DECENTRALIZED AND NERC COMPLIANT ADAPTIVE IMMUNE-BASED LOAD FREQUENCY CONTROL WITH DIFFERENT WIND PENETRATIONS

Arjan Rimal and Rabie Belkacemi

References

  1. [1] NERC Standard BAL-002-0. Disturbance control performance,http://www.nerc.com/files/BAL-002-0.pdf.
  2. [2] NERC Standard BAL-003-0a. Frequency response and bias,http://www.nerc.com/files/BAL-003-0a.pdf.
  3. [3] P.K. Ibraheem and D.P. Kothari, Recent philosophies of au-tomatic generation control strategies in power systems, IEEETransactions of Power Systems, 20 (1), 2005, 346–357.
  4. [4] X. Yingcheng and T. Nengling, Review of contribution to fre-quency control through variable speed wind turbine, RenewableEnergy, 36(6), 2011, 1671–1677.
  5. [5] F. Beaufays, Y. Abdel-Magid, and B. Widrow, Application ofneural networks to load–frequency control in power systems,Neural Networks, 7(1), 1994, 183–194.
  6. [6] H. Shayeghi and H.A. Shayanfar, Application of ANN techniquebased on µ-synthesis to load frequency control of interconnectedpower system, International Journal of Electrical Power andEnergy Systems, 28(7), 2006, 503–511.
  7. [7] D.K. Chaturvedi, P.S. Satsangi, and P.K. Kalra, Load frequencycontrol: A generalised neural network approach, InternationalJournal of Electrical Power and Energy Systems, 21(6), 1999,405–415.
  8. [8] R.A. Shoureshi, B. Hoffner, Z. Hu, and R.A. Kramer, Neural-based generation control for highly varying and uncertain loads,IEEE Porto Power Tech Proceedings, Porto, 2001.
  9. [9] S. Baqqali and M. Makoudi, Decentralized adaptive controlfor a class of nonlinear continuous time interconnected systemusing neural networks, Control and Intelligent Systems, 35(1),2007, p. 1.
  10. [10] S.P. Ghoshal and S.K. Goswami, Application of GA basedoptimal integral gains in fuzzy based active power-frequencycontrol of non-reheat and reheat thermal generating systems,Electrical Power Systems. Research, 67(2), 2003, 79–88.
  11. [11] Y.-W. Huang and P.-C. Tung, Fuzzy PD system in adaptivecontrol systems having input saturation, Control and IntelligentSystems, 35(3), 2007, p. 217.
  12. [12] H. Bevrani and P. Daneshmand, Fuzzy logic-based load–frequency control concerning high penetration of wind turbines,IEEE Systems Journal, 6(1), 2012, 173–180.
  13. [13] R.G. de Almeida and J.A.P. Lopes, Participation of doublyfed induction wind generators in system frequency regulation,IEEE Transactions on Power Systems, 22(3), 2007, 944–950.
  14. [14] G. Delille, B. Francois, and G. Malarange, Dynamic frequencycontrol support by energy storage to reduce the impact of windand solar generation on isolated power system’s inertia, IEEETransactions on Sustainable Energy, 3(4), 2012, 931–939.
  15. [15] V. Pandian, B. Nader, and W. Jeffrey, Dynamic analysis andstability improvement concerning the integration of wind farms:Kurdistan electric network case study, Innovation in Power,Control, and Optimization – Emerging Energy Technologies,Vol. 6, IGI Global, 2012, 1.
  16. [16] J. Nanda and A. Mangla, Automatic generation control ofan interconnected hydro-thermal system using conventionalintegral and fuzzy logic controller, 2004 IEEE InternationalConference on Electric Utility Deregulation, Restructuring andPower Technologies, 2004.
  17. [17] J.M. Mauricio, A. Marano, A. Gomez-Exposito, and J.L.Martinez Ramos, Frequency regulation contribution throughvariable-speed wind energy conversion systems, IEEE Trans-actions on Power Systems, 2009.
  18. [18] A. Feliachi, A decentralized immune based automatic gener-ation control design in compliance with NERC’s standards,2009 IEEE/PES Power Systems Conference and Exposition,Seattle, WA, USA, 2009.
  19. [19] D. Dasgupta, Artificial immune systems and their applications,Springer Berlin Heidelberg, 1999.
  20. [20] C. Wang and J.D. McCalley, Impact of wind power on controlperformance standards, International Journal of ElectricalPower Energy Systems, 47(2013), 2012, 225–234.73

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