Optimal power flow for a deregulated power system using adaptive real coded biogeography-based optimization

• Determine the optimal settings of control variables for optimal power flow problem.
• ARCBBO algorithm was incorporated with objective function of OPF problem.
• Hence, expose accuracy and robustness of results.
• Using of adaptive Gaussian mutation, obtained smooth convergence characteristics.

The optimization is an important role in the wide geographical distribution of electrical power market, finding the optimum solution for the operation and design of power systems has become a necessity with the increasing cost of raw materials, depleting energy resources and the ever growing demand for electrical energy. Using adaptive real coded biogeography-based optimization (ARCBBO), we present the optimization of various objective functions of an optimal power flow (OPF) problem in a power system. We aimed to determine the optimal settings of control variables for an OPF problem. The proposed approach was tested on a standard IEEE 30-bus system and an IEEE 57-bus system with different objective functions. Simulation results reveal that the proposed ARCBBO approach is effective, robust and more accurate than current methods of power flow optimization in literature.