GA tuned differential evolution for economic load dispatch with non-convex cost function

This paper proposes a genetic algorithm (GA) tuned differential evolution (DE) method for solving economic dispatch (ED) problem with non-smooth cost curves. The tuning of the weights in differential evolution is the key issue in designing an efficient differential evolution algorithm. Their values are dependent on nature and characteristic of objective function. As there is no explicit rule or guideline in determining these parameters, they are generally determined after a number of experimentations. In this paper floating point GA is used in tuning these parameters. The developed algorithm is experimented on a medium size of 40 units. The performance of the proposed algorithm is compared with standard improved fast evolutionary programming (IFEP) techniques. The simulation results demonstrate that GA tuned DE method is very efficient in finding higher quality solutions in high order non-convex ED problems.