Hybrid Neuro Fuzzy Approach for Automatic Generation Control of Two -Area Interconnected Power System
The main objective of Automatic Generation Control (AGC) is to balance the total system generation against system load losses so that the desired frequency and power interchange with neighboring systems is maintained. Any mismatch between generation and demand causes the system frequency to deviate from its nominal value. Thus high frequency deviation may lead to system collapse. This necessitates a very fast and accurate controller to maintain the nominal system frequency. This paper deals with a novel approach of artificial intelligence (AI) technique called Hybrid Neuro-Fuzzy (HNF) approach for an (AGC). The advantage of this controller is that it can handle the non-linearities at the same time it is faster than other conventional controllers. The effectiveness of the proposed controller in increasing the damping of local and inter area modes of oscillation is demonstrated in a two area interconnected power system. The result shows that intelligent controller is having improved dynamic response and at the same time faster than conventional controller.
[1] A. J. Wood, B. F. Woolenberg, Power Generation Operation and
Control, John Wiley and Sons, 1984.
[2] O. l. Elgerd, Electric energy Systems Theory - An Introduction,
McGraw Hill Co., 2001.
[3] I. J. Nagrath and D. P. Kothari, Power System Engineering, McGraw
Hill Co., 1998.
[4] G. W. Stagg and A. H. El-Abiad, Computer Methods in Power System
Analysis, McGraw Hill Co., 1985.
[5] N. Jaleeli, L. VanSlyck, D. Ewart, L. Fink, and A. Hoffmann,
"Understanding automatic generation control", IEEE Trans. Power Syst.,
vol. 7, no. 3, pp. 1106-1122, Aug. 1992.
[6] M. L. Kothari, J. Nanda, D. P. Kothari, and D. Das, "Discrete-mode
automatic generation control of a two-area reheat thermal system with
new area control error", IEEE Trans. Power Syst., vol. 4, no. 2, pp. 730-
738, May 1989.
[7] K.Venkateswarlu and A.K. Mahalanabis, "Load frequency control using
output feedback", Journal of The Institution of Engineers (India), pt. El-
4, vol. 58,pp. 200-203,Feb. 1978.
[8] G.A.Chown and R.C.Hartman, "Design and experience with a Fuzzy
Logic Controller for Automatic Generation Control (AGC)", IEEE
Trans. Power Syst., vol. 13, no. 3, pp. 965-970, Nov. 1998.
[9] A.M.Panda, "Automatic generation control of multi area interconnected
power system considering non linearity due to governor dead band",
Archives of Control Sciences,Vol. 7(XLIII), no.3-4, pp. 285-299, 1998.
[10] M. Sheirah and M. M. Abd, "Improved load frequency self tuning
regulator", Int. J. Control, vol. 39, no. 1, 1984, pp. 143-158.
[11] M. Gopal, "Modern control system theory", Wiley Eastern Ltd., 2nd
edison, 1993.
[12] M. Aldeen and H. Trinh, "Load frequency control of interconnected
power system via constrained feedback control schemes", Computer and
Electrical Engineering, Vol. 20, No. 1, 1994, pp. 71-88.
[13] K. Yamashita, and H. Miyagi, " Multivariable Self-tuning regulator for
load frequency control system with interaction of voltage on Load
Demand", IEE Proceedings-D, Vol. 138, No. 2, March 1991.
[14] J. Kannish, et al, "Microprocessor-Based Adaptive load frequency
control", IEE Proceedings-C, Vol. 131, No. 4, July 1984.
[15] S. Mishra, A.K. Pradhan and P.K. Hota, "Development and
Implementation of a Fuzzy logic based constant speed DC Drive",
Journal of Electrical Division of Institution of Engineers (India), Vol.
79, Dec. 1998, pp. 146-149.
[16] J.Lee, "On methods for improving performance of PI-type fuzzy logic
controllers", IEEE Trans. On Fuzzy Systems, Vol. 1, No. 4, Nov. 1993,
pp. 298.
[17] J.R. Jang, "ANFIS: Adaptive-network-Based Fuzzy Inference System",
IEEE Trans. On Systems, Man and Cybernetics, Vol. 23, No.3, May.
1993, pp.665-685.
[18] S. P. Ghoshal, "Multi-Area Frequency and Tie-Line Power Flow Control
with Fuzzy Logic Based Integral Gain Scheduling", IE (I) Journal-EL,
Vol. 84, December 2003, pp. 135-141.
[19] "Fuzzy Logic Toolbox ", Available: www.mathworks.com
[1] A. J. Wood, B. F. Woolenberg, Power Generation Operation and
Control, John Wiley and Sons, 1984.
[2] O. l. Elgerd, Electric energy Systems Theory - An Introduction,
McGraw Hill Co., 2001.
[3] I. J. Nagrath and D. P. Kothari, Power System Engineering, McGraw
Hill Co., 1998.
[4] G. W. Stagg and A. H. El-Abiad, Computer Methods in Power System
Analysis, McGraw Hill Co., 1985.
[5] N. Jaleeli, L. VanSlyck, D. Ewart, L. Fink, and A. Hoffmann,
"Understanding automatic generation control", IEEE Trans. Power Syst.,
vol. 7, no. 3, pp. 1106-1122, Aug. 1992.
[6] M. L. Kothari, J. Nanda, D. P. Kothari, and D. Das, "Discrete-mode
automatic generation control of a two-area reheat thermal system with
new area control error", IEEE Trans. Power Syst., vol. 4, no. 2, pp. 730-
738, May 1989.
[7] K.Venkateswarlu and A.K. Mahalanabis, "Load frequency control using
output feedback", Journal of The Institution of Engineers (India), pt. El-
4, vol. 58,pp. 200-203,Feb. 1978.
[8] G.A.Chown and R.C.Hartman, "Design and experience with a Fuzzy
Logic Controller for Automatic Generation Control (AGC)", IEEE
Trans. Power Syst., vol. 13, no. 3, pp. 965-970, Nov. 1998.
[9] A.M.Panda, "Automatic generation control of multi area interconnected
power system considering non linearity due to governor dead band",
Archives of Control Sciences,Vol. 7(XLIII), no.3-4, pp. 285-299, 1998.
[10] M. Sheirah and M. M. Abd, "Improved load frequency self tuning
regulator", Int. J. Control, vol. 39, no. 1, 1984, pp. 143-158.
[11] M. Gopal, "Modern control system theory", Wiley Eastern Ltd., 2nd
edison, 1993.
[12] M. Aldeen and H. Trinh, "Load frequency control of interconnected
power system via constrained feedback control schemes", Computer and
Electrical Engineering, Vol. 20, No. 1, 1994, pp. 71-88.
[13] K. Yamashita, and H. Miyagi, " Multivariable Self-tuning regulator for
load frequency control system with interaction of voltage on Load
Demand", IEE Proceedings-D, Vol. 138, No. 2, March 1991.
[14] J. Kannish, et al, "Microprocessor-Based Adaptive load frequency
control", IEE Proceedings-C, Vol. 131, No. 4, July 1984.
[15] S. Mishra, A.K. Pradhan and P.K. Hota, "Development and
Implementation of a Fuzzy logic based constant speed DC Drive",
Journal of Electrical Division of Institution of Engineers (India), Vol.
79, Dec. 1998, pp. 146-149.
[16] J.Lee, "On methods for improving performance of PI-type fuzzy logic
controllers", IEEE Trans. On Fuzzy Systems, Vol. 1, No. 4, Nov. 1993,
pp. 298.
[17] J.R. Jang, "ANFIS: Adaptive-network-Based Fuzzy Inference System",
IEEE Trans. On Systems, Man and Cybernetics, Vol. 23, No.3, May.
1993, pp.665-685.
[18] S. P. Ghoshal, "Multi-Area Frequency and Tie-Line Power Flow Control
with Fuzzy Logic Based Integral Gain Scheduling", IE (I) Journal-EL,
Vol. 84, December 2003, pp. 135-141.
[19] "Fuzzy Logic Toolbox ", Available: www.mathworks.com
@article{"International Journal of Electrical, Electronic and Communication Sciences:55642", author = "Gayadhar Panda and Sidhartha Panda and C. Ardil", title = "Hybrid Neuro Fuzzy Approach for Automatic Generation Control of Two -Area Interconnected Power System", abstract = "The main objective of Automatic Generation Control (AGC) is to balance the total system generation against system load losses so that the desired frequency and power interchange with neighboring systems is maintained. Any mismatch between generation and demand causes the system frequency to deviate from its nominal value. Thus high frequency deviation may lead to system collapse. This necessitates a very fast and accurate controller to maintain the nominal system frequency. This paper deals with a novel approach of artificial intelligence (AI) technique called Hybrid Neuro-Fuzzy (HNF) approach for an (AGC). The advantage of this controller is that it can handle the non-linearities at the same time it is faster than other conventional controllers. The effectiveness of the proposed controller in increasing the damping of local and inter area modes of oscillation is demonstrated in a two area interconnected power system. The result shows that intelligent controller is having improved dynamic response and at the same time faster than conventional controller.
", keywords = "Automatic Generation Control (AGC), Dynamic
Model, Two-area Power System, Fuzzy Logic Controller, Neural
Network, Hybrid Neuro-Fuzzy(HNF).", volume = "5", number = "10", pages = "1338-5", }
