Hybrid Taguchi Genetic Algorithm-Based AGC Controller for Multisource Interconnected Power System

References

• S. K. Aditya, and D. Das, “Design of load frequency controllers using genetic algorithm for two area interconnected hydro power system,” Electr. Power Component Syst., vol. 31, no. 1, pp. 81–94, 2003.
   Web of Science ®Google Scholar
• L. C. Saikia, and S. K. Sahu, “Automatic generation control of a combined cycle gas turbine plant with classical controllers using firefly algorithm,” Int. J. Electr. Power Energy Syst., vol. 53, pp. 27–33, 2013.
   Web of Science ®Google Scholar
• S. Bhatti, and I. Nizamuddin. “Automatic generation control in an interconnected power system incorporating diverse source power plants using bacteria foraging optimization technique,” Electr. Power Components Syst., vol. 43, no. 2, pp. 189–199, 2015.
   Web of Science ®Google Scholar
• S. M. Abd-Elazim, and E. S. Ali, “Load frequency controller design via BAT algorithm for nonlinear interconnected power system,” Int. J. Electr. Power Energy Syst., vol. 77, pp. 166–177, 2016.
   Web of Science ®Google Scholar
• S. Dhillon, J. Lather, and S. Marwaha, “Multi objective load frequency control using hybrid bacterial foraging and particle swarm optimized PI controller,” Int. J. Electr. Power Energy Syst., vol. 79, pp. 196–209, 2016.
   Web of Science ®Google Scholar
• L. C. Jiao and L. Wang, “A novel genetic algorithm based on immunity", IEEE Trans Syst. Man Cybernetics A, vol. 30, no. 5, pp. 552–561, 2000.
   Web of Science ®Google Scholar
• T. Vidal, T. G. Crainic, M. Gendreau, and C. Prins, “A hybrid genetic algorithm with adaptive diversity management for a large class of vehicle routing problems with time-windows,” Comput. Oper., vol. 40, no. 1, pp. 475–489, 2013.
   Web of Science ®Google Scholar
• L. Yiu-Wing, and W. Yuping, “An orthogonal genetic algorithm with quantization for global numerical optimization,” IEEE Trans. Evol. Comput., vol. 5, no. 1, pp. 41–53, 2001.
   Web of Science ®Google Scholar
• C. Yang, Jyh-Horng, Ching-Kao, “Hybrid Taguchi based genetic algorithm for flowshop scheduling problem,” Int. J. Innov. Comput. Inform. Control, vol. 9, no. 3, Mar. 2013.
   Google Scholar
• C. Jyh-Horng, L. Tung-Kuan, and T. Jinn-Tsong, “Optimal design of digital IIR filters by using hybrid Taguchi genetic algorithm,” IEEE Trans. Ind. Electron., vol. 53, no. 3, pp. 867–879, 2006.
   Web of Science ®Google Scholar
• M. S. Phadke, Quality Engineering Using Robust Design. Lebanon, IN: Prentice Hall PTR, 1989.
   Google Scholar
• F. Creveling, Engineering Methods for Robust Product Design: using Taguchi Methods in Technology and Product Development. Lebanon, IN: Prentice Hall PTR, 1995.
   Google Scholar
• Y. Wu, Taguchi Methods for Robust Design. New York, NY: ASME, 2000.
   Google Scholar
• P. A. Stubberud, and M. E. Jackson, “A Hybrid Orthogonal Genetic Algorithm for Global Numerical optimization,” in Proceedings of the 2008 19th International Conference on Systems Engineering, 9–21 Aug. 2008, Las Vegas, NV: IEEE Computer Society, 2008, pp. 282–287.
   Google Scholar
• C. Jian, and L. Hua, “An efficient hybrid Taguchi-genetic algorithm for protein folding simulation,” Expert Syst. Appl., vol. 36, pp. 12446–12453, 2009.
   Web of Science ®Google Scholar
• C. Chien-Sheng, and L. Jium-Ming, “The hybrid Taguchi-Genetic algorithm for mobile location,” Int. J. Distributed Sensor Netw., vol. 10, no. 3, pp. 1–8, 2014.
   Google Scholar
• I. Nasiruddin and P. Kumar, “A novel approach to the matrix Riccati equation solution: An application to optimal control of interconnected power systems”, Electr. Power Components Syst., vol. 32, no. 1, pp. 33–52, Jan. 2004.
   Web of Science ®Google Scholar
• H. Kihara, T. Kageyama, T. Shimojo, and A. Izena, “Practical hydraulic turbine model,” in IEEE Power Engineering Society General Meeting, 18–22 Jun. 2006, Montreal, Quebec, Canada, 2006.
   Google Scholar
• E. Çam, “Application of fuzzy logic for load frequency control of hydro electrical power plants,” Energy Convers. Manage., vol. 48, no. 4, pp. 1281–1288, 2007.
   Web of Science ®Google Scholar
• L. C. Saikia, S. Mishra, N. Sinha, and J. Nanda, “Automatic generation control of a multi area hydrothermal system using reinforced learning neural network controller,” Int. J. Electr. Power Energy Syst., vol. 33, no. 4, pp. 1101–1108, 2011.
   Web of Science ®Google Scholar
• I. Edigo, F. Fernandez-Bernal, L. Rouco, E. Porras, and A. Saiz-Chicharro, “Modelling of thermal generating units for automatic generation control purposes,” IEEE Trans. Control Syst. Technol., vol. 12, no. 1, pp. 205–210, Jan. 2004.
   Web of Science ®Google Scholar
• P. Kumar and I. Nasiruddin, “Dynamic performance evaluation of 2-area interconnected power systems: A comparative study,” J. Inst. Eng. (India), vol. 78, pp. 199–208, 1998.
   Google Scholar
• K. Subbaramaiah, V. Mohan, and V.C. Veera Reddy, “Design of integral controller for SSSC and TCPS based AGC of hydrothermal system under deregulated environment,” Int. J. Mod. Eng. Res., vol. 2, no. 2, pp. 050–055, 2012.
   Google Scholar
• J. M. Mauricio, M. Alejandro, G.-E. Antonio, and R. José Luis Martínez, “Frequency regulation contribution through variable-speed wind energy conversion systems,” IEEE Trans. Power Syst., vol. 24, no. 1, Feb. 2009.
   Web of Science ®Google Scholar
• L. Holdsworth, N. Jenkins, and X. Wu, “Dynamic modelling of doubly fed induction generator wind turbines,” IEEE Trans. Power Syst., vol. 18, no. 2, pp. 803–809, May 2003.
   Web of Science ®Google Scholar
• W. Wong, R. J. Koessler, D. L. Dickmander, and P. Pourbeik, “Integration of large wind farms into utility grids (part 2-performance issues),” IEEE Power Eng. Soc., vol. 3, pp. 1525–1528, Jul. 2003.
   Google Scholar
• M. O’Malley, and A. Mullane, “The inertial-response of induction machine based wind-turbines,” IEEE Trans. Power Syst., vol. 20, no. 3, pp. 1496–1503, Aug. 2005.
   Web of Science ®Google Scholar