Critical pseudo-measurement selection for unreduced external system modeling

摘要

Attention is focused on state estimator based methods for unreduced external system representation. The crucial issues related to these methods are: how to prevent the contamination of internal system estimates by usually less accurate external data, and how to keep power mismatches at boundary buses within reasonable limits. The proposed strategy to solve both problems is based on the use of non-redundant pseudo-measurements for the external system. In order to improve the quality of the external system representation, it is desirable to choose, from all currently available external pseudo-measurements, those which are the most reliable in some sense. This paper introduces a method to select the most reliable non-redundant pseudo-measurements for unreduced external system modeling. The proposed algorithm is combinatorial, and exhibits as its main feature the flexibility to accommodate user-defined criteria for selecting the external data. The results obtained through the proposed method are verified by performing contingency analysis studies in the IEEE 14-bus and 30-bus test systems, as well as in a 48-bus realistic network.