Skip to main content
SpringerLink
Log in

Optimal power flow using differential evolution algorithm

  • Original Paper
  • Published:
Electrical Engineering Aims and scope Submit manuscript

Abstract

This paper presents an efficient and reliable evolutionary-based approach to solve the optimal power flow (OPF) problem. The proposed approach employs differential evolution algorithm for optimal settings of OPF problem control variables. The proposed approach is examined and tested on the standard IEEE 30-bus test system with different objectives that reflect fuel cost minimization, voltage profile improvement, and voltage stability enhancement. The proposed approach results are compared with the results reported in the literature. The results show the effectiveness and robustness of the proposed approach.

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

  1. Alsac O, Stott B (1974) Optimal load flow with steady state security. IEEE Trans Power Apparatus Syst 93: 745–751

    Article  Google Scholar 

  2. Dommel H, Tinny W (1968) Optimal power flow solution. IEEE Trans Power Apparatus Syst PSA-87(10): 1866–1876

    Article  Google Scholar 

  3. Shoults R, Sun D (1982) Optimal power flow based on P–Q decomposition. IEEE Trans Power Apparatus Syst PSA-101(2): 397–405

    Article  Google Scholar 

  4. Happ HH (1977) Optimal power dispatch: a comprehensive survey. IEEE Trans Power Apparatus Syst PSA-96: 841–854

    Article  Google Scholar 

  5. Mamandur KRC (1981) Optimal control of reactive power flow for improvements in voltage profiles and for real power loss minimization. IEEE Trans Power Apparatus Syst PSA-100(7): 3185–3193

    Article  Google Scholar 

  6. Habiabollahzadeh H, Luo GX, Semlyen A (1989) Hydrothermal optimal power flow based on a combined linear and non-linear programming methodology. IEEE Trans Power Apparatus Syst PWRS-4(2): 530–537

    Google Scholar 

  7. Burchett RC, Happ HH, Vierath DR (1984) Quadratically convergent optimal power flow. IEEE Trans Power Apparatus Syst PAS-103: 3267–3276

    Article  Google Scholar 

  8. Aoki K, Nishikori A, Yokoyama RT (1987) Constrained load flow using recursive quadratic programming. IEEE Trans Power Apparatus Syst PAS-2(1): 8–16

    Google Scholar 

  9. Reid GF, Hasdorf L (1973) Economic dispatch using quadratic programming. IEEE Trans Power Apparatus Syst PAS-92: 2015–2023

    Article  Google Scholar 

  10. Stadlin W, Fletcher D (1982) Voltage verus reactive current model for dispatch and control. IEEE Trans Power Apparatus Syst PAS-101(10): 3751–3758

    Article  Google Scholar 

  11. Mota-Palomino R (1986) Sparse reactive power scheduling by a penalty-function linear programming technique. IEEE Trans Power Apparatus Syst PAS-1(3): 31–39

    Google Scholar 

  12. Abou El-Ela AA, Abido MA (1992) Optimal operation strategy for reactive power control. Modeling, simulation and control, Part A, vol 41(3). AMSE Press, New York, pp 19–40

  13. Sun DI, Ashley B, Brewer B, Hughes A, Tinney WF (1984) Optimal power flow by newton approach. IEEE Trans Power Apparatus Syst PAS-103(10): 2864–2880

    Article  Google Scholar 

  14. Santos A (1995) Optimal power flow solution by Newton’s method applied to AN augmented lagrangian function. IEE Proc Gener Transm Distrib 142(1): 33–36

    Article  Google Scholar 

  15. Rahli M (1999) Optimal power flow using sequential unconstrained minimization technique (SUMT) method under power transmission losses minimization. Electr Power Syst Res 52: 61–64

    Article  Google Scholar 

  16. Momoh JA (1999) Improved interior point method for OPF problems. IEEE Trans Power Apparatus Syst 14(3): 1114–1120

    Google Scholar 

  17. Momoh JA, El-Hawary ME, Adapa R (1999) A review of selected optimal power flow literature to 1993. Part I: Non-linear and quadratic programming approaches. IEEE Trans Power Syst 14(1): 96–104

    Article  Google Scholar 

  18. Momoh JA, El-Hawary ME, Adapa R (1999) A review of selected optimal power flow literature. Part II: Newton, linear programming and interior point methods. IEEE Trans Power Syst 14(1): 105–111

    Article  Google Scholar 

  19. Lai LL, MA JT, Yokohoma R, Zhao M (1997) Improved genetic algorithm for optimal power flow under both normal and contingent operation states. Electr Power Energy Syst 19: 287–291

    Article  Google Scholar 

  20. Osman MS, Abo-Sinna MA (2003) A solution to the optimal power flow using genetic algorithm. Elsevier, Amsterdam

    Google Scholar 

  21. Miranda V, Srinivasan D, Proenca LM (1998) Evolutionary computation in power systems. Electr Power Energy Syst 20: 89–98

    Article  Google Scholar 

  22. Abido MA (2002) Optimal power flow using tabu search algorithm. Electr Power Compon Syst 30(5): 469–483

    Article  Google Scholar 

  23. Abido MA (2002) Optimal power flow using particle swarm optimization. Int J Electr Power Energy Syst 24(7): 563–571

    Article  Google Scholar 

  24. Feoktistov V (2006) Differential evolution in search of solutions. Springer, Berlin

    MATH  Google Scholar 

  25. Das S, Abraham A, Konar A (2008) Particle swarm optimization and differential evolution algorithms: technical analysis, applications and hybridization perspectives. Appl Soft Comput J 7(3):1019–1026. Availlable at: www.softcomputing.net/aciis.pdf

  26. Karaboga D, Okdem S (2004) A simple and global optimization algorithm for engineering problems: differential evolution algorithm. Turk J Electr Eng 12(1): 53–60

    Google Scholar 

  27. Storn R (1997) Differential evolution, a simple and efficient heuristic strategy for global optimization over continuous spaces. J Glob Optim 1: 341–359

    Article  MathSciNet  Google Scholar 

  28. Thomas P, Vernon D (1997) Image registration by differential evolution. In: Proceedings of the Irish machine vision and image processing conference, pp 221–225

  29. Storn R (1996) Differential evolution design of an IIR-filter with requirements of magnitude and group delay. In: Proceedings of the IEEE conference on evolutionary computation, pp 268-273

  30. Storn R (1999) System design by constraint adaptation and differential evolution. IEEE Trans Evol Comput 3(1): 22–34

    Article  Google Scholar 

  31. Liu J, Lampinen J (2002) A fuzzy adaptive differential evolution algorithm. Lappeenranta University of Technology, TENCON ‘02 Proceedings 2002 IEEE Region 10 conference on computers, communications, control and power engineering, vol 1, pp 606–611

  32. Lee K, Park Y, Ortiz J (1985) A united approach to optimal real and reactive power dispatch. IEEE Trans Power Apparatus Syst 104(5): 1147–1153

    Article  Google Scholar 

  33. Abido MA (2006) Multiobjective optimal VAR dispatch using strength pareto evolutionary algorithm. In: IEEE Congress on Evolutionary Computation Sheraton Vancouver Wall Centre Hotel, Vancouver, BC, Canada, 16–21 July

  34. Dieu VN, Ongsakul W (2006) Enhanced augmented Lagrange Hopfield network for economic dispatch with piecewise quadratic cost functions. In: IEE proceedings on generation. Transmission and distribution, April

Download references

Author information

Authors and Affiliations

  1. Electrical Engineering Department, Faculty of Engineering, Menoufiya University, Shibin al Kawm, Egypt

    A. A. Abou El Ela & S. R. Spea

  2. Electrical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    M. A. Abido

Authors
  1. A. A. Abou El Ela
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. A. Abido
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. R. Spea
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. A. Abou El Ela.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Abou El Ela, A.A., Abido, M.A. & Spea, S.R. Optimal power flow using differential evolution algorithm. Electr Eng 91, 69–78 (2009). https://doi.org/10.1007/s00202-009-0116-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00202-009-0116-z

Keywords

Search

Navigation