Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

Non-smooth/non-convex economic dispatch by a novel hybrid differential evolution algorithm

Non-smooth/non-convex economic dispatch by a novel hybrid differential evolution algorithm

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Generation, Transmission & Distribution — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This paper presents a novel stochastic optimisation approach to determining the feasible optimal solution of the economic dispatch (ED) problem considering various generator constraints. Many practical constraints of generators, such as ramp rate limits, prohibited operating zones and the valve point effect, are considered. These constraints make the ED problem a non-smooth/non-convex minimisation problem with constraints. The proposed optimisation algorithm is called self-tuning hybrid differential evolution (self-tuning HDE). The self-tuning HDE utilises the concept of the 1/5 success rule of evolution strategies (ESs) in the original HDE to accelerate the search for the global optimum. Three test power systems, including 3-, 13- and 40-unit power systems, are applied to compare the performance of the proposed algorithm with genetic algorithms, the differential evolution algorithm and the HDE algorithm. Numerical results indicate that the entire performance of the proposed self-tuning HDE algorithm outperforms the other three algorithms.

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
      • Z. Michalewicz . (1996) Genetic algorithms + data structures = evolution programs.
    5. 5)
      • Price, K.V.: `Differential evolution vs. functions of the 2nd ICEC', IEEE Conf. Evolutionary Computation, 1997, Indianapolis, USA, p. 153–157.
    6. 6)
      • A. Turgeno . Optimal scheduling of thermal generating units. IEEE Trans. Autom. Control , 6 , 1000 - 1005
    7. 7)
    8. 8)
      • K.P. Wong , C.C. Fung . Simulated annealing based economic dispatch algorithm. IEE Proc., Gener. Transm. Distrib. , 6 , 509 - 515
    9. 9)
    10. 10)
      • Sewtohul, L.G., Ah King, R.T.F., Rughooputh, C.S.: `Genetic algorithms for economic dispatch with valve point effect', IEEE Int. Conf. Networking, Sensing and Control, March 2004, Taipei, Taiwan, Vol. 2, p. 1358–1363.
    11. 11)
    12. 12)
      • T. Back , H.P. Schwefel . An overview of evolutionary algorithms for parameter optimisation. Evolution. Comput. , 1 , 1 - 23
    13. 13)
    14. 14)
    15. 15)
      • J.P. Chiou , F.S. Wang . Hybrid method of evolutionary algorithms for static and dynamic optimisation problems with application to a fed-batch fermentation process. J. Comput. Chem. Eng. , 1277 - 1291
    16. 16)
      • Lin, Y.C., Hwang, K.S., Wang, F.S.: `Plant scheduling and planning using mixed-integer hybrid differential evolution with multiplier updating', Proc. Congress on Evolutionary Computation, July 2000, San Diego, CA, 1, p. 593–600.
    17. 17)
      • Back, T., Hoffmeister, F., Schwefel, H.-P.: `A survey of evolution strategies', Proc. Int. Conf. Genetic Algorithms, July 1991, San Diego, CA, p. 2–9.
    18. 18)
      • J.Y. Fan , J.D. McDonald . A practical approach to real time economic dispatch considering unit's prohibited operating zones. IEEE Trans. Power Syst. , 4 , 1737 - 1743
    19. 19)
    20. 20)
      • Ld.S. Coelho , V.C. Mariani . Correction to “combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve-point effect. IEEE Trans. Power Syst. , 3 , 1465 - 1465
    21. 21)
      • A.J. Wood , B.F. Wollenberg . (1996) Power generation, operation and control.
    22. 22)
      • Z.L. Gaing . Closure to discussion of particle swarm optimisation to solving the economic dispatch considering the generator constraints. IEEE Trans. Power Syst. , 4 , 2121 - 2123
    23. 23)
      • J.P. Chiou , F.S. Wang . Estimation of monod model parameters by hybrid differential evolution. J. Bioprocess Biosyst. Eng. , 109 - 113
    24. 24)
    25. 25)
      • Su, C.T., Chiou, G.J.: `A Hopfield network approach to economic dispatch with prohibited operating zones', IEEE Proc. Int. Conf. Energy Management and Power Delivery, Singapore, November 1995, p. 382–387.
    26. 26)
      • Storn, R., Price, K.: `Minimizing the real functions of the ICEC ‘96 contest by differential evolution', IEEE Proc. Int. Conf. Evolutionary Computation, May 1996, Nagoya, Japan, p. 842–844.
    27. 27)
    28. 28)
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd_20070183
Loading

Related content

content/journals/10.1049/iet-gtd_20070183
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address