Abstract
The strategical allocation of meters, such as the Phasor Measurement Unit (PMU), at Power Distribution Systems (PDS), represents an optimization of the use of monitoring resources. This optimization can contribute to the State Estimation (SE) process, which consists of obtaining an estimated electrical network state without full monitoring. Meta-heuristics are potential methods for application to optimal allocation problems, such as meters in PDS. Still, computational intelligence techniques, such as Artificial Neural Networks (ANN), can be applied to SE, due to its agility in processing available measures. Therefore, this work aims to investigate the potential of associating a meta-heuristic technique, Artificial Immunological System (AIS), for the allocation of meters with the processing agility of ANN for the evaluation of different allocation options. A case study using a well-known test system in the area of knowledge demonstrates the applicability of the proposed hybrid method.
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