Invasive weed optimization algorithm for solving economic load dispatch

Abstract

The economic load dispatch problem is an online optimization problem to calculate the minimal fuel cost for each power generator under load constraints. At first, the classical methods such as lambda iteration and non-linear programming were used to solve the economic load dispatch problem. Although of their accuracy, these methods are time consuming. Meta-heuristic algorithms such as Particle swarm optimization, Ant colony and Genetic algorithms give better solution while their running time is longer. The hybrid models, by combining two different algorithms, were experimented to get benefits of both mentioned methods. In this paper, a novel algorithm based on invasive weed optimization method is used to solve the economic load dispatch problem under generation and load constraints in order to overcome drawbacks of previous techniques. The proposed algorithm is implemented in MATLAB environment and tested on a 3-units power system. Different test cases are proposed and the results show the efficiency and accuracy of the proposed algorithm in solving the economic dispatch problem.