Advertisement

Comparative Analysis on Security-Constrained Optimal Power Flow Using Linear Sensitivity Factors-Based Contingency Screening

  • Darshan B. RathodEmail author
  • Rinkesh A. Jain
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 757)

Abstract

Security-Constrained Optimal Power Flow (SCOPF) is a significant tool used for analysis of power system operation and planning. This paper presents a solution of SCOPF considering critical contingencies simulated on IEEE 30-bus system. The main objective of the presented work is to minimize the total generation cost. An interior point algorithm has been used to find out a feasible and optimal solution with minimum computational time for secured power system operation. Contingency screening for SCOPF formulation has been accomplished with the help of Linear Sensitivity Factors (LSFs) obtained from the Z-bus algorithm. Comparative analysis has been carried out for the results obtained with those of other techniques published in the literature for same test cases.

Keywords

Contingency screening Interior point algorithm LSFs Optimal power flow (OPF) SCOPF 

References

  1. 1.
    Alsac, O., Stott, B.: Optimal load flow with steady-state security. IEEE Trans. Power Appar. Syst. PAS-93(3), 745–751 (1974)CrossRefGoogle Scholar
  2. 2.
    Monticelli, A., Pereira, M.V.F., Granville, S.: Security-constrained optimal power flow with post-contingency corrective rescheduling. IEEE Trans. Power Syst. 2(1), 175–180 (1987)CrossRefGoogle Scholar
  3. 3.
    Momoh, J.A., El-Hawary, M.E., Adapa, R.: A review of selected optimal power flow literature to 1993 part I: nonlinear and quadratic programming approaches. IEEE Trans. Power Syst. 14(1), 96–103 (1999)CrossRefGoogle Scholar
  4. 4.
    Monoh, J.A., Ei-Hawary, M.E., Adapa, R.: A review of selected optimal power flow literature to 1993 part II: Newton, linear programming and interior point methods. IEEE Trans. Power Syst. 14(1), 105–111 (1999)CrossRefGoogle Scholar
  5. 5.
    Capitanescu, F., Glavic, M., Ernst, D., Wehenkel, L.: Interior-point based algorithms for the solution of optimal power flow problems. Electr. Power Syst. Res. 77(5–6), 508–517 (2007)CrossRefGoogle Scholar
  6. 6.
    Gunda, J., Djokic, S., Langella, R., Testa, A.: Comparison of conventional and meta-methods for security-constrained OPF analysis. In: 2015 AEIT International Annual Conference (AEIT), pp. 58–65 (2015)Google Scholar
  7. 7.
    J. J. Grainer and W. Stevenson, Power System Analysis. McGraw-Hill, 1994Google Scholar
  8. 8.
    Wood, A.J., Wollenberg, B.F.: Power Generation, Operation, and Control. Wiley, New York (1984)Google Scholar
  9. 9.
    Christie, R: Power Systems Test Case Archive. Washington University, 2013. www.ee.Washington.edu/research/pstca
  10. 10.
    Zimmerman, R.D., Murillo-Sánchez, C.E., Thomas, R.J.: MATPOWER’s extensible optimal power flow architecture. In: 2009 IEEE Power and Energy Society General Meeting, PES’09, no. 2, pp. 1–7 (2009)Google Scholar
  11. 11.
    Ongsakul, W., Tantimaporn, T.: Optimal power flow by improved evolutionary programming. Electr. Power Compon. Syst. 34(1), 79–95 (2006)CrossRefGoogle Scholar
  12. 12.
    Thitithamrongchai, C., Eua-Arporn, B.: Security-constrained optimal power flow: a parallel self-adaptive differential evolution approach. Electr. Power Compon. Syst. 36(3), 280–298 (2008)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Shantilal Shah Engineering CollegeBhavnagarIndia

Personalised recommendations