Economic Dispatch Using an Efficient Teaching-Learning-Based Optimization Algorithm

This paper proposes the utilization of the metaheuristic Teaching-Learning-Based Optimization for solving the economic dispatch problem. Depending on several aspects related to the equipment, and on the objectives to be pursued, the mathematical model of the economic dispatch problem may result in non-convex and non-differentiable, posing difficulties to the conventional mathematical programming techniques. The use of metaheuristics can overcome such difficulties. The population-based metaheuristic used in this paper is conceptually simple and computationally fast. It is also well-known for requiring a few parameters, namely the population size and the number of iterations. The implementation proposed in this paper is parameter-free, in the sense that all required parameters are automatically set as a function of the characteristics of the power system itself. Power systems with three to 15 generation units were used in the computer simulations The results obtained with the proposed method are compared with the ones presented in the literature, demonstrating that TLBO can provide high-quality solutions.