Intelligent computational methods for power systems optimization problems

Many power systems problems require optimization of an objective. Several of these problems are combinatorial and thus they have a discrete objective function. Various intelligent computational methods, some derived from nature, were used to solve such problems. This presentation provides a brief introduction to various intelligent computational methods. Results obtained for an example problem using a genetic algorithm and an ant colony optimization approach is presented and compared.