank sum test for condition monitoring and fault detection of wind turbines[J]. Applied energy, 2022, 318: 119209.
[2] VEGA-ZUÑIGA S, RUEDA-BAYONA J G, OSPINO-CASTRO A. Evaluation of eleven numerical methods for determining weibull parameters for wind energy generation in the Caribbean region of Colombia[J]. Mathematical modelling of engineering problems, 2022, 9(1): 194-199.
[3] TUEGEL E J, INGRAFFEA A R, EASON T G, et al.Reengineering aircraft structural life prediction using a digital twin[J]. International journal of aerospace engineering, 2011, 2011: 154798.
[4] OLATUNJI O O, ADEDEJI P A, MADUSHELE N, et al.Overview of digital twin technology in wind turbine fault diagnosis and condition monitoring[C]//2021 IEEE 12th International Conference on Mechanical and Intelligent Manufacturing Technologies (ICMIMT). Cape Town, South Africa, 2021: 201-207.
[5] CHIACHÍO M, MEGÍA M, CHIACHÍO J, et al. Structural digital twin framework: formulation and technology integration[J]. Automation in construction, 2022, 140: 104333.
[6] QI T F, FANG H R, CHEN Y F, et al.Research on digital twin monitoring system for large complex surface machining[J]. Journal of intelligent manufacturing, 2024, 35(3): 977-990.
[7] FAN Y P, YANG J Z, CHEN J H, et al.A digital-twin visualized architecture for flexible manufacturing system[J]. Journal of manufacturing systems, 2021, 60: 176-201.
[8] WANG K J, LEE Y H, ANGELICA S.Digital twin design for real-time monitoring-a case study of die cutting machine[J]. International journal of production research, 2021, 59(21): 6471-6485.
[9] ZHOU Y, FU Z K, ZHANG J, et al.A digital twin-based operation status monitoring system for port cranes[J]. Sensors, 2022, 22(9): 3216.
[10] 房方, 姚贵山, 胡阳, 等. 风力发电机组数字孪生系统[J]. 中国科学: 技术科学, 2022, 52(10): 1582-1594.
FANG F, YAO G S, HU Y, et al.Digital twin system for wind turbines[J]. Science in China: technology science, 2022, 52(10): 1582-1594.
[11] MOGHADAM F K, NEJAD A R.Online condition monitoring of floating wind turbines drivetrain by means of digital twin[J]. Mechanical systems and signal processing, 2022, 162: 108087.
[12] ZHAO X, DAO M H, LE Q T.Digital twining of an offshore wind turbine on a monopile using reduced-order modelling approach[J]. Renewable energy, 2023, 206: 531-551.
[13] 陶飞, 张贺, 戚庆林, 等. 数字孪生模型构建理论及应用[J]. 计算机集成制造系统, 2021, 27(1): 1-15.
TAO F, ZHANG H, QI Q L, et al.Theory and application of digital twin model construction[J]. Computer integrated manufacturing systems, 2021, 27(1): 1-15.
[14] 尚海勇, 刘利强, 齐咏生, 等. 基于数字孪生技术的风电机组建模研究[J]. 太阳能学报, 2023, 44(5): 391-400.
SHANG H Y, LIU L Q, QI Y S, et al.Research on wind turbine modeling based on digital twin technology[J]. Acta energiae solaris sinica, 2023, 44(5): 391-400.
[15] GARLAND M, HECKBERT P S.Surface simplification using quadric error metrics[C]//Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques. New York, USA, 1997: 209-216.
[16] LIU X C, DU J, YE Z S.A condition monitoring and fault isolation system for wind turbine based on SCADA data[J]. IEEE transactions on industrial informatics, 2022, 18(2): 986-995.
[17] DAO P B.Condition monitoring and fault diagnosis of wind turbines based on structural break detection in SCADA data[J]. Renewable energy, 2022, 185: 641-654.