Skip to main content

Optimal Power Flow Dispatch Using Trust Region Based Multiplier Method

  • Conference paper
  • First Online:
Advanced Intelligent Systems for Sustainable Development (AI2SD’2019) (AI2SD 2019)

Abstract

This work presents the computation technique called Trust-Region Based Multiplier Method (TRMM) to solve the practical Optimal Power Flow Dispatch (OPFD) problem. The proposed approach is tested and examined using the standard IEEE 30-bus test system. The several objectives functions such as fuel cost minimization, power losses minimization and voltage profile improvement are considered. The simulation results prove that the resolution approach gives better-quality solution in terms of convergence and accuracy, when compared to other methods to solve the OPFD problem.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Carpentier, J.: Contribution to the economic dispatch problem. Bulletin de la Societe Francoise des Electriciens 3(8), 431–447 (1962)

    Google Scholar 

  2. Dommel, H.W., Tinney, W.F.: Optimal power flow solutions. IEEE Trans. Power Appar. Syst. 10, 1866–1876 (1968)

    Article  Google Scholar 

  3. Mohamed, A.-A.A., Mohamed, Y.S., El-Gaafary, A.A.M., Hemeida, A.M.: Optimal power flow using moth swarm algorithm. Electric Power Syst. Res, 142, 190–206 (2017)

    Google Scholar 

  4. Habibollahzadeh, H., Luo, G.-X., Semlyen, A.: Hydrothermal optimal power flow based on a combined linear and nonlinear programming methodology. Inst. Electr. Electron. Eng. (1989)

    Google Scholar 

  5. Reid, G.F., Hasdorff, L.: Economic dispatch using quadratic programming. IEEE Trans. Power Appar. Syst. 6, 2015–2023 (1973)

    Article  Google Scholar 

  6. Momoh, J.A., El-Hawary, M.E., Adapa, R.: A review of selected optimal power flow literature to 1993. II. Newton, linear programming and interior point methods. IEEE Trans. Power Syst. 14(1), 105–111 (1999)

    Google Scholar 

  7. Singh, R.P., Mukherjee, V., Ghoshal, S.P.: Particle swarm optimization with an aging leader and challengers algorithm for the solution of optimal power flow problem. Appl. Soft Comput. 40, 161–177 (2016)

    Google Scholar 

  8. Frank, S., Steponavice, I., Rebennack, S.: Optimal power flow: a bibliographic survey I. Energy Syst. 3(3), 221–258 (2012)

    Article  Google Scholar 

  9. Bertsekas, D.P.: Nonlinear programming. Athena scientific Belmont (1999)

    Google Scholar 

  10. Dennis Jr, J.E., El-Alem, M., Williamson, K.: A trust-region approach to nonlinear systems of equalities and inequalities. SIAM J. Optim. 9(2), 291–315 (1999)

    Google Scholar 

  11. Abaali, H., Talbi, E., Skouri, R.: Comparison of newton Raphson and gauss seidel methods for power flow analysis. World Acad. Sci. Eng. Technol. Int. J. Energy Power Eng. 12(9), 627–633 (2018)

    Google Scholar 

  12. Yokoyama, R., Bae, S.H., Morita, T., Sasaki, H.: Multiobjective optimal generation dispatch based on probability security criteria. IEEE Trans. Power Syst. 3(1), 317–324 (1988)

    Article  Google Scholar 

  13. Abou El Ela, A.A., Abido, M.A., Spea, S.R.: Optimal power flow using differential evolution algorithm. Electr. Power Syst. Res. 80(7), 878–885 (2010)

    Article  Google Scholar 

  14. Venkataraman, P.: Applied Optimization with MATLAB Programming. Wiley (2009)

    Google Scholar 

  15. Wang, H., Murillo-Sanchez, C.E., Zimmerman, R.D., Thomas, R.J.: On computational issues of market-based optimal power flow. IEEE Trans. Power Syst. 22(3), 1185–1193 (2007)

    Article  Google Scholar 

  16. Mor, J.J., Sorensen, D.C.: Computing a trust region step. SIAM J. Sci. Stat. Comput. 4(3), 553–572 (1983)

    Article  MathSciNet  Google Scholar 

  17. Wright, S., Nocedal, J.: Numerical Optimization. Springer Sci. 35(67–68), 7 (1999)

    Google Scholar 

  18. Steihaug, T.: The conjugate gradient method and trust regions in large scale optimization. SIAM J. Numer. Anal. 20(3), 626–637 (1983)

    Article  MathSciNet  Google Scholar 

  19. Duman, S., Gven, U., Snmez, Y., Yrkeren, N.: Optimal power flow using gravitational search algorithm. Energy Convers. Manag. 59, 86–95 (2012)

    Article  Google Scholar 

  20. Sayah, S., Zehar, K.: Modified differential evolution algorithm for optimal power flow with non-smooth cost functions. Energy Convers. Manag. 49(11), 3036–3042 (2008)

    Article  Google Scholar 

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

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to El Hachmi Talbi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Talbi, E.H., Abaali, L., Skouri, R. (2020). Optimal Power Flow Dispatch Using Trust Region Based Multiplier Method. In: Ezziyyani, M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2019). AI2SD 2019. Lecture Notes in Electrical Engineering, vol 624. Springer, Cham. https://doi.org/10.1007/978-3-030-36475-5_18

Download citation

Publish with us

Policies and ethics