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Orthogonalization has not been widely used in power system state estimation due to misgivings about its speed. Sparsity related issues and the various advances made in speeding up the orthogonalization are presented in this paper.The efficiency of the method is illustrated by tests on various networks. These tests indicate that the performance is comparable to the normal equations method.

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AbstradPower system state estimation derives a real-time network model by extracting information from a redundant data set consisting of telemetered, predicted and static data items. This paper describes a generalized, fully developed, estimation approach that fundamentally improves the information extraction process. Its main contribution is the successful inclusion of topology and parameters in the estimation and bad data analysis processes. This is valuable both in the initial commissioning of a state estimator, and in its routine real-time and study mode application. The approach involves a variety of novel concepts and methods. It is usable in Weighted Least Squares WLS) and other estimation approaches. *

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