Power system state estimation and bad data analysis using weighted least square method

Abstract

The static state of an electric power system is defined by the voltage magnitudes and angles at all network buses. The static-state estimator is a data processing algorithm for converting redundant meter readings and other available information into an estimate of the static-state of the system. This paper explains the concept of Weighted Least Square static state estimation. Static state estimation is performed on the data made available through the SCADA system. In this paper this data is obtained through Newton Raphson Load flow analysis. Power flow, power injections and voltage magnitudes are the various measurements taken from load flow analysis as the measurements for state estimation. Weighted least square method estimates the state of the power system based on the weight given to each measurement. A state estimator should have the ability to detect and identify the presence of a bad data. If a bad data is present among the measurements, then the estimated state variables will vary from the actual state variables. In this paper bad data detection is performed using Chi Squared test and bad data identification is performed using largest normalized residual method. Weighted least square algorithm is applied on an IEEE 14 bus.