Development of a Static State Estimator Part I: Estimation and Bad Data Suppression

This paper forms Part I of a two- part series which describes the construction and the overall software structure of a static state estimator. This part outlines the process of estimation and bad data suppression. The estimation technique uses a fast decoupled approach. The bad data suppression is a modification of the single breaking point of a non-quadratic cost function based on the quadratic-flat. Numerical tests show that this new variable breaking point quadratic-flat has an excellent bad data suppression property. An important feature of the method is that the initial estimates are much closer to the final true solution than the unmodified approach. Many tests have been performed to obtain ranges for the initial breaking point, the step length, the final breaking point and the weighting factor recommended to achieve fast and reliable convergence. These constants are given in the paper.