Skip to main content
SpringerLink
Log in

An improved chaotic hybrid differential evolution for the short-term hydrothermal scheduling problem considering practical constraints

  • Published:
Frontiers of Information Technology & Electronic Engineering Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • 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. [doi:10.1016/j.epsr.2009.11.004]

    Article  Google Scholar 

  • Basu, M., 2014. Improved differential evolution for shortterm hydrothermal scheduling. Int. J. Electr. Power Energy Syst., 58:91–100. [doi:10.1016/j.ijepes.2013.12.016]

    Article  Google Scholar 

  • 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. [doi:10.1016/j.ijepes.2014.05.065]

    Article  Google Scholar 

  • Caponetto, R., Fortuna, L., Fazzino, S., et al., 2003. Chaotic sequences to improve the performance of evolutionary algorithms. IEEE Trans. Evol. Comput., 7(3):289–304. [doi:10.1109/TEVC.2003.810069]

    Article  Google Scholar 

  • Chang, G.W., Aganagic, M., Waight, J.G., et al., 2001. Experiences with mixed integer linear programming based approaches on short-term hydro scheduling. IEEE Trans. Power Syst., 16(4):743–749. [doi:10.1109/59.962421]

    Article  Google Scholar 

  • Chang, S.C., Chen, C.H., Fong, I.K., et al., 1990. Hydroelectric generation scheduling with an effective differential dynamic programming algorithm. IEEE Trans. Power Syst., 5(3):737–743. [doi:10.1109/59.65900]

    Article  Google Scholar 

  • 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. [doi:10.1016/j.ijepes.2007.08.001]

    Article  Google Scholar 

  • Fang, N., Zhou, J., Zhang, R., et al., 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. [doi:10.1016/j.ijepes.2014.05.017]

    Article  Google Scholar 

  • 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. [doi:10.1109/TPWRS.2003.819877]

    Article  Google Scholar 

  • 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. [doi:10.1016/j.epsr.2009.01.001]

    Article  Google Scholar 

  • 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. [doi:10.1109/ICEEE.2010.5661578]

    Google Scholar 

  • 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. [doi:10.1016/j.ijepes.2007.06.001]

    Article  Google Scholar 

  • 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. [doi:10.1049/ip-gtd:20050407]

    Article  Google Scholar 

  • 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. [doi:10.1016/j.enconman.2008.05.021]

    Article  Google Scholar 

  • 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. [doi:10.1109/59.260895]

    Article  Google Scholar 

  • Liao, X., Zhou, J., Ouyang, S., et al., 2013. An adaptive chaotic artificial bee colony algorithm for short-term hydrothermal generation scheduling. Int. J. Electr. Power Energy Syst., 53:34–42. [doi:10.1016/j.ijepes.2013.04.004]

    Article  Google Scholar 

  • 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. [doi:10.1016/j.enconman.2009.10.024]

    Article  MathSciNet  Google Scholar 

  • Lu, Y., Zhou, J., Qin, H., et al., 2010. An adaptive chaotic differential evolution for the short-term hydrothermal generation scheduling problem. Energy Conv. Manag., 51(7):1481–1490. [doi:10.1016/j.enconman.2010.02.006]

    Article  Google Scholar 

  • Mallipeddi, R., Suganthan, P.N., Pan, Q.K., et al., 2011. Differential evolution algorithm with ensemble of parameters and mutation strategies. Appl. Soft Comput., 11(2):1679–1696. [doi:10.1016/j.asoc.2010.04.024]

    Article  Google Scholar 

  • 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. [doi:10.1016/j.epsr.2008.04.006]

    Article  Google Scholar 

  • Mandal, K.K., Basu, M., Chakraborty, N., 2008. Particle swarm optimization technique based short-term hydrothermal scheduling. Appl. Soft Comput., 8(4):1392–1399. [doi:10.1016/j.asoc.2007.10.006]

    Article  Google Scholar 

  • 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. [doi:10.1145/1143997.1144086]

    Google Scholar 

  • 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. [doi:10.1016/0142-0615(92)90007-V]

    Article  Google Scholar 

  • 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. [doi:10.1109/TPAS.1983.317709]

    Article  Google Scholar 

  • 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. [doi:10.1109/59.317636]

    Article  Google Scholar 

  • 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. [doi:10.1109/59.744490]

    Article  Google Scholar 

  • 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. [doi:10.1016/j.ijepes.2013.03.024]

    Article  Google Scholar 

  • Shan, L., Qiang, H., Li, J., et al., 2005. Chaotic optimization algorithm based on tent map. Contr. Dec., 20(2):179–182.

    MATH  Google Scholar 

  • Sinha, N., Chakrabarti, R., Chattopadhyay, P., 2003. Fast evolutionary programming techniques for short-term hydrothermal scheduling. Electr. Power Syst. Res., 66(2):97–103. [doi:10.1016/S0378-7796(03)00016-6]

    Article  Google Scholar 

  • 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. [doi:10.1023/A:1008202821328]

    Article  MATH  MathSciNet  Google Scholar 

  • Swain, R., Barisal, A., Hota, P., et al., 2011. Short-term hydrothermal scheduling using clonal selection algorithm. Int. J. Electr. Power Energy Syst., 33(3):647–656. [doi:10.1016/j.ijepes.2010.11.016]

    Article  Google Scholar 

  • Tang, J., Luh, P.B., 1995. Hydrothermal scheduling via extended differential dynamic programming and mixed coordination. IEEE Trans. Power Syst., 10(4):2021–2028. [doi:10.1109/59.476071]

    Article  Google Scholar 

  • Turgeon, A., 1981. Optimal short-term hydro scheduling from the principle of progressive optimality. Water Resourc. Res., 17(3):481–486. [doi:10.1029/WR017i003p00481]

    Article  Google Scholar 

  • Wang, Y., Zhou, J., Mo, L., et al., 2012. Short-term hydrothermal generation scheduling using differential realcoded quantum-inspired evolutionary algorithm. Energy, 44(1):657–671. [doi:10.1016/j.energy.2012.05.026]

    Article  Google Scholar 

  • Wong, K., Wong, Y., 1994a. Short-term hydrothermal scheduling. I. Simulated annealing approach. IEE Proc.-Gener. Transm. Distr., 141(5):497–501. [doi:10.1049/ipgtd:19941350]

    Article  Google Scholar 

  • Wong, K., Wong, Y., 1994b. Short-term hydrothermal scheduling. II. Parallel simulated annealing approach. IEE Proc.-Gener. Transm. Distr., 141(5):502–506. [doi:10.1049/ip-gtd:19941351]

    Article  Google Scholar 

  • Yang, J.S., Chen, N., 1989. Short term hydrothermal coordination using multi-pass dynamic programming. IEEE Trans. Power Syst., 4(3):1050–1056. [doi:10.1109/59.32598]

    Article  Google Scholar 

  • Yang, P.C., Yang, H.T., Huang, C.L., 1996. Scheduling short-term hydrothermal generation using evolutionary programming techniques. IEE Proc.-Gener. Transm. Distr., 143(4):371–376. [doi:10.1049/ip-gtd:19960463]

    Article  Google Scholar 

  • Yuan, X., Yuan, Y., 2006. Application of cultural algorithm to generation scheduling of hydrothermal systems. Energy Conv. Manag., 47(15–16):2192–2201. [doi:10.1016/j.enconman.2005.12.006]

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Electrical Engineering Department, University of Engineering and Technology, Taxila, 47050, Pakistan

    Tahir Nadeem Malik, Salman Zafar & Saaqib Haroon

Authors
  1. Tahir Nadeem Malik
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Salman Zafar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Saaqib Haroon
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Salman Zafar.

Additional information

ORCID: Salman ZAFAR, http://orcid.org/0000-0002-7449-5275

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Malik, T.N., Zafar, S. & Haroon, S. An improved chaotic hybrid differential evolution for the short-term hydrothermal scheduling problem considering practical constraints. Frontiers Inf Technol Electronic Eng 16, 404–417 (2015). https://doi.org/10.1631/FITEE.1400189

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1631/FITEE.1400189

Key words

Search

Navigation