Optimal Experiment Design for AC Power Systems Admittance Estimation

TL;DR

This paper introduces an optimal experimental design approach for online parameter estimation in AC power systems, enhancing the accuracy and speed of grid admittance estimation by maximizing information gain per measurement.

Contribution

It presents a novel method that computes optimal excitations for faster and more reliable grid parameter estimation compared to conventional techniques.

Findings

Accelerates convergence of parameter estimation.

Maximizes information gain per measurement.

Improves accuracy of grid admittance models.

Abstract

The integration of renewables into electrical grids calls for the development of tailored control schemes which in turn require reliable grid models. In many cases, the grid topology is known but the actual parameters are not exactly known. This paper proposes a new approach for online parameter estimation in power systems based on optimal experimental design using multiple measurement snapshots. In contrast to conventional methods, our method computes optimal excitations extracting the maximum information in each estimation step to accelerate convergence. The performance of the proposed method is illustrated on a case study.