Integration of Acceleration Feedback Control with Automatic Generation Control in Intelligent Load Frequency Control

This paper investigates the effects of knowledge-based acceleration feedback control integrated with Automatic Generation Control (AGC) to enhance the quality of frequency control of governing system. The Intelligent Acceleration Feedback Controller (IAFC) is proposed to counter the over and under frequency occurrences due to major load change in power system network. Therefore, generator tripping and load shedding operations can be reduced. Meanwhile, the integration of IAFC with AGC, a well known Load-Frequency Control (LFC) is essential to ensure the system frequency is restored to the nominal value. Computer simulations of frequency response of governing system are used to optimize the parameters of IAFC. As a result, there is substantial improvement on the LFC of governing system that employing the proposed control strategy.





References:
[1] Working Group J6 of the Rotating Machinery Protection Subcommittee,
Power System Relaying Committee., "Performance of Generator
Protection During Major System Disturbances," IEEE Transactions on
Power Delivery, Vol. 10, No. 1, pp. 195-195, March 1995.
[2] P. Kundur, Power System Stability and Control (Electrical Power
Research Institute), McGraw-Hill, Inc., pp. 581-626, 1994.
[3] IEEE Std C37.117™-2007, IEEE Guide for the Application of
Protective Relays Used for Abnormal Frequency Load Shedding and
Restoration
[4] A. A. Mohd. Zin, H. Mohd. Hafiz, M. S. Aziz, "A Review of Under -
frequency Load Shedding Scheme on TNB System", Proceedings on
National Power & Energy Conference (PECon) 2004, pp. 170-174,
Kuala Lumpur, Malaysia
[5] Bulgarian Grid Code, Bulgaria State Energy Regulatory Commission
[6] Gujarat Electricity Regulatory Commission (GERC), Gujarat Electricity
Grid Code, Notification: No. 5 of 2004.
[7] National Electricity Code Administrator, Reliability Panel Frequency
Standards Consultation Paper, March 1999.
[8] J.W. Kim, S.W. Kim, "Design of incremental fuzzy PI controllers for a
gas-turbine plant," IEEE/ASME Transactions on Mechatronics, Vol. 8,
No. 3, pp. 410-414, Sept. 2003.
[9] S. Jovanovic, B.W. Hogg, B. Fox, "Intelligent adaptive turbine
controller," IEEE Transactions on Energy Conversion, Vol. 10, No. 1,
pp. 195-198, March 1995.
[10] B.W. Hogg, S. Jovanovic, B. Fox, E. Swidenbank, "Intelligent adaptive
control of a multi-machine power system," 12th World IFAC Congress,
July 1993, Sydney, Australia.
[11] T. Hiyama, "Rule-based stabilizer for multi-machine system," IEEE
Transactions on Power Systems, Vol. 5, No. 2, pp. 403-411, May 1990.
[12] S.P. Ghoshal, "Multi-area frequency and tie-line power flow control
with fuzzy logic based integral gain scheduling," The Institution of
Engineers (India)-Technical Journals: Electrical Engineering, Vol. 84,
pp. 135-141, Dec. 2003.
[13] K. Warwick, A. Ekwue, R. Aggarwal (Eds), Artificial Intelligence
Techniques in Power Systems, The Institute of Electrical Engineers,
London, 1997.
[14] M. Nagpal, A. Moshref, G.K. Morison, P. Kundur, "Experience with
testing and modeling of gas turbines", Proceeding IEEE/Power
Engineering Society Winter Meeting, Vol. 2, pp. 652-656, 28 Jan.-1 Feb.
2001.