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A Robust Numerical Technique for Power System State Estimation

It is well known in numerical analysis that the least-squares solution via the conventional Gauss' normal equation used in power system state estimation is prone to ill-conditioning problems by its own nature. Under unfavorable circumstances, this may be detrimental to the method's performance. This paper utilizes a numerically more reliable algorithm, known as Golub's method, to solve the least-squares problem as formulated in power system state estimation. Its improved numerical properties stem from the use of orthogonal transformations, which are perfectly conditioned. Details of the algorithm and its implementation are given, as well as results of its application to three different networks, including an actual 121-bus power system.