Real-time hardware emulation of wind turbine model with asynchronous generator under hardware-in-the-loop platform
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Tomson Thomas
,
Prince Asok
,
Anoopraj Mattathil Radhakrishnan
and
Sunil Kumar P. R. Puthenpurayil
Abstract
Renewable energy sources are becoming as one of the major generation strategies around the world. The wind energy systems have been technologically advanced and integrated to the power system in a rapid routine. This paper looks into the modelling as well as operational exploration of a three blade wind turbine connected to asynchronous generator. State-of-the-art wind turbine topologies and a comparative summary of real-time simulation technologies for electrical systems are described. A 2.4 MW wind turbine with three blades is modelled for the analysis of power characteristics. The shift from sub-synchronous to super-synchronous mode is analysed for type-A wind energy conversion system (WECS) with 2 MW asynchronous generator by using MATLAB/Simulink model. The step-by-step standard operating procedure for modelling and real-time simulation of 2 MW type-A WECS having asynchronous generator under hardware-in-the-loop platform is elucidated. The steady state and transient behaviours of the WECS are validated by the real-time emulation under a hardware-in-the-loop platform.
Acknowledgement
Authors recognize the assistance from the Centre for Engineering Research and Development (CERD), Kerala, India.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
1. Global Wind Energy Council; 2021. https://www.gwec.net/.Search in Google Scholar
2. Taczi, I. Enhancing power system frequency stability with synthetic inertia. In: IEEE EUROCON 2017 – 17th International Conf. on. Ohrid: Smart Technologies; 2017:960–5 pp.10.1109/EUROCON.2017.8011254Search in Google Scholar
3. Hossain, MM, Ali, MH. Transient stability improvement of doubly fed induction generator based variable speed wind generator using DC resistive fault current limiter. IET Renew Power Gener 2016;10:150–7. https://doi.org/10.1049/iet-rpg.2015.0150.Search in Google Scholar
4. Papadopoulos, PN, Milanović, JV. Probabilistic framework for transient stability assessment of power systems with high penetration of renewable generation. IEEE Trans Power Syst 2017;32:3078–88. https://doi.org/10.1109/tpwrs.2016.2630799.Search in Google Scholar
5. Firouzi, M, Gharehpetian, GB, Salami, Y. Active and reactive power control of wind farm for enhancement transient stability of multi-machine power system using UIPC. IET Renew Power Gener 2017;11:1246–52. https://doi.org/10.1049/iet-rpg.2016.0459.Search in Google Scholar
6. Hwang, M, Muljadi, E, Jang, G, Kang, YC. Disturbance-adaptive short-term frequency support of a DFIG associated with the variable gain based on the ROCOF and rotor speed. IEEE Trans Power Syst 2017;32:1873–81. https://doi.org/10.1109/tpwrs.2016.2592535.Search in Google Scholar
7. Thomas, T, Prince, A. LVRT capability evaluation of DFIG based wind energy conversion system under type-A and type-C grid voltage sags. In: International conference on power electronics, smart grid and renewable energy (PESGRE2020). Cochin: IEEE; 2020:1–6 pp.10.1109/PESGRE45664.2020.9070540Search in Google Scholar
8. Ghosh, S, Isbeih, Y, Bhattarai, R, El Moursi, MS, El-Saadany, EF, Kamalasadan, S. A dynamic coordination control architecture for reactive power capability enhancement of the DFIG-based wind power generation. IEEE Trans Power Syst 2020;35:3051–64. https://doi.org/10.1109/tpwrs.2020.2968483.Search in Google Scholar
9. Ouyang, J, Tang, T, Yao, J, Li, M. Active voltage control for DFIG-based wind farm integrated power system by coordinating active and reactive powers under wind speed variations. IEEE Trans Energy Convers 2019;34:1504–11. https://doi.org/10.1109/tec.2019.2905673.Search in Google Scholar
10. Maharjan, R, Kamalasadan, S. Real-time simulation for active and reactive power control of doubly fed induction generator. In: IEEE North American Power Symposium (NAPS), Manhattan; 2013:1–6 pp.10.1109/NAPS.2013.6666957Search in Google Scholar
11. Zakaria Moustafa, MM, Nzimako, O, Dekhordi, A. Real time simulation of a wind turbine driven doubly fed induction generator. In: 19th IEEE European conference on power electronics and applications (EPE’17 ECCE Europe), Warsaw; 2017:P.1–10 pp.10.23919/EPE17ECCEEurope.2017.8098987Search in Google Scholar
12. Soued, S. Experimental behaviour analysis for optimally controlled standalone DFIG system. IET Electr Power Appl 2019;13:1462–73. https://doi.org/10.1049/iet-epa.2018.5648.Search in Google Scholar
13. Gao, J, Wang, N, Wang, J, Wang, S, Zhan, P. The implementation and test for HIL real-time simulation of doubly-fed induction generator based on FPGA. In: 22nd IEEE international conference on electrical machines and systems (ICEMS), Harbin; 2019:1–5 pp.10.1109/ICEMS.2019.8922247Search in Google Scholar
14. Jaladi, KK, Sandhu, KS. Real-time simulator based hybrid control of DFIG-WES. ISA Trans 2019;93:325–40. https://doi.org/10.1016/j.isatra.2019.03.024.Search in Google Scholar
15. Shihabudheen, KV, Pillai, GN, Krishnama Raju, S. Neuro-fuzzy control of DFIG wind energy system with distribution network. Elec Power Compon Syst 2018;46:1416–31. https://doi.org/10.1080/15325008.2018.1499154.Search in Google Scholar
16. Shihabudheen, KV, Raju, SK, Pillai, GN. Control for grid‐connected DFIG‐based wind energy system using adaptive neuro‐fuzzy technique. Int Trans Electr Energ Syst 2018;28:e2526. https://doi.org/10.1002/etep.2526.Search in Google Scholar
17. Liu, W, Xie, X, Zhang, X, Li, X. Frequency-coupling admittance modeling of converter-based wind turbine generators and the control-hardware-in-the-loop validation. IEEE Trans Energy Convers 2020;35:425–33. https://doi.org/10.1109/tec.2019.2940076.Search in Google Scholar
18. Lin, X, Xiahou, K, Liu, Y, Wu, QH. Design and hardware-in-the-loop experiment of multiloop adaptive control for DFIG-WT. IEEE Trans Ind Electron 2018;65:7049–59. https://doi.org/10.1109/tie.2018.2798566.Search in Google Scholar
19. Faruque, MO, Strasser, T, Lauss, G, Jalili-Marandi, V, Forsyth, P, Dufour, C, et al.. Real-time simulation technologies for power systems design, testing, and analysis. IEEE Power Energy Technol Syst J 2015;2:63–73. https://doi.org/10.1109/jpets.2015.2427370.Search in Google Scholar
20. Thomas, T, Asok, P. Event analysis and real-time validation of doubly fed induction generator-based wind energy system with grid reactive power exchange under sub-synchronous and super-synchronous modes. Eng Rep 2020;2:e12282. https://doi.org/10.1002/eng2.12282.Search in Google Scholar
21. Ackermann, T. Wind power in power systems. England: John Wiley & Sons, Ltd; 2005.10.1002/0470012684Search in Google Scholar
22. Velpula, S, Thirumalaivasan, R, Janaki, M. Stability analysis on torsional interactions of turbine-generator connected with DFIG-WECS using admittance model. IEEE Trans Power Syst 2020;35:4745–55. https://doi.org/10.1109/tpwrs.2020.2992111.Search in Google Scholar
23. Ma, J, Shen, Y, Phadke, AG. Stability assessment of DFIG subsynchronous oscillation based on energy dissipation intensity analysis. IEEE Trans Power Electron 2020;35:8074–87. https://doi.org/10.1109/tpel.2019.2962217.Search in Google Scholar
24. Nair, SG, Senroy, N. Dynamics of a flywheel energy storage system supporting a wind turbine generator in a microgrid. Int J Emerg Elec Power Syst 2016;17:15–26. https://doi.org/10.1515/ijeeps-2015-0128.Search in Google Scholar
25. Goyal, M, Fan, Y, Ghosh, A, Shahnia, F. Techniques for a wind energy system integration with an islanded microgrid. Int J Emerg Elec Power Syst 2016;17:191–203. https://doi.org/10.1515/ijeeps-2015-0139.Search in Google Scholar
26. Jahanpour-Dehkordi, M, Vaez-Zadeh, S, Mohammadi, J. Development of a combined control system to improve the performance of a PMSG-based wind energy conversion system under normal and grid fault conditions. IEEE Trans Energy Convers 2019;34:1287–95. https://doi.org/10.1109/tec.2019.2912080.Search in Google Scholar
27. Khazaei, J, Nguyen, DH, Asrari, A. Consensus-based demand response of PMSG wind turbines with distributed energy storage considering capability curves. IEEE Trans Sustain Energy 2020;11:2315–25. https://doi.org/10.1109/tste.2019.2954796.Search in Google Scholar
28. Zubiaga, M, Abad, G, Barrena, JA, Aurtenetxea, S, Cárcar, A. Energy transmission and grid integration of AC offshore wind farms. Croatia: InTech; 2012.10.5772/45610Search in Google Scholar
29. Thomas, T, Cheriyan, EP. Wind energy system for a laboratory scale micro-grid. In: Electrical, electronics and computer science (SCEECS), 2012 IEEE Students’ Conf. on, Bhopal; 2012:1–5 pp.10.1109/SCEECS.2012.6184761Search in Google Scholar
30. Wu, B, Lang, Y, Zargari, N, Kouro, S. Power conversion and control of wind energy systems. Hoboken, New Jersey: IEEE Press; John Wiley & Sons, Inc; 2011.10.1002/9781118029008Search in Google Scholar
31. Chen, Z, Yin, M, Zou, Y, Meng, K, Dong, Z. Maximum wind energy extraction for variable speed wind turbines with slow dynamic behavior. IEEE Trans Power Syst 2017;32:3321–2. https://doi.org/10.1109/tpwrs.2016.2623981.Search in Google Scholar
32. Vidyanandan, KV, Senroy, N. Primary frequency regulation by deloaded wind turbines using variable droop. IEEE Trans Power Syst 2013;28:837–46. https://doi.org/10.1109/tpwrs.2012.2208233.Search in Google Scholar
33. Xiong, L, Li, P, Wu, F, Wang, J. Stability enhancement of power systems with high DFIG-wind turbine penetration via virtual inertia planning. IEEE Trans Power Syst 2019;34:1352–61. https://doi.org/10.1109/tpwrs.2018.2869925.Search in Google Scholar
© 2021 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Research Articles
- Differential positive sequence power angle-based microgrid feeder protection
- Real-time hardware emulation of wind turbine model with asynchronous generator under hardware-in-the-loop platform
- Frequency stability analysis with fuzzy adaptive selfish herd optimization based optimal sliding mode controller for microgrids
- Seamless control of grid-tied PV-Hybrid Energy Storage System
- Improved higher order adaptive sliding mode control for increased efficiency of grid connected hybrid systems
- Optimal siting of solar based distributed generation (DG) in distribution system for constant power load model
- Electricity demand modeling techniques for hybrid solar PV system
- Robust decentralized model predictive load-frequency control design for time-delay renewable power systems
- A techno-economic analysis of the roof top off-grid solar PV system for Jamshedpur, Jharkhand, India
Articles in the same Issue
- Frontmatter
- Research Articles
- Differential positive sequence power angle-based microgrid feeder protection
- Real-time hardware emulation of wind turbine model with asynchronous generator under hardware-in-the-loop platform
- Frequency stability analysis with fuzzy adaptive selfish herd optimization based optimal sliding mode controller for microgrids
- Seamless control of grid-tied PV-Hybrid Energy Storage System
- Improved higher order adaptive sliding mode control for increased efficiency of grid connected hybrid systems
- Optimal siting of solar based distributed generation (DG) in distribution system for constant power load model
- Electricity demand modeling techniques for hybrid solar PV system
- Robust decentralized model predictive load-frequency control design for time-delay renewable power systems
- A techno-economic analysis of the roof top off-grid solar PV system for Jamshedpur, Jharkhand, India
