Effect of latency on state estimation uncertainty

State Estimation is a key function for the control and secure operation of automated systems. Distribution system operators exploit the state estimation algorithms to merge the available measurements and to obtain the most likely state of the system. The knowledge of the expected uncertainty of the state estimator is critical to fine-tune the applications based on state estimation results or to determine type and placement of instruments. This paper extends the existing methodologies to derive the state estimation uncertainty by considering the case of non-ideal measurement reporting due to possible delays and/or asynchronous measurements. The developed uncertainty propagation models are validated via Monte Carlo analysis using a sample distribution network as test system.