Network-Based Approach to Identify Criticalities in State Estimation

Power system state estimation (SE) plays a crucial role in the success of advanced tools employed for power system analysis and control in Energy Management Systems. SE is responsible for providing a consistent real-time dataset, free from errors that may compromise decision-making and put the system at risk. The presence of criticalities involving elements such as network branches, measuring units or measurements may impose difficulties for the detection/identification of gross errors in the acquired data. The simultaneous unavailability of the elements that form a given criticality makes the grid unobservable. This paper presents a flexible and effective network-based methodology for the integrated identification of critical groups of branches, measurements and measuring units in SE. The proposed algorithms are constructed, having the properties of such criticalities as their central pillar. Tests performed with IEEE 14-, 30-, and 118-bus benchmark systems are presented, and the obtained results show the effectiveness of the proposed approach.