Data Analytics for Admittance Matrix Estimation of Poorly Monitored Distribution Grids

Smart grid operations require accurate information on network topology and electrical equipment parameters. This paper proposes estimating such information with data from the smart grid. Assuming that the availability of bus voltage data is restricted to their magnitude, a linear model of the relationship between these data and the parameters of the admittance matrix is derived in a way that does not involve bus voltage angles. A regression optimizer is then proposed to minimize the deviation between data and values estimated by the linear model. Results on the IEEE 33 bus system are presented to illustrate the model accuracy and efficiency when used to estimate parameters of medium-voltage, three-phase balanced grids.

Automated summary

This paper proposes a method for estimating accurate network topology and electrical equipment parameters using data from the smart grid. By deriving a linear model of the relationship between the data and the parameters of the admittance matrix, without considering bus voltage angles, and using a regression optimizer to minimize deviations, the model shows accuracy and efficiency in estimating parameters of medium-voltage, three-phase balanced grids, as demonstrated with the IEEE 33 bus system.