Optimization of Economic Dispatch Problem using Nature-Inspired Pelican Optimization Algorithm

Economic Dispatch (ED) is vital to running a power system. It is capable of lowering operational costs and conserving energy resources. The ED problem that is addressed in this paper is non-convex and quadratic in nature, having system constraints such as power balancing and generation limit constraints. The effect of valve-point loading is also considered in the generation cost function. A penalty function strategy is employed to solve the constraint violation problems inherent in this ED problem. The penalized cost of generation is calculated using static penalty functions for infeasible solutions. In this study, we present a pelican optimization algorithm (POA) based strategy for addressing ED problems, which takes its inspiration from the natural world. Inspiring itself from the pelican's foraging habits, POA is a population-based meta-heuristic algorithm with two basic stages: exploration and exploitation. It has a good rate of convergence. The functionality of POA is evaluated using four different test systems of varying degrees of complexity. The results of the experiments and comparisons with other techniques that have been described for ED solutions demonstrate that POA is capable of producing a solution of comparable quality.