Design and advanced control strategies of a hybrid energy storage system for the grid integration of wind power generations

Shu Wang; Yuejin Tang; Jing Shi; Kang Gong; Yang Liu; Li Ren; Jingdong Li

Design and advanced control strategies of a hybrid energy storage system for the grid integration of wind power generations

View Fulltext

Author(s): Shu Wang ¹ ; Yuejin Tang ¹ ; Jing Shi ¹ ; Kang Gong ¹ ; Yang Liu ¹ ; Li Ren ¹ ; Jingdong Li ¹
- Affiliations: 1: State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan, 430074, People's Republic of China
Source: Volume 9, Issue 2, March 2015, p. 89 – 98
DOI: 10.1049/iet-rpg.2013.0340 , Print ISSN 1752-1416, Online ISSN 1752-1424

« Previous Article
Table of contents
Next Article »

Received 22/10/2013, Accepted 05/06/2014, Revised 23/04/2014, Published 22/08/2014

Energy storage (ES) has become increasingly important in modern power system, whereas no single type of ES element can satisfy all diverse demands simultaneously. This study proposes a hybrid energy storage system (HESS) based on superconducting magnetic energy storage (SMES) and battery because of their complementary characteristics for the grid integration of wind power generations (WPG). This study investigates the mathematical model and the topology of the proposed HESS, which is equipped with a grid-side DC/AC converter, a battery buck/boost converter and a SMES DC chopper. The advanced control strategies comprised of device level and system level are designed. The control strategy for the converters which can be considered as device level is briefly discussed. The significant contribution of this study is proposing a novel system-level control strategy for reasonable and effective power allocation between SMES and battery. According to the control objectives, a fuzzy logic controller optimised with genetic algorithm is adopted. The detailed controller designs are described, meanwhile system stability and HESS operation performance are evaluated. MATLAB simulations are presented to demonstrate the effectiveness of the proposed strategies.

References

1. 1)
  - 24. Erdinc, O., Vural, B., Uzunoglu, M.: ‘A wavelet-fuzzy logic based energy management strategy for a fuel cell/battery/ultra-capacitor hybrid vehicular power system’, J. Power Sources, 2009, 194, (1), pp. 369–380 (doi: 10.1016/j.jpowsour.2009.04.072).
2. 2)
  - 9. Siemes, P., Haubrich, H.J., Vennegeerts, H., Ohrem, S.: ‘Concepts for the improved integration of wind power into the German interconnected system’, IET Renew. Power Gener., 2008, 2, (1), pp. 26–33 (doi: 10.1049/iet-rpg:20070072).
3. 3)
  - 25. Shi, J., Tang, Y.J., Yao, T., Li, J.D., Cheng, S.J.: ‘Study on control method of voltage source power conditioning system for SMES’. 2005 IEEE/PES Transmission and Distribution Conf. & Exhibition: Asia and Pacific, Dalian, China, 2005, pp. 1–6.
4. 4)
  - 37. Michalewicz, Z.: ‘Genetic algorithms + data structures = evolution programs’ (Springer, 1996, 3rd edn.).
5. 5)
  - A.A. Ferreira , J.A. Pomilio , G. Spiazzi , L. de Araujo Silva . Energy management fuzzy logic supervisory for electric vehicle power supplies system. IEEE Trans. Power Electron. , 107 - 115
6. 6)
  - 20. Xue, X.D., Cheng, K.W.E., Sutanto, D.X.D.: ‘A study of the status and future of superconducting magnetic energy storage in power systems’, Supercond. Sci. Technol., 2006, 19, (6), pp. 31–39 (doi: 10.1088/0953-2048/19/6/R01).
7. 7)
  - 34. Cheong, F., Lai, R.: ‘Constraining the optimization of a fuzzy logic controller using an enhanced genetic algorithm’, IEEE Trans. Syst. Man Cybern. B, Cybern., 2000, 30, (1), pp. 31–46 (doi: 10.1109/3477.826945).
8. 8)
  - 12. Li, X.: ‘Fuzzy adaptive Kalman filter for wind power output smoothing with battery energy storage system’, IETRenew. Power Gener., 2012, 6, (5), pp. 340–347 (doi: 10.1049/iet-rpg.2011.0177).
9. 9)
  - 10. Díaz-González, F., Sumper, A., Gomis-Bellmunt, O.: ‘A review of energy storage technologies for wind power applications’, Renew. Sustain. Energy Rev., 2012, 16, (4), pp. 2154–2171 (doi: 10.1016/j.rser.2012.01.029).
10. 10)
  - C. Haisheng , N.C. Thang , Y. Wei , L. Chunqing Tyongliang , D. Yulong . Process in electrical energy storage system: a critical review. Process Nat. Sci. , 3 , 291 - 312
11. 11)
  - M. Tsili , S. Papathanassiou . A review of grid code technical requirements for wind farms. IET Renew. Power Gener. , 3 , 308 - 332
12. 12)
  - M.H. Ali , W. Bin , R.A. Dougal . An overview of SMES applications in power and energy systems. IEEE Trans. Sustain. Energy , 1 , 38 - 47
13. 13)
  - 3. Rekioua, D., Bensmail, S., Bettar, N.: ‘Development of hybrid photovoltaic-fuel cell system for stand-alone application’, Int. J. Hydrog. Energy, 2014, 39, (3), pp. 1604–1611 (doi: 10.1016/j.ijhydene.2013.03.040).
14. 14)
  - 6. Xu, G., Xu, L., Morrow, J.: ‘Power oscillation damping using wind turbines with energy storage systems’, IET Renew. Power Gener., 2013, 7, (5), pp. 449–457 (doi: 10.1049/iet-rpg.2012.0019).
15. 15)
  - 18. Nomura, S., Shintomi, T., Akita, S., Nitta, T., Shimada, R., Meguro, S.: ‘Technical and cost evaluation on SMES for electric power compensation’, IEEE Trans. Appl. Supercond., 2010, 20, (2), pp. 101–106.
16. 16)
  - 38. The MathWorks. http://www.mathworks.com/.
17. 17)
  - L. Solero , A. Lidozzi , J. Pomilio . Design of multiple-input power converter for hybrid vehicles power electronics. IEEE Trans. Power Electron. , 5 , 1007 - 1016
18. 18)
  - P.F. Ribeiro , B.K. Johnson , M.L. Crow , A. Arsoy , Y. Liu . Energy storage systems for advanced power applications. Proc. IEEE , 12 , 1744 - 1756
19. 19)
  - A. Khaligh , L. Zhihao . Battery, ultracapacitor, fuel cell, and hybrid energy storage systems for electric, hybrid electric, fuel cell, and plug-in hybrid electric vehicles: state of the art. IEEE Trans. Veh. Technol. , 2806 - 2814
20. 20)
  - A. Abedini , H. Nikkhajoei . Dynamic model and control of a wind-turbine generator with energy storage. IET Renew. Power Gener. , 1 , 67 - 78
21. 21)
  - 15. Pedram, M., Chang, N., Kim, Y., Wang, Y.: ‘Hybrid electrical energy storage systems’. 2010 ACM/IEEE Int. Symp. Low-Power Electronics and Design, Austin, Texas, USA, August 2010, pp. 363–368.
22. 22)
  - B.C. Ummels , E. Pelgrum , W. Kling . Integration of large-scale wind power and use of energy storage in the Netherlands. IET Renew. Power Gener. , 1 , 34 - 46
23. 23)
  - 26. Shi, J., Tang, Y.J., Yang, K., et al: ‘SMES based on dynamic voltage restorer for voltage fluctuations compensation’, IEEE Trans. Appl. Supercond., 2010, 20, (3), pp. 1360–1364 (doi: 10.1109/TASC.2010.2041499).
24. 24)
  - 21. Moore, T., Douglas, J.: ‘Energy storage, big opportunities on a smaller scale’, EPRI., Spring, 2006, pp. 16–23.
25. 25)
  - 32. Linkens, D.A., Nyongesa, H.O.: ‘Genetic algorithms for fuzzy control. 1. Offline system development and application’, IEE Proc., Control Theory Appl., 1995, 142, (3), pp. 161–176 (doi: 10.1049/ip-cta:19951766).
26. 26)
  - N.J. Schouten , M.A. Salman , N.A. Kheir . Fuzzy logic control for parallel hybrid vehicles. IEEE Trans. Control Syst. Technol. , 460 - 468
27. 27)
  - 36. Goldberg, D.E.: ‘Genetic algorithms in search, optimization, and machine learning’ (Addison-Wesley Publishing Company, 1989).
28. 28)
  - S.S. Chen , L. Wang , W.J. Lee , Z. Chen . Power flow control and damping enhancement of a large wind farm using a superconducting magnetic energy storage unit. IET Renew. Power Gener. , 1 , 23 - 38
29. 29)
  - 30. Kosko, B., Burgess, J.C.: ‘Neural networks and fuzzy systems’, J. Acoust. Soc. Am., 1998, 103, (6), pp. 3131–3131.
30. 30)
  - 1. Rekioua, D., Matagne, E.: ‘Optimization of photovoltaic power systems: modelization, simulation and control’ (Springer, 2012).
31. 31)
  - 7. Wang, L., Yu, J.Y., Chen, Y.T.: ‘Dynamic stability improvement of an integrated offshore wind and marine-current farm using a flywheel energy-storage system’, IET Renew. Power Gener., 2011, 5, (5), pp. 387–396 (doi: 10.1049/iet-rpg.2010.0194).
32. 32)
  - A.R. Prasad , E. Natarajan . Optimization of integrated photovoltaic-wind power generation systems with battery storage. Energy , 1943 - 1954
33. 33)
  - 27. Suvire, G.O., Mercado, P.E.: ‘Combined control of a distribution static synchronous compensator/flywheel energy storage system for wind energy applications’, IET Gener. Transm. Distrib., 2012, 6, (6), pp. 483–492 (doi: 10.1049/iet-gtd.2011.0148).
34. 34)
  - 31. Jang, J.S.: ‘Self-learning fuzzy controllers based on temporal backpropagation’, IEEE Trans. Neural Netw., 1992, 3, (5), pp. 714–723.
35. 35)
  - 8. Nasiri, A., Esmaili, A., Abdel-Baqi, O., Novakovic, B.: ‘A hybrid system of li-ion capacitors and flow battery for dynamic wind energy support’, IEEE Trans. Ind. Appl., 2013, 49, (4), pp. 1649–1657 (doi: 10.1109/TIA.2013.2255112).
36. 36)
  - 33. Linkens, D.A., Nyongesa, H.O.: ‘Genetic algorithms for fuzzy control. 2. Online system development and application’, IEE Proc., Control Theory Appl., 1995, 142, (3), pp. 177–185 (doi: 10.1049/ip-cta:19951767).
37. 37)
  - 27. Chen, G., Pham, T.T.: ‘Introduction to fuzzy sets, fuzzy logic, and fuzzy control systems’ (CRC Press, 2000).
38. 38)
  - 35. Tang, K.S., Man, K.F., Chen, G., Kwong, S.: ‘An optimal fuzzy PID controller’, IEEE Trans. Ind. Electron., 2001, 48, (4), pp. 757–765 (doi: 10.1109/41.937407).

Login

Not registered yet?

Share

Tools

Login to add to favourites

Key

Design and advanced control strategies of a hybrid energy storage system for the grid integration of wind power generations

References

Related content