Automatic Generation Control of Multi-Area Electric Energy Systems Using Modified GA
A modified Genetic Algorithm (GA) based optimal selection of parameters for Automatic Generation Control (AGC) of multi-area electric energy systems is proposed in this paper. Simulations on multi-area reheat thermal system with and without consideration of nonlinearity like governor dead band followed by 1% step load perturbation is performed to exemplify the optimum parameter search. In this proposed method, a modified Genetic Algorithm is proposed where one point crossover with modification is employed. Positional dependency in respect of crossing site helps to maintain diversity of search point as well as exploitation of already known optimum value. This makes a trade-off between exploration and exploitation of search space to find global optimum in less number of generations. The proposed GA along with decomposition technique as developed has been used to obtain the optimum megawatt frequency control of multi-area electric energy systems. Time-domain simulations are conducted with trapezoidal integration along with decomposition technique. The superiority of the proposed method over existing one is verified from simulations and comparisons.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1076816Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2226
 J. Wood, B. F. Woolenberg, Power Generation Operation and Control, John Wiley and Sons, 1984.
 O. l. Elgerd, Electric energy Systems Theory - An Introduction, McGraw Hill Co., 2001.
 J. Nanda and B. Kaul, "Automatic generation control of an interconnected power system", IEE Proc., Vol. 125, no. 5, May 1978, pp. 385-390.
 O. I. Elgerd and C. E. Fosha, ., "Optimum megawatt-frequency control of multi-area electric energy systems", IEEE Trans. On PAS, vol. PAS- 89, no. 4, April 1970, pp. 556-563.
 M. Aldden and H. Trinh, "Load frequency control of interconnected power systems via constrained feedback control schemes", Computer and Electrical Engineering, Vol. 20, no. 1, 1994, pp. 71-88.
 H.J. Kunish, K.G. Kramer and H. D. Dominik, "Battery energy storage - Another option for load-frequency control and instantaneous reserve", IEEE Trans. Energy Convers., vol. EC-1, no. 3, Sept. 1986, pp. 46-51.
 S. Banerjee, J.K. Chatterjee and S.C. Tripathy, "Application of magnetic energy storage unit as load frequency stabilizer", IEEE Trans. Energy Convers., vol. 5, no. 1, March 1990, pp. 46-51.
 Y.L. Karnavas and D.P. Papadopoulos,"AGC for autonomous power system using combined intelligent techniques", Electric Power System Research, 62 (2002), 225-239.
 Y.L. Abdel-Magid and M.M. Dawound, "Optimal AGC tuning with genetic algorithms", Electric Power System Research, 38 (1997), 231- 238.
 S.K. Aditya and D. Das, "Design of load frequency controllers using genetic algorithm for two-area interconnected hydro power system", Elect. Power Compon. Syst., vol. 31, no. 1, Jan. 2003, pp. 81-94.
 Z. M. Al-Hamouz, and H. N. Al-Dowaish, "A New Load Frequency Variable Structure Controller using Genetic Algorithms", Elect. Power Syst. Res., vol. 55, no. 1, July 2000, pp. 1-6.
 D. Rerkpreedapong, A. Hasanovic and A. Feliachi, "Robust Load Frequency Control using Genetic Algorithms and Linear Matrix Inequalities", IEEE Trans. Power Syst., vol. 18, no. 2, May 2003, pp. 855-861.
 A.M. Panda, "Automatic generation control of multi area interconnected power system considering nonlinearity due to governor deadband", Archives of control sciences, Vol. 7(XLIII), no. 3-4, March 1998, pp. 285-299.
 W. Chan and Y. Hsu, "Optimal control of power generation using variable structure controllers", Elect. Power Syst. Res.", vol. 6, 1983, pp. 269-276.