DISEÑO Y EXPERIMENTACIÓN DE TÉCNICAS DE COMPUTO EVOLUTIVO EN ENERGÍA E IDENTIFICACIÓN DE SISTEMAS

Abstract

The area of research and development in the field of engineering has been growing in recent years, especially those related to renewable energy and energy applications due to their environmental repercussions. The main objective of these applications is reducing the costs of operation, increase the efficiency of certain elements, reduce the losses of energy, and so on. On the other hand, the systems identification is an area that has attracted the attention in several fields of engineering due they can emulate real-world plants and processes which are of non-linear nature. So that, the correct optimization in the energy applications and the accurate approximation in the systems identifications become in a really complex task. Evolutionary computational techniques (ETC) are techniques developed to solve optimization problems competitively, especially where the error surface generated by a particular problem tends to multimodal nature, in which traditional optimization techniques are unable to determine the global optimal. In this work, several ETCs are used in energy applications such as Induction motor parameter estimation, Distribution networks, Solar cells parameters estimation, and for the system identification of Hammerstein models. All experiments reported in this work, are validated using statistical tools to corroborate the results.