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

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.

[1]  K. Lee,et al.  A United Approach to Optimal Real and Reactive Power Dispatch , 1985, IEEE Transactions on Power Apparatus and Systems.

[2]  H. R. E. H. Bouchekara,et al.  Optimal power flow using black-hole-based optimization approach , 2014, Appl. Soft Comput..

[3]  Shakil Akhtar,et al.  A new hybrid approach for the solution of nonconvex economic dispatch problem with valve-point effects , 2010 .

[4]  Harish Pulluri,et al.  An enhanced self-adaptive differential evolution based solution methodology for multiobjective optimal power flow , 2017, Appl. Soft Comput..

[5]  Sydulu Maheswarapu,et al.  Enhanced Genetic Algorithm based computation technique for multi-objective Optimal Power Flow solution , 2010 .

[6]  H. R. E. H. Bouchekara,et al.  Optimal power flow using GA with a new multi-parent crossover considering: prohibited zones, valve-point effect, multi-fuels and emission , 2018 .

[7]  M. A. Abido,et al.  Optimal power flow using the league championship algorithm: A case study of the Algerian power system , 2014 .

[8]  Y. W. Wong,et al.  Genetic and genetic/simulated-annealing approaches to economic dispatch , 1994 .

[9]  Soliman Abdel-hady Soliman,et al.  Modern Optimization Techniques with Applications in Electric Power Systems , 2011 .

[10]  Harish Pulluri,et al.  A new colliding bodies optimization for solving optimal power flow problem in power system , 2016, 2016 IEEE 6th International Conference on Power Systems (ICPS).

[11]  Ruhul A. Sarker,et al.  GA with a new multi-parent crossover for constrained optimization , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).