Guaranteed state estimation of power system via interval constraints propagation

This study deals with guaranteed state estimation of power systems in the bounded-error context, which avoids the effect of inexact matching of the assumed statistical hypotheses on the error. A new approach, based on interval constraint propagation, is proposed to compute guaranteed estimates of state variables and measurements. According to the feature of power systems, two improvements based on interval constraint propagation are presented to improve contraction and obtain narrow interval images. First, a monotonicity-based contractor is exploited because of the monotonicity of measure function to part of state variables. Second, the constraints set are extended by combining the measurement constraints. The improved method is guaranteed, contraction efficient and time efficient. The results, achieved using the proposed method, are compared with those typical existing methods to demonstrate its effectiveness. Tests are carried out on the IEEE 14-bus system and the IEEE 118-bus system, respectively.