Metering scheme optimization with emphasis on ensuring bad-data processing capability

This paper addresses the optimization of metering schemes employed for power system online monitoring through state estimation. The proposed methodology preserves the state estimator bad-data processing capability while different cost criteria are minimized. This is accomplished by employing an enhanced topological method to perform observability/criticality analysis on candidate metering schemes. The optimization is carried out by a steady-state genetic algorithm. Extended applications are developed to guarantee robustness in case of loss of. a. remote terminal unit and to improve existing metering schemes. Results show that the approach adequately fulfills the desired properties related to bad-data processing, cost, and robustness.