English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Recent advances in power system State Estimation (SE) have includedequivalent circuit models for representing measurement data that allowsincorporation of both PMU and RTU measurements within the state estimator. Inthis paper, we introduce a probabilistic framework with a new RTU model thatrenders the complete SE problem linear while not affecting its accuracy. It isdemonstrated that the probabilistic state of a system can be efficiently andaccurately estimated not only with the uncertainties from the measurement data,but also while including variations from transmission network models. Todemonstrate accuracy and scalability we present probabilistic state estimationresults for the 82k test case that represents the transmission level grid ofthe entire USA. It is shown that the estimated state distributions include thetrue grid state, while their mean exactly corresponds to the estimateddeterministic state obtained from the nonlinear state estimator.

Linear Power Grid State Estimation with Modeling Uncertainties