Search of Initial Conditions for Dynamic Systems using Intelligent Optimization Methods

In this contribution we propose the use of intelligent op- timization methods in the search of initial conditions for the analysis of dynamic systems. The use of intelligent opti- mization methods provides a search tool that does not de- pend on the experience of the researcher in the particular system to analyze. An example of a dynamic system that models an electrical power system is provided. Three in- telligent optimization methods are compared: genetic algo- rithms, multimodal genetic algorithms, and particle swarm optimization. An analysis of precision and error is pre- sented, contrasting the three methods.