Adaptive-improved genetic algorithm for the economic dispatch of units with multiple fuel options

This article presents the improved genetic algorithm with the Adaptive Multiplier Updating Method (IGA_AMUM) for power economic dispatch of units having multiple fuel options. The Improved Genetic Algorithm (IGA) equipped with an improved, evolutionary direction operator and a migration can search efficiently and actively explore solutions. The Adaptive Multiplier Updating Method (AMUM) is introduced to avoid deforming the augmented Lagrange function and resulting in a difficult solution search. The proposed method integrates the IGA and the AMUM that has merits of automatically adjusting the randomly given penalty to a proper value and requiring only a small-size population for the Economic Dispatch Problem (EDP) with multiple fuel options. Numerical results indicate that the proposed algorithm is more suitable than previous approaches in the practical application. Moreover, the proposed algorithm provides an efficacious approach for the large-scale system of the EDP with multiple fuel options.