The Application of Genetic Algorithm with Multi-parent Crossover to Optimal Power Flow Problem

  • T. Srihari
  • Madhu Boppa
  • S. Anil Kumar
  • Harish Pulluri
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 626)


Optimal power flow problem (OPF) with continuous, non-smooth function solved with various optimization methods in the literature. OPF can be solved easily by using evolutionary algorithms such as genetic algorithm. Genetic algorithms are widely used in practice. In the current work, IEEE 30-bus system with several objective functions is solved using genetic algorithm with a new multi-parent crossover (GA-MPC) and this was identified to be better than the other algorithms reported in the paper.


Genetic algorithm Multi-parent crossover Optimal power flow Sum of voltage deviation 


  1. 1.
    J. Carpentier, Contribution to the economic dispatch problem. Bull. Soc. Fr. Electr. 3, 431–447 (1962)Google Scholar
  2. 2.
    K. Lee, Y. Park, J. Ortiz, A united approach to optimal real and reactive power dispatch. IEEE Trans. Power App. Syst. 104, 1147–1153 (1985)Google Scholar
  3. 3.
    M.S. Kumari, S. Maheswarapu, Enhanced genetic algorithm based computation technique for multi-objective optimal power flow. Int. J. Electr. Power Energy Syst. 32(6), 736–742 (2010)Google Scholar
  4. 4.
    H. Pulluri, R.N. Sharma, V. Sharma, An enhanced self-adaptive differential evolution based solution methodology for multi-objective optimal power flow. Appl. Soft Comput. 54, 229–245 (2017)CrossRefGoogle Scholar
  5. 5.
    H. Pulluri, R.N. Sharma, V. Sharma, Preeti, A new colliding bodies optimization for solving optimal power flow problem in power system. Int. Conf. Power Syst., 1–6 (2016).
  6. 6.
    H.R.E.H. Bouchekara, M.A. Abido, A.E. Chaib, R. Mehasni, Optimal power flow using the league championship algorithm: a case study of the Algerian power system. Energy Convers. Manag. 87, 58–70 (2014)CrossRefGoogle Scholar
  7. 7.
    H.R.E.H. Bouchekara, Optimal power flow using black-hole-based optimization approach. Appl. Soft Comput. 24, 879–888 (2014)CrossRefGoogle Scholar
  8. 8.
    A. Sloiman, H. Abdel-Aal, Modern Optimization Techniques with Applications in Electric Systems (Springer Publications, 2011).
  9. 9.
    T.N. Malik, A. Asar, M.F. Wyne, A new hybrid approach for the solution of nonconvex economic dispatch problem with valve point loading effects. Electr. Power Syst. Res. 80, 1128–1136 (2010)Google Scholar
  10. 10.
    K.P. Womg, Y.W. Wong, Genetic and genetic/simulated-annealing approaches to economic dispatch. IEE Proc-Gene. Trnams. Distr. 141(5), 507–514 (1994)CrossRefGoogle Scholar
  11. 11.
    H.R.E.H. Bouchekara, A.E. Chaib, M.A. Abdio, Optimal power flow using GA with a new-multi parent crossover considering: prohibited zone, valve-point effect, multi-fuels and emission. Electr. Engg. (2016).
  12. 12.
    M. Saber, A. Ruhul, L. Dary, GA with a new multi-parent crossover for constrained optimization, in IEEE Congress on Evolutionary Computation, pp. 857–864 (2011)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • T. Srihari
    • 1
  • Madhu Boppa
    • 2
  • S. Anil Kumar
    • 3
  • Harish Pulluri
    • 4
  1. 1.Department of Electrical and Electronics EngineeringGuru Nanak Institution Technical CampusHyderabadIndia
  2. 2.Electrical & Electronics Engineering DepartmentACE Engineering CollegeHyderabadIndia
  3. 3.Electrical & Electronics Engineering DepartmentSt. Mary’s Group of InstitutionsHyderabadIndia
  4. 4.Electrical & Electronics Engineering DepartmentGeethanjali College of Engineering and TechnologyHyderabadIndia

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