Application of Epsilon Variable-Multi Objective Genetic Algorithm for Multi-Objective Optimal Power Flow with TCSC
Subject Areas : electrical and computer engineeringAbstract :
This paper ε-multi objective genetic algorithm variable (εV-MOGA) to optimize cost of generation, emission and active power transmission loss of flexible ac transmission systems (FACTS) device-equipped power systems. In the proposed approach, optimal power flow problem is formulated as a multi-objective optimization problem. FACTS devices considered include thyristor controlled series capacitor (TCSC). The proposed approach has been examined and tested on the modified IEEE 57-bus test system. The results obtained from the proposed approach have been compared with those obtained from nondominated sorting genetic algorithm-II, multi-objective differential evolution.
References:
[1] J. A. Momoh, M. E. El - Hawary, and R. Adapa, "A review of selected optimal power flow literature to 1993, part I: nonlinear and quadratic programming approach," IEEE Trans. Power Syst., vol. 14, no. 1, pp. 96-104, Feb. 1999.
[2] J. A. Momoh, M. E. El - Hawary, and R. Adapa, "A review of selected optimal power flow literature to 1993, part II: newton, linear programming and interior point methods," IEEE Trans. Power Syst., vol. 14, no. 1, pp. 104-111, Feb. 1999.
[3] N. G. Hingorani and L. Gyugyi, Understanding FACTS: Concepts and Technology of Flexible AC Transmission Systems, New York: IEEE Press, 1999.
[4] W. Ongsakul and P. Bhasaputra, "Optimal power flow with FACTS devices by hybrid TS/SA approach," Electr Power Energy Syst, vol. 24, no. 1, pp. 851-857, 2002.
[5] J. H. Talaq, F. El - Hawary, and M. E. El - Hawary, "A summary of environmental/economic dispatch algorithms," IEEE Trans. Power Syst., vol. 9, no. 3, pp. 1508-1516, Aug. 1994.
[6] D. Srinivasan, C. S. Chang, and A. C. Liew, "Multiobjective generation scheduling using fuzzy optimal search technique," IEE IEE Proceedings – C: Generation, Transmission and Distribution, vol. 141, no. 3, pp. 233-242, May 1994.
[7] A. Farag, S. Al - Baiyat, and T. C. Cheng, "Economic load dispatch multiobjective optimization procedures using linear programming techniques," IEEE Trans. Power Syst., vol. 10, no. 2, pp. 731-738, May 1995.
[8] D. B. Das and C. Patvardhan, "New multi - objective stochastic search technique for economic load dispatch," IEE IEE Proceedings – C: Generation, Transmission and Distribution, vol. 145, no. 6, pp. 747-752, Nov. 1998.
[9] D. A. V. Veldhuizen and G. B. Lamont, "Multiobjective evolutionary algorithms: analyzing the state-of-the-art," Evolutionary Computation, vol. 8, no. 2, pp. 125-147, Jun. 2000.
[10] E. Zitzler, M. Laumanns, and L. Thiele, "Improving the strength pareto evolutionary algorithm, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland, Technical Report TIK - Report 103, May 2001.
[11] H. A. Abbass and R. Sarker, "The pareto differential evolution algorithm," Int J. Artif Intell Tools, vol. 11, no. 4, pp. 531-552, Dec. 2002.
[12] K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, "A fast and elitist multiobjective genetic algorithm: NSGA-II," IEEE Trans. Evol Comput., vol. 6, no. 2, pp. 182-197, Apr. 2002.
[13] B. V. Babu and B. Anbarasu, "Multi - objective differential evolution (MODE): an evolutionary algorithm for multi - objective optimization problems (MOOPs)," in Proc. of 3rd Int. Conf. on Computational Intelligence, Robotics, and Autonomous Systems, CIRAS'05, Singapore, Dec. 2005.
[14] K. V. Price, R. Storn, and J. Lampinen, Differential Evolution: A Practical Approach to Global Optimization, Berlin: Springer- Verlag, 2005.
[15] M. A. Abido, "Environmental/economic power dispatch using multiobjective evolutionary algorithm," IEEE Trans. Power Syst., vol. 18, no. 4, pp. 1529-1537, Nov. 2003.
[16] M. A. Abido, "Multi - objective evolutionary algorithms for electric power dispatch problem," IEEE Trans. Evol Comput, vol. 10, no. 3, pp. 315-329, Jun. 2006.
[17] S. Agrawal, B. K. Panigrahi, and M. K. Tiwari, "Multiobjective particle swarm algorithm with fuzzy clustering for electrical power dispatch," IEEE Trans. Evol Comput, vol. 12, no. 5, pp. 529-541, Oct. 2008.
[18] X. Hugang, C. Haozhong, and L. Haiyub, "Optimal reactive power flow incorporating static voltage stability based on multi - objective adaptive immune algorithm," Energy Convers Manage, vol. 49, no. 5, pp. 1175-1181, May 2008.
[19] T. Niknam, M. R. Narimani, M. Jabbari, and A. R. Malekpour, "A modified shuffle frog leaping algorithm for multi - objective optimal power flow," Energy, vol. 36, no. 11, pp. 6420-6432, Nov. 2011.
[20] M. Joorabian and E. Afzalan, "Optimal power flow under both normal and contingent operationconditions using the hybrid fuzzy particle swarm optimisation and Nelder - Mead algorithm (HFPSO - NM)," Applied Soft Computing, pt. C, vol. 14, pp. 623-633, Jan. 2014.
[21] D. C. Walters and G. B. Sheble, "Genetic algorithm solution of economic dispatch with valve point loading," IEEE Trans. Power Syst, vol. 8, no. 3, pp. 1325-1332, Aug. 1993.
[22] R. Yokoyama, S. H. Bae, T. Morita, and H. Sasaki, "Multiobjective optimal generation dispatch based on probability security criteria," IEEE Trans. Power Syst, vol. 3, no. 1, pp. 317-324, Feb. 1988.
[23] M. Laumanns, L. Thiele, K. Deb, and E. Zitzler, "Combining convergence and diversity in evolutionary multi-objective optimization," Evolutionary Computation, vol. 10, no. 3, pp. 263-282, Fall 2002.
[24] M. Basu, "Economic environmental dispatch using multi - objective differential evolution," Applied Soft Computing, vol. 11, no. 1, pp. 2845-2853, Mar. 2011.
[1] J. A. Momoh, M. E. El - Hawary, and R. Adapa, "A review of selected optimal power flow literature to 1993, part I: nonlinear and quadratic programming approach," IEEE Trans. Power Syst., vol. 14, no. 1, pp. 96-104, Feb. 1999.
[2] J. A. Momoh, M. E. El - Hawary, and R. Adapa, "A review of selected optimal power flow literature to 1993, part II: newton, linear programming and interior point methods," IEEE Trans. Power Syst., vol. 14, no. 1, pp. 104-111, Feb. 1999.
[3] N. G. Hingorani and L. Gyugyi, Understanding FACTS: Concepts and Technology of Flexible AC Transmission Systems, New York: IEEE Press, 1999.
[4] W. Ongsakul and P. Bhasaputra, "Optimal power flow with FACTS devices by hybrid TS/SA approach," Electr Power Energy Syst, vol. 24, no. 1, pp. 851-857, 2002.
[5] J. H. Talaq, F. El - Hawary, and M. E. El - Hawary, "A summary of environmental/economic dispatch algorithms," IEEE Trans. Power Syst., vol. 9, no. 3, pp. 1508-1516, Aug. 1994.
[6] D. Srinivasan, C. S. Chang, and A. C. Liew, "Multiobjective generation scheduling using fuzzy optimal search technique," IEE IEE Proceedings – C: Generation, Transmission and Distribution, vol. 141, no. 3, pp. 233-242, May 1994.
[7] A. Farag, S. Al - Baiyat, and T. C. Cheng, "Economic load dispatch multiobjective optimization procedures using linear programming techniques," IEEE Trans. Power Syst., vol. 10, no. 2, pp. 731-738, May 1995.
[8] D. B. Das and C. Patvardhan, "New multi - objective stochastic search technique for economic load dispatch," IEE IEE Proceedings – C: Generation, Transmission and Distribution, vol. 145, no. 6, pp. 747-752, Nov. 1998.
[9] D. A. V. Veldhuizen and G. B. Lamont, "Multiobjective evolutionary algorithms: analyzing the state-of-the-art," Evolutionary Computation, vol. 8, no. 2, pp. 125-147, Jun. 2000.
[10] E. Zitzler, M. Laumanns, and L. Thiele, "Improving the strength pareto evolutionary algorithm, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland, Technical Report TIK - Report 103, May 2001.
[11] H. A. Abbass and R. Sarker, "The pareto differential evolution algorithm," Int J. Artif Intell Tools, vol. 11, no. 4, pp. 531-552, Dec. 2002.
[12] K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, "A fast and elitist multiobjective genetic algorithm: NSGA-II," IEEE Trans. Evol Comput., vol. 6, no. 2, pp. 182-197, Apr. 2002.
[13] B. V. Babu and B. Anbarasu, "Multi - objective differential evolution (MODE): an evolutionary algorithm for multi - objective optimization problems (MOOPs)," in Proc. of 3rd Int. Conf. on Computational Intelligence, Robotics, and Autonomous Systems, CIRAS'05, Singapore, Dec. 2005.
[14] K. V. Price, R. Storn, and J. Lampinen, Differential Evolution: A Practical Approach to Global Optimization, Berlin: Springer- Verlag, 2005.
[15] M. A. Abido, "Environmental/economic power dispatch using multiobjective evolutionary algorithm," IEEE Trans. Power Syst., vol. 18, no. 4, pp. 1529-1537, Nov. 2003.
[16] M. A. Abido, "Multi - objective evolutionary algorithms for electric power dispatch problem," IEEE Trans. Evol Comput, vol. 10, no. 3, pp. 315-329, Jun. 2006.
[17] S. Agrawal, B. K. Panigrahi, and M. K. Tiwari, "Multiobjective particle swarm algorithm with fuzzy clustering for electrical power dispatch," IEEE Trans. Evol Comput, vol. 12, no. 5, pp. 529-541, Oct. 2008.
[18] X. Hugang, C. Haozhong, and L. Haiyub, "Optimal reactive power flow incorporating static voltage stability based on multi - objective adaptive immune algorithm," Energy Convers Manage, vol. 49, no. 5, pp. 1175-1181, May 2008.
[19] T. Niknam, M. R. Narimani, M. Jabbari, and A. R. Malekpour, "A modified shuffle frog leaping algorithm for multi - objective optimal power flow," Energy, vol. 36, no. 11, pp. 6420-6432, Nov. 2011.
[20] M. Joorabian and E. Afzalan, "Optimal power flow under both normal and contingent operationconditions using the hybrid fuzzy particle swarm optimisation and Nelder - Mead algorithm (HFPSO - NM)," Applied Soft Computing, pt. C, vol. 14, pp. 623-633, Jan. 2014.
[21] D. C. Walters and G. B. Sheble, "Genetic algorithm solution of economic dispatch with valve point loading," IEEE Trans. Power Syst, vol. 8, no. 3, pp. 1325-1332, Aug. 1993.
[22] R. Yokoyama, S. H. Bae, T. Morita, and H. Sasaki, "Multiobjective optimal generation dispatch based on probability security criteria," IEEE Trans. Power Syst, vol. 3, no. 1, pp. 317-324, Feb. 1988.
[23] M. Laumanns, L. Thiele, K. Deb, and E. Zitzler, "Combining convergence and diversity in evolutionary multi-objective optimization," Evolutionary Computation, vol. 10, no. 3, pp. 263-282, Fall 2002.
[24] M. Basu, "Economic environmental dispatch using multi - objective differential evolution," Applied Soft Computing, vol. 11, no. 1, pp. 2845-2853, Mar. 2011.