New technical report on Bayesian identification of Power Networks
© 2021 EPFL
Bayesian error-in-variable models made specifically for distribution grids can enable the automatic estimation of network parameters from noisy phasor measurements.
With the rise of renewable energies, power flow computations at the distribution level are required in order to optimally schedule the distributed generation and storage capacity. Network parameters such as admittance and topology are required to compute the power flows of an electrical grid. Obtaining such parameters can be challenging for distribution grids due to frequent changes and lower stakes. Solutions to this problem are presented in our new technical report.