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