Skip to main content

An ANN-Based Power System Emergency Control Scheme in the Presence of High Wind Power Penetration

  • Chapter

Part of the book series: Green Energy and Technology ((GREEN,volume 0))

Abstract

Re-evaluation of emergency control and protection schemes for distribution and transmission networks are one of the main problems posed by wind turbines in power systems. Change of operational conditions and dynamic characteristics influence the requirements to control and protection parameters.

Introducing a significant wind power into power systems leads to new undesirable oscillations. The local and inter-modal oscillations during large disturbances can cause frequency and voltage relays to measure a quantity at a location that is different to the actual underlying system voltage and frequency gradient. From an operational point of view, this issue is important for those networks that use the protective voltage and frequency relays to re-evaluate their tuning strategies.

In this chapter, an overview of the key issues in the use of high wind power penetration in power system emergency control is presented. The impact of wind power fluctuation on system frequency, voltage and frequency gradient is analyzed, the need for the revising of tuning strategies for frequency protective relays, automatic under-frequency load shedding (UFLS) and under-voltage load shed-ding (UFLS) relays are also emphasized.

In the present chapter, necessity of considering both system frequency and voltage indices to design an effective power system emergency control plan is shown. Then, an intelligent artificial neural network (ANN) based emergency control scheme considering the dynamic impacts of wind turbines is proposed. In the developed algorithm, following an event, the related contingency is determined by an appropriate ANN using the online measured tie-line powers. A suitable set of voltage sensitivity indices based on a comprehensive voltage stability analysis in the presence of the wind turbines is proposed. Another intelligent ANN is used to examine the stability margin by estimating the system power-voltage (P-V) curves. Finally, the system frequency gradient, voltage sensitivity indices and stability information are properly used by an effective load shedding algorithm. The proposed emergency control scheme and discussions are supplemented by computer nonlinear simulations on the IEEE 9-bus test system.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alexander, J.F., Renuka, G., Jayabharath, R.D.: New Power Sensitivity Method of Ranking Branch Outage Contingencies for Voltage Collapse. IEEE Transactions on Power Systems 17(2), 265–270 (2002)

    Article  Google Scholar 

  2. Bevrani, H.: Robust Power System Frequency Control. Springer, New York (2009)

    MATH  Google Scholar 

  3. Bevrani, H., Ledwich, G., Ford, J.J.: On the Use of df/dt in Power System Emergency Control. In: Proceedings 2009 IEEE Power Systems Conference & Exposition, Seattle, Washington, USA (2009)

    Google Scholar 

  4. Bevrani, H., Ledwich, G., Dong, Z.Y., Ford, J.J.: Regional Frequency Response Analysis under Normal and Emergency Conditions. Electric Power Systems Research 79, 837–845 (2009)

    Article  Google Scholar 

  5. Bevrani, H., Ledwich, G., Ford, J.J., Dong, Z.Y.: On Power System Frequency Control in Emergency Conditions. Journal of Electrical Engineering & Technology 3(4), 499–508 (2008)

    Google Scholar 

  6. Bevrani, H., Hiyama, T.: On Load-Frequency Regulation with Time Delays: Design and Real Time Implementation. IEEE Transactions on Energy Conversion 24(1), 292–300 (2009)

    Article  Google Scholar 

  7. Bevrani, H., Ghosh, A., Ledwich, G.: Renewable Energy Resources and Frequency regulation: Survey and New Perspectives. Will be submitted to IET Renewable Power Generation (2009)

    Google Scholar 

  8. Bijwe, P.R., Nanda, J., Puttabuddhi, K.L.: Ranking of line outages in an AC-DC system causing overload and voltage problems. IEE Proceedings-C 138(3), 207–211 (1991)

    Google Scholar 

  9. Claudio, A.C., Nadarajah, M., Federico, M., John, R.: Linear Performance Indices to Predict Oscillatory Stability Problems in Power Systems. IEEE Transactions on Power Systems 19(2), 1104–1114 (2004)

    Article  Google Scholar 

  10. Ejebe, G.C., Wollenberg, B.F.: Automatic Contingency Selection. IEEE Transactions on Power Apparatus and Systems PAS-98(1), 97–109 (1979)

    Article  Google Scholar 

  11. El-Saadawi, M.M., Kaddah, S.S., Osman, M.G., Abdel-Wahab, M.N.: Impact of wind farms on contingent power system voltage stability. In: 12th International Middle-East Power System Conference, pp. 637–644 (2008)

    Google Scholar 

  12. Erlich, I., Rensch, K., Shewarega, F.: Impact of large wind power generation on frequency stability. In: Proc. of Power Engineering Society General Meeting (2006) (CD ROM)

    Google Scholar 

  13. Ford, J.J., Bevrani, H., Ledwich, G.: Adaptive Load Shedding and Regional Protection. International Journal of Electrical Power and Energy Systems 31, 611–618 (2009)

    Article  Google Scholar 

  14. FRCC Automatic Underfrequency Load Shedding Program, PRC-006-FRCC-01 (2009), https://www.frcc.com/

  15. Fu, X., Wang, X.: Load Shedding Scheme Ensuring Voltage Stability. In: Power Engineering Society General Meeting IEEE, pp. 1–6 (2007)

    Google Scholar 

  16. Gillian, L., Alan, M., Mark, O.M.: Frequency Control and Wind Turbine Technologies. IEEE Transactions on Power Systems 20(4), 1905–1913 (2005)

    Article  Google Scholar 

  17. Gu, X., Canizares, C.A.: Fast prediction of load ability margins using neural networks to approximate security boundaries of power systems. IET Gener. Transm. Distrib., 466–475 (2007)

    Google Scholar 

  18. IEEE PES, power and energy magazine 7(2), March/April Issue (2009)

    Google Scholar 

  19. Jadid, S., Jalilzadeh, S.: Application of Neural Network for Contingency Ranking Based on Combination of Severity Indices. In: Proceedings of World Academy of Science, Engineering and Technology, vol. 5 (2005)

    Google Scholar 

  20. Kundur, P.: Power System Stability and Control. McGraw-Hill, New York (1994)

    Google Scholar 

  21. Marcus, V.A.N., Ja, P.L., Hans, H.Z., Ubiratan, H.B., Rogério, G.A.: Influence of the Variable-Speed Wind Generators in Transient Stability Margin of the Conventional Generators Integrated in Electrical Grids. IEEE Transactions on Energy Conversion 19(4), 692–701 (2004)

    Article  Google Scholar 

  22. Moura, R.D., Prada, R.B.: Contingency screening and ranking method for voltage stability assessment. IEE Proc.-Gener. Transm. Distrib. 152(6), 891–898 (2005)

    Article  Google Scholar 

  23. Mukhtiar, S., Ambrish, C.: Power Maximization and Voltage Sag/Swell Ride- through Capability of PMSG based Variable Speed Wind Energy Conversion System. In: Annual Conference of IEEE on Industrial Electronics, vol. 34, pp. 2206–2211 (2008)

    Google Scholar 

  24. Naoto, Y., Hua-Qiang, L., Hiroshi, S.: A Predictor/Corrector Scheme for Obtaining Q-Limit Points for Power Flow Studies. IEEE Transactions on Power Systems 20(1), 130–137 (2005)

    Article  Google Scholar 

  25. Oscar, E.M.: A Spinning Reserve, Load Shedding, and Economic Dispatch Solution by Bender’s Decomposition. IEEE Transactions on Power Systems 20(1), 384–388 (2005)

    Article  Google Scholar 

  26. Pengcheng, Z., Gareth, T., Malcolm: A Novel Q-Limit Guided Continuation Power Flow Method. In: Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy, July 20-24, pp. 1–7 (2008)

    Google Scholar 

  27. Power Systems Relaying Committee, IEEE Guide for the Application of Protective Relays Used for Abnormal Frequency Load Shedding and Restoration. IEEE Std C37.117TM, pp. c1–c43 (2007)

    Google Scholar 

  28. Faranda, R., Pievatolo, A., Tironi, E.: Load Shedding: A New Proposal. IEEE Transactions on Power Systems 22(4), 2086–2093 (2007)

    Article  Google Scholar 

  29. Mark, S.H., Keith, A.H., Robert, A.J., Lee, Y.T.: Slope-Permissive Under-Voltage Load Shed Relay for Delayed Voltage Recovery Mitigation. IEEE Transactions on Power 23(3), 1211–1216 (2008)

    Article  Google Scholar 

  30. Simon, H.: Neural Network a Comprehensive foundation. Prentice hall international, Inc., Englewood Cliffs (1999)

    Google Scholar 

  31. Shao-Hua, L., Hsiao-Dong, C.: Continuation Power Flow with Multiple Load Variation and Generation Re-Dispatch Patterns. In: Proc of Power Engineering Society General Meeting (2006) CD ROM

    Google Scholar 

  32. Smith, J.C.: Winds of change: Issues in utility wind integration. IEEE Power Energy Mag. 3(6), 20–25 (2005)

    Article  Google Scholar 

  33. Shu-Jen, S.T., Kim-Hoi, W.: Adaptive Under-voltage Load Shedding Relay Design Using Thevenin Equivalent Estimation. In: Power and Energy Society General Meeting, pp. 1–8, July 20-24 (2008)

    Google Scholar 

  34. Tarlochan, S.S., Lan, C.: Contingency Screening for Steady-State Security Analysis By Using FFT and Artificial Neural Networks. WEE Transactions on Power Systems 15(1), 421–426 (2000)

    Article  Google Scholar 

  35. Thelma, S.P.F., Lenzi, J.R., Miguel, A.M.: Load Shedding Strategies Using Optimal Load Flow with Relaxation of Restrictions. IEEE Transactions on Power Systems 23(2), 712–718 (2008)

    Article  Google Scholar 

  36. Tikdari, A.: Load Shedding in the Presence of Renewable Energy Sources in a Restructured Power System Environment, Master Thesis, University of Kurdistan (2009)

    Google Scholar 

  37. Venkataramana, A.: Computational Techniques for Voltage Stability Assessment and Control. Springer, Heidelberg (2006)

    Google Scholar 

  38. Venkataramana, A., Colin, C.: The Continuation Power Flow a Tool for Steady State Voltage Stability Analysis. Transactions on Power Systems 7(1), 416–423 (1992)

    Article  Google Scholar 

  39. Vladimir, V.T.: Under-frequency Load Shedding Based on the Magnitude of the Disturbance Estimation. IEEE Transactions on Power Systems 21(3), 1260–1266 (2006)

    Article  Google Scholar 

  40. Vidya, S.S.V., Nutakki, D.R.: Contingency Screening through Optimizing Hopfield Neural Networks Canadian Conference on Electrical and Computer Engineering, vol. 1, pp. 199–204 (1993)

    Google Scholar 

  41. Yeu, R.H., Sauer, P.W.: Post-Contingency Equilibrium Analysis Techniques for Power Systems. In: Annual North American Power Symposium, vol. 37, pp. 429–433 (2005)

    Google Scholar 

  42. Yongning, C., Yanhua, L., Weisheng, W., Huizhu, D.: Voltage Stability Analysis of Wind Farm Integration into Transmission Network. In: International Conference on Power System Technology, pp. 1–7 (2006)

    Google Scholar 

  43. Yuri, V.M., Viktor, I.R., Vladimir, A.S., Nikolai, I.V.: Blackout Prevention in the United States, Europe, and Russia. IEEE Transactions on Energy Conversion 14(3), 749–753 (1999)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer Berlin Heidelberg

About this chapter

Cite this chapter

Bevrani, H., Tikdari, A.G. (2010). An ANN-Based Power System Emergency Control Scheme in the Presence of High Wind Power Penetration. In: Wang, L., Singh, C., Kusiak, A. (eds) Wind Power Systems. Green Energy and Technology, vol 0. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13250-6_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-13250-6_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13249-0

  • Online ISBN: 978-3-642-13250-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics