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Fault localization in microgrids based on an optimized meter allocation


The current changes in the electric power system, for example, due to the introduction ofdistributed generation sources, bring new challenges to the model and operation for traditional distribution electric power systems. These changes in the electrical scenario have arised due to the continuous search for more sustainable sources of electrical energy, transport, final use of electricity more efficiently and by due to the need to modernize the infrastructure of theelectrical sector. In this sense, there is an increasing interest in improving the electrical current networks through the automation of all processes and an incorporation of some intelligence in the actions of the operation and restoration of the system in face of undesired situations. In this way, this research project proposes, based on an optimized allocation of meters, to determine aprecise location of short-circuits that can occur in the micro grids. A fast and precise location of short-circuits in this context reflects on the agility of the operation, on the restoration of the electrical system for the utilities, as well as on the satisfaction of the end users. It also reflects on a better evaluation of the utilities by the regulatory agencies when analyzing the quality indicesof service provided. In this research, considering an optimized allocation of meters, machine learning tools, and/or deep learning will be used, resulting in a precise and fast location of the fault situation, also addressing the problem of multiple fault location, still not well solved in the current proposals for distribution systems. For an assessment and validation of the techniquesapplied to the short-circuit location problem, PSCAD"/ EMTDC" software will be employed. (AU)

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