Abstract
In view of the grid voltage unbalance, wind power generation system (PGS) in the variable speed gearbox, torque ripple of serious harm, unit monitoring data timeliness is strong, large amount of data, so in the process of analysis, also need a unified analysis was carried out on the wind field data, the effective analysis method based on big data is a necessity. In this paper, a dual current loop control strategy based on the separation of positive and negative sequence (PNS) components is proposed to suppress the electromagnetic torque ripple. Vector control is performed on the rotor-side converter, that is, the positive sequence component of the rotor current is controlled in the positive sequence rotating coordinate system (CS) to achieve independent regulation of active power. The model of doubly-fed wind PGS is modeled, and the characteristics of the system, such as instantaneous APRP (APRP), are analyzed. The experimental results show that the control strategy can effectively restrain the electromagnetic torque ripple, and it has a good guiding significance for wind farms to obtain good grid-connected power generation performance.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Qin, B., Sun, H., Ma, J.: Robust H∞ control of doubly fed wind generator via state-dependent riccati equation technique. IEEE Trans. Power Syst. 34, 99 (2018)
Ouyang, J., Tang, T., Zheng, D.: Characteristics and calculation method of short-circuit current of doubly fed wind generator under lower voltage ride through. Trans. China Electrotech. Soc. 32(22), 216–224 (2017)
Yang, B., Zhang, X., Yu, T.: Grouped grey wolf optimizer for maximum power point tracking of doubly-fed induction generator based wind turbine. Energy Convers. & Manag. 133, 427–443 (2016)
Mousa, M.G., Allam, S.M., Rashad, E.M.: Maximum power extraction under different vector-control schemes and grid-synchronization strategy of a wind-driven brushless doubly-fed reluctance generator. ISA Trans. 72, 287 (2018)
Pradhan, C., Bhende, C.N.: Enhancement in primary frequency regulation of wind generator using fuzzy-based control. Electr. Power Compon. & Syst. 44(15), 1–14 (2016)
Laina, R., Lamzouri, F.E.Z., Boufounas, E.M.: Intelligent control of a DFIG wind turbine using a PSO evolutionary algorithm. Procedia Comput. Sci. 127, 471–480 (2018)
Lo’ai, A.T., Mehmood, R., Benkhelifa, E.:. Mobile cloud computing model and big data analysis for healthcare applications. IEEE Access 4, 99:1–1 (2016)
Tang, B., Chen, Z., Hefferman, G.: Incorporating intelligence in fog computing for big data analysis in smart cities. IEEE Trans. Ind. Inform. 13(5), 2140–2150 (2017)
Chen, B.Y., Yuan, H., Li, Q.: Spatiotemporal data model for network time geographic analysis in the era of big data. Int. J. Geogr. Inf. Sci. 30(6), 1041–1071 (2016)
Hussaina, A., Cambriab, E.: Semi-supervised learning for big social data analysis. Neurocomputing 275 (2017)
Acknowledgements
This work was supported by Scientific research fund of education department of liaoning province (LJKX201906).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Wang, N., Wang, L. (2021). Voltage Unbalance Factors of Doubly-Fed Wind Generator Based on Big Data Analysis. In: Sugumaran, V., Xu, Z., Zhou, H. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. MMIA 2020. Advances in Intelligent Systems and Computing, vol 1233. Springer, Cham. https://doi.org/10.1007/978-3-030-51431-0_95
Download citation
DOI: https://doi.org/10.1007/978-3-030-51431-0_95
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-51430-3
Online ISBN: 978-3-030-51431-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)