Optimal Power Flow Using Differential Search Algorithm

REFERENCES

• Squires, R.B., “Economic dispatch of generation directly from power system voltages and admittances,” IEEE Trans. Power App. Syst., Vol. 79, No. 3, pp. 1235–1245, 1961.
   Google Scholar
• Carpentier, J., “Contribution à l’étude du Dispatching Economique” (“Contribution to the study of economic dispatch”), Bull. Soc. Francaise Elect., Vol. 3, pp. 431–447, 1962.
   Google Scholar
• Niknam, T., Narimani, M.R., Jabbari, M., and Malekpour, A.R., “A modified shuffle frog leaping algorithm for multi-objective optimal power flow,” Energy, Vol. 36, No. 11, pp. 6420–6432, 2011.
   Web of Science ®Google Scholar
• Huneault, M., and Galiana, F.D., “A survey of the optimal power flow literature,” IEEE Trans. Power Syst., Vol. 6, No. 2, pp. 762–770, 1991.
   Web of Science ®Google Scholar
• Frank, S., Steponavice, I., and Rebennack, S., “Optimal power flow: A bibliographic survey I, formulations and deterministic methods,” Energy Syst., Vol. 3, No. 3, pp. 221–258, 2012.
   Google Scholar
• AlRashidi, M.R., and El-Hawary, M.E., “Applications of computational intelligence techniques for solving the revived optimal power flow problem,” Elect. Power Syst. Res., Vol. 79, No. 4, pp. 694–702, 2009.
   Web of Science ®Google Scholar
• Frank, S., Steponavice, I., and Rebennack, S., “Optimal power flow: A bibliographic survey II, non-deterministic and hybrid methods,” Energy Syst., Vol. 3, No. 3, pp. 259–289, 2012.
   Google Scholar
• Nasr Azadani, E., Hosseinian, S.H., Hasanpor Divshali, P., and Vahidi, B., “Stability constrained optimal power flow in deregulated power systems,” Elect. Power Compon. Syst., Vol. 39, No. 8, pp. 713–732, 2011.
   Web of Science ®Google Scholar
• Roy, P.K., and Mandal, D., “Quasi-oppositional biogeography-based optimization for multi-objective optimal power flow,” Elect. Power Compon. Syst., Vol. 40, No. 2, pp. 236–256, 2011.
   Web of Science ®Google Scholar
• Roy, P.K., Mandal, B., and Bhattacharya, K., “Gravitational search algorithm based optimal reactive power dispatch for voltage stability enhancement,” Elect. Power Compon. Syst., Vol. 40, pp. 956–976, 2012.
   Web of Science ®Google Scholar
• Arul, R., Ravi, G., and Velusami, S., “Solving optimal power flow problems using chaotic self-adaptive differential harmony search algorithm, Elect. Power Compon. Syst., Vol. 41, No. 8, pp. 782–805, 2013.
   Web of Science ®Google Scholar
• Civicioglu, P., “Transforming geocentric Cartesian coordinates to geodetic coordinates by using differential search algorithm,” Comput. Geosci., Vol. 46, pp. 229–247, 2012.
   Web of Science ®Google Scholar
• Vito, T., Elio, T., and Kevin, M.P., “Swarm cognition: An interdisciplinary approach to the study of self-organising biological collectives,” Swarm Intell., Vol. 5, pp. 3–18, 2011.
   Web of Science ®Google Scholar
• Abido, M.A., “Optimal power flow using particle swarm optimization,” Int. J. Elect. Power Energy Syst., Vol. 24, No. 7, pp. 563–571, 2002.
   Web of Science ®Google Scholar
• Lee, K., Park, Y., and Ortiz, J., “A united approach to optimal real and reactive power dispatch,” IEEE Trans. Power Appar. Syst., Vol. 104, No. 5, pp. 1147–1153, 1985.
   Web of Science ®Google Scholar
• Abou El Ela, A.A., and Abido, M.A., “Optimal power flow using differential evolution algorithm,” Elect. Power Syst. Res., Vol. 80, No. 7, pp. 878–885, 2010.
   Web of Science ®Google Scholar
• Belhadj, C.A., and Abido, M.A., “An optimized fast voltage stability indicator,” Electric Power International Conference on Engineering (PowerTech), pp. 79–83, Budapest, . August 29–September 2 1999.
   Google Scholar
• Kessel, P., and Glavitsch, H., “Estimating the voltage stability of a power system,” IEEE Trans. Power Delivery, Vol. 1, No. 3, pp. 346–354, 1986.
   Web of Science ®Google Scholar
• Bhattacharya, A., and Chattopadhyay, P.K., “Application of biogeography-based optimisation to solve different optimal power flow problems,” IET Generat. Transm. Distribut., Vol. 5, No. 1, pp. 70–80, 2011.
   Web of Science ®Google Scholar
• Pinar, A., Reichert, A., and Lesieutre, B., “Computing criticality of lines in power systems,” IEEE International Symposium on Circuits and Systems (ISCAS 2007), pp. 65–68, New Orleans, USA, 27–30 May 2007.
   Google Scholar
• Subramani, C., Dash, S.S., Jagdeeshkumar, M., and Bhaskar, M.A., “Stability index based voltage collapse prediction and contingency analysis,” J. Elect. Eng. Technol., Vol. 4, No. 4, pp. 438–442, 2009.
   Web of Science ®Google Scholar
• Yuryevich, J., and Wong, K.P., “Evolutionary programming based optimal power flow algorithm,” IEEE Trans. Power Syst., Vol. 14, No. 4, pp. 1245–1250, 1999.
   Web of Science ®Google Scholar
• Duman, S., Güvenç, U., Sönmez, Y., and Yörükeren, N., “Optimal power flow using gravitational search algorithm,” Energy Conv. Manag., Vol. 59, pp. 86–95, 2012.
   Web of Science ®Google Scholar
• Roa-Sepulveda, C.A., and Pavez-Lazo, B.J., “A solution to the optimal power flow using simulated annealing,” Int. J. Elect. Power Energy Syst., Vol. 25, No. 1, pp. 47–57, 2003.
   Web of Science ®Google Scholar
• Attia, A.F., Al-Turki, Y.A., and Abusorrah, A.M., “Optimal power flow using adapted genetic algorithm with adjusting population size,” Elect. Power Compon. Syst., Vol. 40, No. 11, pp. 1285–1299, 2012.
   Web of Science ®Google Scholar
• Vaisakh, K., and Srinivas, L.R., “Genetic evolving ant direction HDE for OPF with nonsmooth cost functions and statistical analysis,” Expert Syst. Appl., Vol. 38, pp. 2046–2062, 2011.
   Web of Science ®Google Scholar
• Vaisakh, K., and Srinivas, L.R., “Evolving ant direction differential evolution for OPF with non-smooth cost functions,” Eng. Appl. Art. Intell., Vol. 24, pp. 426–436, 2011.
   Web of Science ®Google Scholar
• Liang, R.H., Tsai, S.R., Chen, Y.T., and Tseng, W.-T., “Optimal power flow by a fuzzy based hybrid particle swarm optimization approach,” Elect. Power Syst. Res., Vol. 81, No. 7, pp. 1466–1474, 2011.
   Web of Science ®Google Scholar
• Lai, L.L., Ma, J.T., Yokoyama, R., and Zhao, M., “Improved genetic algorithms for optimal power flow under both normal and contingent operation states,” Int. J. Elect. Power Energy Syst., Vol. 19, No. 5, pp. 287–292, 1997.
   Web of Science ®Google Scholar
• Ghanizadeh, A.J., Mokhtari, G., Abedi, M., and Gharehpetian, G.B., “Optimal power flow based on imperialist competitive algorithm,” Int. Rev. Elect. Eng. Part B, Vol. 6, No. 4, pp. 1847–1852, June 2011.
   Google Scholar
• Bakirtzis, A.G., Biskas, P.N., Zoumas, C.E., and Petridis, V., “Optimal power flow by enhanced genetic algorithm,” IEEE Trans. Power Syst., Vol. 17, No. 2, pp. 229–236, 2002.
   Web of Science ®Google Scholar
• Abido, M.A., “Optimal power flow using tabu search algorithm,” Elect. Power Compon. Syst., Vol. 30, pp. 469–483, 2002.
   Web of Science ®Google Scholar
• Sayah, S., and Zehar, K., “Modified differential evolution algorithm for optimal power flow with non-smooth cost functions,” Energy Convers. Manag., Vol. 49, No. 11, pp. 3036–3042, 2008.
   Web of Science ®Google Scholar
• Ongsakul, W., and Tantimaporn, T., “Optimal power flow by improved evolutionary programming,” Elect. Power Compon. Syst., Vol. 34, No. 1, pp. 79–95, 2006.
   Web of Science ®Google Scholar
• Paranjothi, S.R., and Anburaja, K., “Optimal power flow using refined genetic algorithm,” Elect. Power Compon. Syst., Vol. 30, pp. 1055–1063, 2002.
   Web of Science ®Google Scholar
• Sinsuphan, N., Leeton, U., and Kulworawanichpong, T., “Optimal power flow solution using improved harmony search method,” Appl. Soft Comput., Vol. 13, No. 5, pp. 2364–2374, 2013.
   Web of Science ®Google Scholar
• MATLAB, “Matpower MATLAB toolbox,” available at: http://www.pserc.cornell.edu/matpower/matpower.html
   Google Scholar