Publication

Abstract : Generally, Economic dispatch (ED) represents the heart of economic operation of a power system. Besides sustaining the system reliability, meeting the forecasted system load at the lowest possible cost is one of the important objectives in power system operation. Nevertheless, the ED problem chiefly based on the generating unit cost function. This paper presents a novel hybrid Particle Swarm optimization and Butterfly Optimization (PSO-BF) algorithm to optimize the economic dispatch of the electric power system. Here, the load distribution problem for various time periods given multiple objectives of the power market is described. Moreover, different weights are assigned for different objectives to change multiobjective optimization issues into fuzzy single-objective optimization issues. Thus, the solution exploiting the idea of maximum satisfaction is attained. This proposed algorithm is used to establish a widespread dispatching optimization technique with the objective of minimization of coal consumption, pollution emission and purchasing cost. Finally, the computation time for the proposed algorithm is summarized and shows better results than the conventional methods such as Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), Artificial Bee Colony (ABC), and Ant Colony Optimization (ACO).