GA and PSO culled hybrid technique for economic dispatch problem with prohibited operating zones

Chen, P.H., Chang, H.C., 1995. Large scale economic dispatch by genetic algorithm. IEEE Trans. on Power Syst., 10(4):1919–1926. [doi:10.1109/59.476058]

Fung, C.C., Chow, S.Y., Wong, K.P., 2000. Solving the Economic Dispatch Problem with an Integrated Parallel Genetic Algorithm. Proc. Int. Conf. on Power System Technology, p.1257–1262.

Gaing, Z.L., 2003. Particle swarm optimization to solving the economic dispatch considering the generator constraints. IEEE Trans. on Power Syst., 18(3):1187–1195. [doi:10.1109/TPWRS.2003.814889]

Huang, C.M., Huang, C.J., Wang, M.L., 2005. A particle swarm optimization to identify the ARMAX model for short term load forecasting. IEEE Trans. on Power Syst., 20(2):1126–1133. [doi:10.1109/TPWRS.2005.846106]

Kennedy, J., Eberhart, R., 1995. Particle Swarm Optimization. Proc. IEEE Int. Conf. on Neural Networks, 4:1942–1948. [doi:10.1109/ICNN.1995.488968]

Lee, F.N., Breipohl, A.M., 1993. Reserve constrained economic dispatch with prohibited operating zones. IEEE Trans. on Power Syst., 8(1):246–254. [doi:10.1109/59.221233]

Mantawy, A.H., Abdel-Magid, Y.L., Selim, S.Z., 1999. Integrating GA, TS and SA for the unit commitment problem. IEEE Trans. on Power Syst., 14(3):829–836. [doi:10.1109/59.780892]

Michalewicz, Z., 1994. Genetic Algorithm + Data Structure = Evolution Programs. Springer-Verlag, New York.

Sheble, G.B., Brittig, K., 1995. Refined genetic algorithm—economic dispatch example. IEEE Trans. on Power Syst., 10(1):117–123. [doi:10.1109/59.373934]

Song, Y.H., Xuan, Q.Y., 1998. Combined heat and power economic dispatch using genetic algorithm based penalty function method. Int. J. Electric Machines & Power Syst., 26:363–371.

Victoire, T.A.A., Jeyakumar, A.E., 2005. Reserve constrained dynamic dispatch of units with valve-point effects. IEEE Trans. on Power Syst., 20(3):1273–1282. [doi:10.1109/TPWRS.2005.851958]

Walters, D.C., Sheble, G.B., 1993. Genetic algorithm solution of economic dispatch with valve point loading. IEEE Trans. on Power Syst., 8(3):1325–1332. [doi:10.1109/59.260861]

Wong, K.P., Wong, Y.W., 1994. Genetic and genetic/simulated annealing approaches to economic dispatch. IEE Proc. Gener., Trans. & Distrib., 141(5):507–513. [doi:10.1049/ip-gtd:19941354]

Wood, A.J., Wallenberg, B.F., 1984. Power Generation, Operation and Control. John Wiley and Sons.

Yalcinoz, T., Short, M.J., 1998. Neural network approach for solving economic dispatch with valve point loading. IEEE Trans. on Power Syst., 13(2):307–313. [doi:10.1109/59.667341]

Yang, H.T., Yang, P.C., Huang, C.L., 1996. Evolutionary programming based economic dispatch for units with non-smooth fuel cost functions. IEEE Trans. on Power Syst., 11(1):112–117. [doi:10.1109/59.485992]

Yoshida, H., Kawata, K., Fukuyama, Y., Takayama, S., Nakanishi, Y., 2000. A particle swarm optimization for reactive power and voltage control considering voltage security assessment. IEEE Trans. on Power Syst., 15(4):1232–1239. [doi:10.1109/59.898095]

Zhao, B., Guo, C.X., Cao, Y.J., 2005. A multiagent-based particle swarm optimization approach for optimal reactive power dispatch. IEEE Trans. on Power Syst., 20(2):1070–1078. [doi:10.1109/TPWRS.2005.846064]