access icon free Adaptive predictive control of a small capacity SMES unit for improved frequency control of a wind-diesel power system

© The Institution of Engineering and Technology
Received 06/02/2017, Accepted 15/09/2017, Revised 27/08/2017, Published 18/09/2017

Energy storage is becoming increasingly important for isolated power systems having overall low inertia. Among many energy storage devices, superconducting magnetic energy storage (SMES) is most suited for improved frequency control in isolated power systems, due to its outstanding advantages. However, a small rating SMES device has operational constraints, therefore a suitable control strategy is required for its profitable and constrained operation. An adaptive controller which encapsulates on-line identification with model predictive control is proposed in this paper. A recursive least-squares algorithm is used to identify a reduced-order model of wind-diesel power system on-line. Based on the identified model and a simple discrete time model of SMES unit, an adaptive generalized predictive control scheme (AGPC) considering constraints on SMES current level and converter rating is formulated. The scheme yields a control signal which on one hand keeps the system frequency deviations to minimum and on the other hand forces the SMES device to operate within and near its operational constraints, for profitable operation. Simulation studies are performed to illustrate the potency of the proposed strategy in achieving all the control objectives.

Inspec keywords: wind power plants; predictive control; power system identification; least squares approximations; power convertors; diesel-electric power stations; adaptive control; power generation control; superconducting magnet energy storage; discrete time systems

Other keywords: wind-diesel power system; S-function code; adaptive generalised predictive control scheme; converter rating; AGPC scheme; small capacity SMES unit; reduced-order model; encapsulate online identification; recursive least-square algorithm; isolated power system; SMES device; discrete time model; MATLAB; improved frequency control; superconducting magnetic energy storage device

Subjects: Control of electric power systems; Interpolation and function approximation (numerical analysis); Other energy storage; Superconducting coils and magnets; Power convertors and power supplies to apparatus; Optimal control; Wind power plants; Power system control; Self-adjusting control systems; Discrete control systems; Interpolation and function approximation (numerical analysis); Diesel power stations and plants

References

    1. 1)
      • 16. Ngamroo, I., Vachirasricirikul, S.: ‘Design of optimal SMES controller considering SOC and robustness for microgrid stabilization’, IEEE Trans. Appl. Supercond., 2016, 26, (7), p. 5403005.
    2. 2)
      • 8. Wu, C.J., Lee, Y.S.: ‘Application of superconducting magnetic energy storage unit to improve the damping of synchronous generator’, IEEE Trans. Energy Convers., 1991, 6, (4), pp. 573–578.
    3. 3)
      • 22. Zhang, K., Mao, C., Lu, J., et al: ‘Optimal control of state-of-charge of superconducting magnetic energy storage for wind power system’, IET Renew. Power Gener., 2014, 8, (1), pp. 58–66.
    4. 4)
      • 25. Milano, F., Ortega, A.: ‘Frequency divider’, IEEE Trans. Power Syst., 2017, 32, (2), pp. 1493–1501.
    5. 5)
      • 1. Kaiee, M., Cruden, A., Infield, D., et al: ‘Utilisation of alkaline electrolysers to improve power system frequency stability with a high penetration of wind power’, IET Renew. Power Gener., 2014, 8, (5), pp. 529–536.
    6. 6)
      • 20. Skiles, J.J., Kustom, R.L., Ko, K.P.: ‘Performance of a power conversion system for superconducting magnetic energy storage (SMES)’, IEEE Trans. Power Syst., 1996, 11, (4), pp. 1718–1723.
    7. 7)
      • 23. Ise, T., Murakami, Y., Tsuji, K.: ‘Charging and discharging characteristics of SMES with active filter in transmission system’, IEEE Trans. Magn., 1987, MAG-23, (2), pp. 545–548.
    8. 8)
      • 12. Tripathy, S.C., Juengst, K.P.: ‘Sampled data automatic generation control with superconducting magnetic energy storage’, IEEE Trans. Energy Convers., 1997, 12, (2), pp. 187–192.
    9. 9)
      • 14. Hemeida, A.M.: ‘A fuzzy logic controlled superconducting magnetic energy storage, SMES frequency stabilizer’, Electr. Power Syst. Res., 2010, 80, pp. 651–656.
    10. 10)
      • 19. Ngamroo, I., Mitani, Y., Tsuji, K.: ‘Application of SMES coordinated with solid-state phase shifter to load frequency control’, IEEE Trans. Appl. Supercond., 1999, 9, (2), pp. 322–325.
    11. 11)
      • 7. Chen, S.S., Wang, L., Lee, W.J., et al: ‘Power flow control and damping enhancement of a large wind farm using a superconducting magnetic energy storage unit’, IET Renew. Power Gener., 2009, 3, (1), pp. 23–38.
    12. 12)
      • 2. Yao, J., Yu, M., Gao, W., et al: ‘Frequency regulation control strategy for PMSG wind-power generation system with flywheel energy storage unit’, IET Renew. Power Gener., 2017, 11, (8), pp. 1082–1093.
    13. 13)
      • 11. Iqbal, S.J., Mufti, M.D., Lone, S.A., et al: ‘Intelligently controlled superconducting magnetic energy storage for improved load frequency control’, Int. J. Power Energy Syst., 2009, 29, (4), pp. 241–254.
    14. 14)
      • 9. Tripathy, S.C., Kalantar, M., Balasubramanian, R.: ‘Dynamics and stability of wind and diesel turbine generators with superconducting magnetic energy storage on an isolated power system’, IEEE Trans. Energy Convers., 1991, 6, (4), pp. 579–585.
    15. 15)
      • 21. Mufti, M.D., Iqbal, S.J., Lone, S.A., et al: ‘Supervisory adaptive predictive control scheme for supercapacitor energy storage system’, IEEE Syst. J., 2015, 9, (3), pp. 1020–1030.
    16. 16)
      • 18. Tripathy, S.C., Balasubramanian, R., Chandramohan Nair, P.S.: ‘Effects of superconducting magnetic energy storage on automatic generation control considering governor deadband and boiler dynamics’, IEEE Trans. Power Syst., 1992, 7, (3), pp. 1266–1273.
    17. 17)
      • 10. Hasanien, H.M.: ‘A set-membership affine projection algorithm-based adaptive-controlled SMES units for wind farms output power smoothing’, IEEE Trans. Sustain. Energy, 2014, 5, (4), pp. 1226–1233.
    18. 18)
      • 6. Ali, M.H., Wu, B., Dougal, R.A.: ‘An overview of SMES applications in power and energy systems’, IEEE Trans. Sustain. Energy, 2010, 1, (1), pp. 38–47.
    19. 19)
      • 15. Gong, K., Shi, J., Liu, Y., et al: ‘Application of SMES in the microgrid based on fuzzy control’, IEEE Trans. Appl. Supercond., 2016, 26, p. 3800205.
    20. 20)
      • 17. Ali, M.H., Murata, T., Tamura, J.: ‘Fuzzy logic controlled SMES for damping shaft torsional oscillation of synchronous generator’, IEEJ Trans. Electr. Electron. Eng., 2006, 1, (1), pp. 116–120.
    21. 21)
      • 26. Mufti, M.D., Zargar, M.Y., Lone, S.A.: ‘Predictive controlled SMES for frequency control of hybrid wind- diesel standalone system’. Presented in Int. Conf. Computing, Communication and Automation – ICCCA, 2017, pp. 1–6.
    22. 22)
      • 24. Dechanupaprittha, S., Hongesombut, K., Watanabe, M., et al: ‘Stabilization of tie-line power flow by robust SMES controller for interconnected power system with wind farms’, IEEE Trans. Appl. Supercond., 2007, 17, (2), pp. 2365–2368.
    23. 23)
      • 5. Molina, M.G., Mercado, P.E.: ‘Power flow stabilization and control of microgrid with wind generation by superconducting magnetic energy storage’, IEEE Trans. Power Electron., 2011, 26, (3), pp. 910–922.
    24. 24)
      • 13. Tripathy, S.C., Balasubramanian, R., Chandramohan Nair, P.S.: ‘Adaptive automatic generation control with superconducting magnetic energy storage in power system’, IEEE Trans. Energy Convers., 1992, 7, (3), pp. 434–441.
    25. 25)
      • 3. Wang, S., Tang, Y., Shi, J., et al: ‘Design and advanced control strategies of a hybrid energy storage system for the grid integration of wind power generations’, IET Renew. Power Gener., 2015, 9, (2), pp. 89–98.
    26. 26)
      • 4. Sebastian, R.: ‘Battery energy storage for increasing stability and reliability of an isolated wind diesel power system’, IET Renew. Power Gener., 2017, 11, (2), pp. 296–303.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-rpg.2017.0074
Loading

Related content

content/journals/10.1049/iet-rpg.2017.0074
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading