Identification of topology errors with use of unbalance indices and neural networks

The paper deals with identification of topology errors, i.e. identification of interconnect modelling of the physical connections of a power system, which is one of the most important tasks of the real-time modeling of a power system. The paper presents the method, based on utilization of introduced-by-authors so-called unbalance indices and artificial neural networks. Values of the unbalance indices create characteristic sets for different cases of modeling of branches and nodes of the considered power system. In the paper, analyses of the mentioned sets is made. The analysis allows to point out these cases of topology errors, which can be distinguished by examination of values of the unbalance indices. The analysis gives bases for determination of the cases, for which the considered method is efficient. The presented considerations are illustrated by the case study. At the end, the features of the method are summed up.