Application of Self-Adaptive Biogeography Based Optimization to Economic Load Dispatch Problems

A bio-inspired algorithm of Biogeography Based Optimization (BBO) is organized by two processes; such as the process of migration and mutation. These operations work in the basic probabilistic way. It does not achieve good ability for population diversity and exploration. To improve the superiority of the solutions, the original BBO algorithm is modified. In the proposed algorithm, the migration operation of BBO is migrated with the mutation operation of differential evolution (DE) to enhance population diversity. In addition, BBO’s mutation process is tailored to Gaussian mutation to improve the potential for discovery. It is namely selfadaptive biogeography-based optimization (SABBO). The SABBO algorithm is proposed to solve the extremely challenging economic load dispatch problems in various power system networks. To validate the advantages of the proposed SABBO algorithm used to check economic dispatch problems with consideration of valve-point effects, restricted operating zones, and generator ramp rate limits. Moreover, the SABBO algorithm has been compared in the literature with existing algorithms. The suggested SABBO algorithm's suitability was tested using the standard 6-unit, 15-unit, and 40-unit frameworks.