Abstract
The important feature of wind energy is the fluctuation of the power produced over time. The stability of the network is based on the balance between production and consumption. For this, the idea of storage has been exploited. Owing of this, in first stage, an ANFIS controller is proposed for speed control in order to ensure the real-time tracking of the optimum operating point and MPPT giving online a maximum production of electric power for different wind speeds. In second stage, we present a new solution for the wind energy storage based on short term storage. This solution is based on the use of the intelligent flywheel based on fuzzy logic. The new Fuzzy FESS can be used not only to minimize wind power fluctuations, but also to adjust the frequency and the voltage of the grid during operating conditions. Simulation testes on a 1.5 MW DSIG system are given to illustrate the feature of control method and the large interest of energy storage in such WECS.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wu, B., Lang, Y., Zargari, N., Kouro, S.: Power Conversion and Control of Wind Energy Systems. IEEE Press Series on Power Engineering. Wiley, Hoboken (2011)
Khaterchi, M., Elhadj, J., Elleuch, M.: DPC for three-phase inverter to improve the integration of wind turbine associated to flywheel energy storage system into the grid. In: Proceedings of the 6th Annual International Multi Conference on System, Signals and Devices (2009)
Davigny, A.: Participation aux services systèmes de fermes d’éoliennes à vitesse variable intégrant du stockage inertial d’énergie. Ph.D thesis. Lillle University (2007)
Leclerq, L.: Apport du stockage inrtiel associé à des éoliennes dans un réseau électrique en vue d’assurer des services systèmes. Ph.D thesis, Lillle University (2004)
Cimuca, G.O.: Système Inertiel de Stockage D’énergie Associé à des générateurs Eoliens ‘. Ph.D thesis, Lille University (2005)
Abo-Khalil, A., Lee, D.C., Seok, J.K.: Variable speed wind power generation system based on fuzzy logic control for maximum output power tracking. In: Proceedings of the 35th Annual IEEE Conference on Power Electronics Specialists, pp. 2039–2043, June 2004
Chekkal, S., Aouzellag, D., Ghedamsi, K., Amimeur, H.: New control strategy of wind generator based on the dual-stator induction generator. In: July of the 10th Annual IEEE Conference (EEEIC), pp. 68–71, May 2011
Amimeur, H., Aouzellag, D., Abdessemed, R., Ghedamsi, K.: Sliding mode control of a dual-stator induction generator for wind energy conversion systems. Trans. Electr. Power Energ. Syst. 42(1), 60–70 (2012). Elsevier
Pant, V., Siugh, G.K., Singh, S.N.: Modeling of a multi-phase induction machine under fault condition. In: July IEEE Conference Power Electronics and Drive Systems, pp. 92–97, July 1999
Vas, P.: Sensorless Vector and Direct Torque, p. 267. Oxford University Press, U.K (1998). Chapter 4
Kouzi, K., Mokrani, L., Naït-Saïd, M-S.: High performances of fuzzy self-tuning scaling factor of PI fuzzy logic controller based on direct vector control for induction motor drive without flux measurements. In: Proceedings of IEEE International Conference on Industrial Technology (ICIT), pp. 1106–1111, December 2004
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Appendix. A Parameters
Appendix. A Parameters
DSIG: 1.5 MW, 400 V, 50 Hz, 2 pole pairs, \( R_{s1} = R_{s2} = 0.008\,{\text{X}} \), \( L_{1} = L_{2} = 0.134\,{\text{mH,}} \) \( L_{m} = 0.0045\,{\text{H}} \), \( R_{r} = 0.007\,{\text{X,}} \) \( L_{r} = 0.067\,{\text{mH}} \), \( {\text{J}} = 104\;{\text{kg}}\;{\text{m}}^{2} \left( {{\text{turbine}}\,{ + }\,{\text{Machine}}} \right), \) \( f_{r} = 2.5\;{\text{N}}\,{\text{m}}\,{\text{S/rd}}:\left( {{\text{turbine}} + {\text{Machine}}} \right). \)
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Bouras, M., Kouzi, K. (2018). Analysis of Novel Flywheel Energy Storage System Based on Dual Stator Induction Machine Incorporated in Wind Energy Systems Using Intelligent Approach. In: Hatti, M. (eds) Artificial Intelligence in Renewable Energetic Systems. ICAIRES 2017. Lecture Notes in Networks and Systems, vol 35. Springer, Cham. https://doi.org/10.1007/978-3-319-73192-6_37
Download citation
DOI: https://doi.org/10.1007/978-3-319-73192-6_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-73191-9
Online ISBN: 978-3-319-73192-6
eBook Packages: EngineeringEngineering (R0)