Use of AR Block Processing for Estimating the State Variables of Power System

This paper describes an approach to identify and
change the measurement weights used in Weight Least Square
(WLS) estimation method employed in State Estimation (SE). In
practice, the individual measurement is assigned with their own
weight factor based on technical experience by the engineers.
However, uncertainty in analog measurements could occur in a
real time system. Those measurements that are assigned with
high weighting factor need not be a good data. This problem is
solved by introducing signal-processing technique for identifying
and changing the measurement weights of the bad measurements
if the related measurement is assigned with high weight factors.
Samples of the local utility network for 103-bus parameter are
collected and simulated using Burg and Modified Covariance
algorithm to estimate the state variables. Simulation results to
support the proposed method are also presented and compared
with WLS method.