Avaliação da implantação de sistemas de recomposição automática em redes de distribuição de energia elétrica - Guth, Thiago Freire (2013)
The automation of power distribution networks contributes to the improvement of the quality indicators for providing isolation of defective parts through remote controls for opening and closing devices, as well as transfers to defective parts without alternative sources of supply. These commands are normally executed in the Operation Centers by specialized technicians. Although, providing greater speed than the local execution of opening and closing braces through teams in the field for more complex circuits requires technicians operating an analysis of a significant set of variables for decision making. This time devoted to technical analysis reduces earnings quality compared automation solution, where commands could be achieved through pre-defined algorithms, known as Automatic Replenishment. To measure the gain of additional solutions of this nature is necessary to determine the behavior of time to maneuver performed by technicians and those obtained by automatic recomposition. With such a statistical study sample can define the average times for each situation and size of these times you can compare the two situations, basically inserting the time difference on a methodology for calculation of quality indicators. This study aims to perform the statistical survey on a sample of a system already deployed in a power distributor, to establish comparison regarding the quality gains through the methodology of the MLE (Logical Structural) and apply a decision model based on multicriteria to provide a prioritization matrix circuits where automatic recovery can be more advantageous. Although the scope of this work involves only the automatic replenishment, the statistical basis of the obtained times can serve as a starting point for studies related to other more sophisticated mechanisms of self-diagnosis and self restoration as the "Self Healing" present in the context of Smart Grids.