Interconnected network state estimation using randomly delayed measurements

In an interconnected power system, the network security and power transfer capability analyzes require a complete network base case solution. With the advent of communications among operations control center computers, real-t ime telemetered data can be exchanged for complete network modeling. Measur ement time skew is a consideration when combining large area data received via a data communication network. In order to accommodate the effects of ra ndomly varying arrival of measurement data, this paper presents an implemen tation of a stochastic Extended Kalman Filter (EKF) algorithm, which provid es optimal estimates of interconnected network states for systems in which some or all measurements are delayed. The method relies on the delay statis tics of exchanged data arrival at the control center and the delay is assum ed to have a binary statistics, i.e., either the measurements arrive in tim e or it is delayed by one time sample. Performance of the proposed method i s compared with that of the standard Weighted Least Square (WLS) technique.