A new power quality monitor placement method using the multivariable regression model and statistical indices

This paper presents a new method for the placement of power quality monitors (PQMs) by using the multivariable regression (MVR) model and statistical indices. In this method, initially, the correlation coefficients (CC) which show the relationship between buses during system disturbances are calculated and the two buses with highest CC values are identified. These buses are considered as the most sensitive buses in the system. The identified bus voltages are then considered as independent variables in the developed MVR model to estimate the other bus voltages. Finally, the sum square error of the estimator, and mean square error are employed to obtain the Mallows Cp statistic. The appropriate number and placement of PQMs is then determined based on the lowest value of the Mallows Cp statistic. To illustrate the effectiveness of proposed method, the method is tested on two test systems, namely, the 6 bus and the IEEE 9 bus systems.