This paper presents the development and application of an adaptive neuro fuzzy inference system (ANFIS) based intelligent hybrid neuro fuzzy controller for automatic generation control (AGC) of two-area interconnected thermal power system with reheat non linearity. The dynamic response of the system has been studied for 1% step load perturbation in area-1. The performance of the proposed neuro fuzzy controller is compared against conventional proportional-integral (PI) controller, state feedback linear quadratic regulator (LQR) controller and fuzzy gain scheduled proportionalintegral (FGSPI) controller. Comparative analysis demonstrates that the proposed intelligent neuro fuzzy controller is the most effective of all in improving the transients of frequency and tie-line power deviations against small step load disturbances. Simulations have been performed using Matlab®.<\/p>\r\n","references":"[1] O. I. Elgerd, Electric Energy Systems Theory: An Introduction. New\r\nYork: McGraw-Hill, 1982.\r\n[2] Kundur, P. Power system stability and control, McGraw-Hill, Inc.,1994.\r\n[3] Ibraheem, Prabhat Kumar, and Dwarka P. Kothari, \"Recent philosophies\r\nof automatic generation control strategies in power systems,\" IEEE\r\nTransactions On Power Systems, vol. 20, no. 1, pp. 346-57, February 2005.\r\n[4] C. S. Indulkar and B. Raj, \"Application of fuzzy controller to automatic generation control,\" Elect. Machines Power Syst., vol. 23, no. 2, pp. 209-220, Mar.-Apr. 1995.\r\n[5] Chang C.S., Fu W., \"Area load-frequency control using fuzzy gain scheduling of PI controllers,\" Electric Power system Research, vol. 42,\r\nno. 2, pp. 145-52, 1997.\r\n[6] J. Talaq and F. Al-Basri, \"Adaptive fuzzy gain scheduling for loadfrequency\r\ncontrol,\" IEEE Trans. Power Syst., vol. 14, no. 1, pp. 145-\r\n150, Feb. 1999.\r\n[7] D. K. Chaturvedi, P. S. Satsangi, and P. K. Kalra, \"Load frequency control: A generalized neural network approach,\" Elect. Power Energy Syst., vol. 21, no. 6, pp. 405-415, Aug. 1999.\r\n[8] Y. L. Karnavas and D. P. Papadopoulos, \"AGC for autonomous power\r\nsystem using combined intelligent techniques,\" Elect. Power Syst. Res.,\r\nvol. 62, no. 3, pp. 225-239, Jul. 2002.\r\n[9] S. K. Aditya and D. Das, \"Design of load frequency controllers using\r\ngenetic algorithm for two area interconnected hydro power system,\" Elect. Power Compon. Syst., vol. 31, no. 1, pp. 81-94, Jan. 2003.\r\n[10] Ibhan Kocaarslan, Ertugrul Cam, \"Fuzzy logic controller in interconnected electric power systems for load-frequency control,\"\r\nElectrical Power and Energy Systems, vol. 27,no. 8, pp. 542-549, 2005.\r\n[11] L. H. Hassan, H. A. F. Mohamed, M. Moghavvemi, S. S. Yang,\r\n\"Automatic generation control of power system with fuzzy gain scheduling integral and derivative controllers\", International Journal of\r\nPower, Energy and Artificial Intelligence, vol. 1, no. 1, pp. 29-33, August 2008.\r\n[12] Gayadhar Panda, Sidhartha Panda and Cemal Ardil, \u201cAutomatic \r\nGeneration Control of Interconnected Power System with Generation \r\nRate Constraints by Hybrid Neuro Fuzzy Approach,\u201d Int. J. of Electrical \r\nand Electronics Engineering, vol. 3, no. 9, pp. 532-537, 2009. \r\n[13] J.S.R. Jang, \u201cANFIS: Adaptive-Network-Based Fuzzy Inference \r\nSystem,\u201d IEEE Trans. Syst., Man, Cybern., vol. 23, no. 3, pp. 665\u2013685, \r\n1993. \r\n[14] Porter, B., \u201cOptimal control of multivariable systems incorporahng \r\nintegral feedback,\u201d Electronics Letters, vol 7, pp 170-172, 1971. \r\n[15] Reddoch, P., Julich, T. Tan, and Tacker, E., \u201cModels and performance \r\nfunctional for load frequency control in interconnected power systems,\u201d \r\nIEEE Conf. on Decision and Control, Florida, Dec. 1971. ","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 60, 2011"}