Short-term hydrothermal scheduling (STHTS) is a non-linear and complex optimization problem with a set of operational hydraulic and thermal constraints. Earlier, this problem has been addressed by several classical techniques; however, due to limitations such as non-linearity and non-convexity in cost curves, artificial intelligence tools based techniques are being used to solve the STHTS problem. In this paper an improved chaotic hybrid differential evolution (ICHDE) algorithm is proposed to find an optimal solution to this problem taking into account practical constraints. A self-adjusted parameter setting is obtained in differential evolution (DE) with the application of chaos theory, and a chaotic hybridized local search mechanism is embedded in DE to effectively prevent it from premature convergence. Furthermore, heuristic constraint handling techniques without any penalty factor setting are adopted to handle the complex hydraulic and thermal constraints. The superiority and effectiveness of the developed methodology are evaluated by its application in two illustrated hydrothermal test systems taken from the literature. The transmission line losses, prohibited discharge zones of hydel plants, and ramp rate limits of thermal plants are also taken into account. The simulation results reveal that the proposed technique is competent to produce an encouraging solution as compared with other recently established evolutionary approaches.
Amjady, N., Soleymanpour, H.R., 2010. Daily hydrothermal generation scheduling by a new modified adaptive particle swarm optimization technique. Electr. Power Syst. Res., 80(6): 723-732. []
https://doi.org/10.1016/j.epsr.2009.11.004
2
Basu, M., 2014. Improved differential evolution for shortterm hydrothermal scheduling. Int. J. Electr. Power Energy Syst., 58: 91-100. []
https://doi.org/10.1016/j.ijepes.2013.12.016
3
Bhattacharjee, K., Bhattacharya, A., Halder Nee Dey, S., 2014. Oppositional real coded chemical reaction based optimization to solve short-term hydrothermal scheduling problems. Int. J. Electr. Power Energy Syst., 63: 145-157. []
https://doi.org/10.1016/j.ijepes.2014.05.065
4
Caponetto, R., Fortuna, L., Fazzino, S., , 2003. Chaotic sequences to improve the performance of evolutionary algorithms. IEEE Trans. Evol. Comput., 7(3): 289-304. []
https://doi.org/10.1109/TEVC.2003.810069
5
Chang, G.W., Aganagic, M., Waight, J.G., ., 2001. Experiences with mixed integer linear programming based approaches on short-term hydro scheduling. IEEE Trans. Power Syst., 16(4): 743-749. []
https://doi.org/10.1109/59.962421
6
Chang, S.C., Chen, C.H., Fong, I.K., , 1990. Hydroelectric generation scheduling with an effective differential dynamic programming algorithm. IEEE Trans. Power Syst., 5(3): 737-743. []
https://doi.org/10.1109/59.65900
7
Coelho, L.D.S., Lee, C.S., 2008. Solving economic load dispatch problems in power systems using chaotic and Gaussian particle swarm optimization approaches. Int. J. Electr. Power Energy Syst., 30(5): 297-307. []
https://doi.org/10.1016/j.ijepes.2007.08.001
8
Fang, N., Zhou, J., Zhang, R., , 2014. A hybrid of real coded genetic algorithm and artificial fish swarm algorithm for short-term optimal hydrothermal scheduling. Int. J. Electr. Power Energy Syst., 62: 617-629. []
https://doi.org/10.1016/j.ijepes.2014.05.017
9
Gil, E., Bustos, J., Rudnick, H., 2003. Short-term hydrothermal generation scheduling model using a genetic algorithm. IEEE Trans. Power Syst., 18(4): 1256-1264. []
https://doi.org/10.1109/TPWRS.2003.819877
10
Hota, P., Barisal, A., Chakrabarti, R., 2009. An improved PSO technique for short-term optimal hydrothermal scheduling. Electr. Power Syst. Res., 79(7): 1047-1053. []
https://doi.org/10.1016/j.epsr.2009.01.001
11
Kong, F.N., Wu, J.K., 2010. Cultural algorithm based shortterm scheduling of hydrothermal power systems. Int. Conf. on E-Product E-Service and E-Entertainment, p.1-4. []
https://doi.org/10.1109/ICEEE.2010.5661578
12
Kumar, S., Naresh, R., 2007. Efficient real coded genetic algorithm to solve the non-convex hydrothermal scheduling problem. Int. J. Electr. Power Energy Syst., 29(10): 738-747. []
https://doi.org/10.1016/j.ijepes.2007.06.001
13
Lakshminarasimman, L., Subramanian, S., 2006. Short-term scheduling of hydrothermal power system with cascaded reservoirs by using modified differential evolution. IEE Proc.-Gener. Transm. Distr., 153(6): 693-700. []
https://doi.org/10.1049/ip-gtd:20050407
14
Lakshminarasimman, L., Subramanian, S., 2008. A modified hybrid differential evolution for short-term scheduling of hydrothermal power systems with cascaded reservoirs. Energy Conv. Manag., 49(10): 2513-2521. []
https://doi.org/10.1016/j.enconman.2008.05.021
15
Li, C.A., Jap, P.J., Streiffert, D.L., 1993. Implementation of network flow programming to the hydrothermal coordination in an energy management system. IEEE Trans. Power Syst., 8(3): 1045-1053. []
https://doi.org/10.1109/59.260895
16
Liao, X., Zhou, J., Ouyang, S., , 2013. An adaptive chaotic artificial bee colony algorithm for short-term hydrothermal generation scheduling. Int. J. Electr. Power Energy Syst., 53: 34-42. []
https://doi.org/10.1016/j.ijepes.2013.04.004
17
Lu, S., Sun, C., Lu, Z., 2010. An improved quantum-behaved particle swarm optimization method for short-term combined economic emission hydrothermal scheduling. Energy Conv. Manag., 51(3): 561-571. []
https://doi.org/10.1016/j.enconman.2009.10.024
18
Lu, Y., Zhou, J., Qin, H., ., 2010. An adaptive chaotic differential evolution for the short-term hydrothermal generation scheduling problem. Energy Conv. Manag., 51(7): 1481-1490. []
https://doi.org/10.1016/j.enconman.2010.02.006
19
Mallipeddi, R., Suganthan, P.N., Pan, Q.K., ., 2011. Differential evolution algorithm with ensemble of parameters and mutation strategies. Appl. Soft Comput., 11(2): 1679-1696. []
https://doi.org/10.1016/j.asoc.2010.04.024
20
Mandal, K., Chakraborty, N., 2008. Differential evolution technique-based short-term economic generation scheduling of hydrothermal systems. Electr. Power Syst. Res., 78(11): 1972-1979. []
https://doi.org/10.1016/j.epsr.2008.04.006
Mezura-Montes, E., Velázquez-Reyes, J., Coello Coello, C.A., 2006. A comparative study of differential evolution variants for global optimization. Proc. 8th Annual Conf. on Genetic and Evolutionary Computation, p.485-492. []
https://doi.org/10.1145/1143997.1144086
23
Mohan, M., Kuppusamy, K., Khan, M.A., 1992. Optimal short-term hydrothermal scheduling using decomposition approach and linear programming method. Int. J. Electr. Power Energy Syst., 14(1): 39-44. []
https://doi.org/10.1016/0142-0615(92)90007-V
24
Pereira, M., Pinto, L., 1983. Application of decomposition techniques to the mid- and short-term scheduling of hydrothermal systems. IEEE Trans. Power Appar. Syst., PAS-102(11): 3611-3618. []
https://doi.org/10.1109/TPAS.1983.317709
25
Piekutowski, M., Litwinowicz, T., Frowd, R., 1994. Optimal short-term scheduling for a large-scale cascaded hydro system. IEEE Trans. Power Syst., 9(2): 805-811. []
https://doi.org/10.1109/59.317636
26
Redondo, N.J., Conejo, A., 1999. Short-term hydro-thermal coordination by Lagrangian relaxation: solution of the dual problem. IEEE Trans. Power Syst., 14(1): 89-95. []
https://doi.org/10.1109/59.744490
27
Roy, P.K., 2013. Teaching learning based optimization for short-term hydrothermal scheduling problem considering valve point effect and prohibited discharge constraint. Int. J. Electr. Power Energy Syst., 53: 10-19. []
https://doi.org/10.1016/j.ijepes.2013.03.024
28
Shan, L., Qiang, H., Li, J., , 2005. Chaotic optimization algorithm based on tent map. Contr. Dec., 20(2): 179-182.
29
Sinha, N., Chakrabarti, R., Chattopadhyay, P., 2003. Fast evolutionary programming techniques for short-term hydrothermal scheduling. Electr. Power Syst. Res., 66(2): 97-103. []
https://doi.org/10.1016/S0378-7796(03)00016-6
30
Storn, R., Price, K., 1997. Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces. J. Glob. Optim., 11(4): 341-359. []
https://doi.org/10.1023/A:1008202821328
31
Swain, R., Barisal, A., Hota, P., , 2011. Short-term hydrothermal scheduling using clonal selection algorithm. Int. J. Electr. Power Energy Syst., 33(3): 647-656. []
https://doi.org/10.1016/j.ijepes.2010.11.016
32
Tang, J., Luh, P.B., 1995. Hydrothermal scheduling via extended differential dynamic programming and mixed coordination. IEEE Trans. Power Syst., 10(4): 2021-2028. []
https://doi.org/10.1109/59.476071
33
Turgeon, A., 1981. Optimal short-term hydro scheduling from the principle of progressive optimality. Water Resourc. Res., 17(3): 481-486. []
https://doi.org/10.1029/WR017i003p00481
Yuan, X., Yuan, Y., 2006. Application of cultural algorithm to generation scheduling of hydrothermal systems. Energy Conv. Manag., 47(15-16): 2192-2201. []
https://doi.org/10.1016/j.enconman.2005.12.006
