Power Exchange Algorithm for Improving Answers of Meta-heuristic Methods in Economic Dispatch

The main purpose of solving economic dispatch problem in power network is to plan the generation of thermal units in order to meet the network demanded load at minimum operating cost while satisfying constraints of system. The represented algorithm in this paper tends to promote the results of economic dispatch problem. This algorithm implements a solution to reach an optimal point near the initial point addressed by meta-heuristic algorithms by using power exchange in units based on incremental cost. Real model of cost function in thermal units is a non-convex function; therefore, gradient-based methods could not be useful in solving mentioned problem. Although lots of meta-heuristic methods for solving economic dispatch problem with constraints Such as genetic algorithm, imperial competition algorithm, tabu search and particle swarm optimization have been presented and all of them have been succeeded in finding optimal solution, none of them could ensures that there wouldn’t be a better point for the problem. Proposed algorithm tends to provide possibility for finding optimal point without calculation burden. This algorithm has been tested on three systems with 10, 13 and 40 thermal units and the results are presented. The conclusions have shown that in the most of the cases, total cost reduced by implementing power exchange algorithm.