Hybrid applications of multiagent systems and artificial intelligence techniques to smart grids in power distribution level

The smart grids represent a new generation of electric power systems, combining advances in computing, communication, distributed systems, and artificial intelligence, to provide new features to the power systems as the real-time demand monitoring and real-time energy consumption monitoring, large-scale managing of distributed generators, among others. It is possible by the existence of a distributed control system on the grid. This structure modifies the way it conducts the planning and operation of electrical systems currently, especially in the distribution level, and there are interesting possibilities for research and development made possible by the need for implementation of these features. With this scenario in mind, this thesis uses an approach based on multi-agent systems to simulate this new power distribution system, considering different control options. The use of multi-agent systems technology for smart grid simulation is based on the concept of smart grid as a distributed system - this conceptualization is realized in this work too. In order to validate this proposal, three features expected of these grids were simulated: the classification of non-linear loads; the voltage profile management; and the topological reconfiguration in order to reduce electrical losses. All modeling and developments of these studies are reported here. Finally, the study aims to identify the multi-agent systems as a technology to be utilized both for research and for implementing these grids. (AU)