access icon free Emergency wind power plant re-dispatching against transmission system cascading failures using reverse tracking of line power flow

Due to high wind power penetration into power system, synchronous generators may no longer be the dominant generation, which implicitly requires participation of wind power plants (WPPs) in the load-frequency control (LFC). Frequency, a common variable throughout the entire power system, is the key variable for LFC, which causes equal contribution of all distant and nearby WPPs in LFC. Power transfer from distant WPPs to the event location may overload the middle transmission lines leading to cascading failures. This study proposes an online dispatch rescheduling algorithm for WPPs participating in the LFC task to prevent over loading of transmission lines and hence cascading failures following severe frequency contingencies. The WPP dispatch limits are calculated based on line ampacity for each generation unit participating in the LFC task. Numerical simulations carried out in DigSilent PowerFactory on 39 bus IEEE standard test system, demonstrates the efficiency of suggested online dispatch rescheduling technique for keeping the loading rate of transmission lines, bus voltages and system frequency in range.

Inspec keywords: power generation dispatch; frequency control; power generation scheduling; load flow control; power transmission reliability; wind power plants; power transmission protection; power generation control; power transmission lines; IEEE standards

Other keywords: reverse tracking; WPP dispatch limits; nearby WPP; LFC task; transmission lines; frequency contingencies; online dispatch rescheduling algorithm; online dispatch rescheduling technique; DigSilent PowerFactory; overloading prevention; wind power plants; 39 bus IEEE standard test system; distant WPP; emergency wind power plant redispatching; generation unit; line power flow; power transfer; transmission system cascading failures; system frequency; line ampacity; bus voltages; numerical simulation; load-frequency control; high wind power penetration; power system

Subjects: Power transmission lines and cables; Power transmission, distribution and supply; Frequency control; Power system control; Power system protection; Power system management, operation and economics; Reliability; Wind power plants; Control of electric power systems

References

    1. 1)
      • 18. Pavlovsky, V., Steliuk, A., Lenga, O., et al: ‘Frequency stability simulation considering underfrequency load shedding relays,special protection automatics and agc software models’. 2017 IEEE Manchester PowerTech, Manchester, UK, 2017, pp. 15.
    2. 2)
      • 7. Liao, K., Xu, Y.: ‘A robust load frequency control scheme for power systems based on second-order sliding mode and extended disturbance observer’, IEEE Trans. Ind. Inf., 2018, 14, (7), pp. 30763086.
    3. 3)
      • 17. Mohamed, E.A., Magdy, G., Mitani, Y.: ‘Digital frequency protection for micro-grid coordinated with lfc considering high pv/wind penetration level’. 2018 6th Int. Istanbul Smart Grids and Cities Congress and Fair (ICSG), Istanbul, Turkey, 2018, pp. 6266.
    4. 4)
      • 3. Hoseinzadeh, B., Bak, C.L.: ‘Centralized coordination of emergency control and protection system using online outage sensitivity index’, Electr. Power Syst. Res., 2018, 163, pp. 413422.
    5. 5)
      • 8. Liu, F., Ma, J.: ‘Equivalent input disturbance-based robust lfc strategy for power system with wind farms’, IET Gener. Transm. Distrib., 2018, 12, (20), pp. 45824588.
    6. 6)
      • 26. Kundur, P.: ‘Power system stability and control’ (Tata McGraw-Hill Education, New York, NY, USA, 1994).
    7. 7)
      • 16. Ramachandran, R., Madasamy, B., Veerasamy, V., et al: ‘Load frequency control of a dynamic interconnected power system using generalised hopfield neural network based self-adaptive pid controller’, IET Gener. Transm. Distrib., 2018, 12, (21), pp. 57135722.
    8. 8)
      • 12. Mir, A.S., Senroy, N.: ‘Adaptive model predictive control scheme for application of smes for load frequency control’, IEEE Trans. Power Syst., 2017, pp. 11.
    9. 9)
      • 24. Saffarian, A., Sanaye-Pasand, M.: ‘Enhancement of power system stability using adaptive combinational load shedding methods’, IEEE Trans. Power Syst., 2011, 26, (3), pp. 10101020.
    10. 10)
      • 11. Ma, M., Liu, X., Zhang, C.: ‘Lfc for multi-area interconnected power system concerning wind turbines based on DMPC’, IET Gener. Transm. Distrib., 2017, 11, (10), pp. 26892696.
    11. 11)
      • 6. Ojaghi, P., Rahmani, M.: ‘Lmi-based robust predictive load frequency control for power systems with communication delays’, IEEE Trans. Power Syst., 2017, 32, (5), pp. 40914100.
    12. 12)
      • 15. Qian, D., Fan, G.: ‘Neural-network-based terminal sliding mode control for frequency stabilization of renewable power systems’, IEEE/CAA J. Autom. Sin., 2018, 5, (3), pp. 706717.
    13. 13)
      • 13. Li, H., Wang, X., Xiao, J.: ‘Adaptive event-triggered load frequency control for interconnected microgrids by observer-based sliding mode control’, IEEE Access, 2019, 7, pp. 6827168280.
    14. 14)
      • 21. Pai, M.: ‘Energy function analysis for power system stability’ (Springer, New York, NY, USA, 1989).
    15. 15)
      • 19. Xie, D., Xu, Z., Yang, L., et al: ‘A comprehensive lvrt control strategy for dfig wind turbines with enhanced reactive power support’, IEEE Trans. Power Syst., 2013, 28, (3), pp. 33023310.
    16. 16)
      • 5. Khooban, M., Niknam, T., Shasadeghi, M., et al: ‘Load frequency control in microgrids based on a stochastic noninteger controller’, IEEE Trans. Sustain. Energy, 2018, 9, (2), pp. 853861.
    17. 17)
      • 14. Xu, D., Liu, J., Yan, X., et al: ‘A novel adaptive neural network constrained control for a multi-area interconnected power system with hybrid energy storage’, IEEE Trans. Ind. Electron., 2018, 65, (8), pp. 66256634.
    18. 18)
      • 2. Andersson, G., Donalek, P., Farmer, R., et al: ‘Causes of the 2003 major grid blackouts in North America and Europe, and recommended means to improve system dynamic performance’, IEEE Trans. Power Syst., 2005, 20, (4), pp. 19221928.
    19. 19)
      • 4. Hoseinzadeh, B., Faria-Silva, F., Leth-Bak, C.: ‘Decentralized coordination of load shedding and plant protection considering high share of RESs’, IEEE Trans. Power Syst., 2016, 31, (5), pp. 36073615.
    20. 20)
      • 25. Margaris, I.D., Papathanassiou, S.A., Hatziargyriou, N.D., et al: ‘Frequency control in autonomous power systems with high wind power penetration’, IEEE Trans. Sustain. Energy, 2012, 3, (2), pp. 189199.
    21. 21)
      • 1. Hoseinzadeh, B., Leth-Bak, C.: ‘Centralized coordination of load shedding and protection system of transmission lines’, Int. Trans. Electr. Energy Syst., 2018, 29, (1), p. e2674.
    22. 22)
      • 22. IEEE: ‘Ieee guide for the application of protective relays used for abnormal frequency load shedding and restoration’. IEEE Std C37117-2007, Power System Relaying Committee, 2007, pp. 143.
    23. 23)
      • 10. Liu, X., Zhang, Y., Lee, K.Y.: ‘Coordinated distributed mpc for load frequency control of power system with wind farms’, IEEE Trans. Ind. Electron., 2017, 64, (6), pp. 51405150.
    24. 24)
      • 9. Ma, M., Zhang, C., Liu, X., et al: ‘Distributed model predictive load frequency control of the multi-area power system after deregulation’, IEEE Trans. Ind. Electron., 2017, 64, (6), pp. 51295139.
    25. 25)
      • 20. Hoseinzadeh, B., Faria-Silva, F., Leth-Bak, C.: ‘Malfunction operation of lvrt capability of wind turbines under islanding conditions’. 2015 Power Tech Conf. Proc., Eindhoven, Netherland, 2015, pp. 15.
    26. 26)
      • 23. GmbH D: ‘Powerfactory, digsilent, version 20.0’. DIgSILENT International, Germany, 2020.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2019.1950
Loading

Related content

content/journals/10.1049/iet-gtd.2019.1950
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading