Affiliation: | Departamento de Engenharia Elétrica, Universidade Federal de Santa Catarina, Caixa Postal 476, 88049, Florianópolis, SC, Brazil Applied Mathematics Department, University of Manitoba, Winnipeg, Man., R3T 2N2, Canada |
Abstract: | The augmented matrix method for power system state estimation combines simple conception, good numerical behavior and computational efficiency. Concerning bad-data processing, however, the method presents a difficulty: the calculation of normalized residuals is not straightforward, so that the implementation of conventional bad-data identification procedures may become complicated. This paper presents a technique for bad-data processing based on weighted residuals and a nonquadratic cost function to circumvent that problem. The weighted residuals are immediately available from the proposed formulation for the augmented matrix method. The non-quadratic cost function is piecewise quadratic-constant and the break points are varied through the iterations to allow proper bad-data identification. The application of a diakoptical technique avoids the need for costly refactorizations of the augmented matrix. The results from simulation studies carried out with the IEEE 14-bus and 30-bus test systems are presented. |