Analysis of confidence bounds in power system state estimation with uncertainty in both measurements and parameters

A method for uncertainty analysis in power system state estimation is proposed. The uncertainty is expressed in both measurements and network parameters. Uncertainties in both measurements and parameters are known and bounded. The problem is formulated as a constrained non-linear optimization problem. To find the tightest possible upper and lower bounds of any state variable, the problem is solved by sequential quadratic programming (SQP) techniques. When applied to the 6-bus, IEEE 14-bus and IEEE 30-bus networks, the proposed method shows reliability and accuracy in estimating the uncertainty bounds in power system state estimation. In addition, assessment of time performance is carried out to demonstrate that the proposed method is suitable for either an on-line or an off-line application.