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

Estimation of sensitivity matrices in electrical transmission systems allowsgrid operators to evaluate in real-time how changes in power injections reflectinto changes in power flows. In this paper, we propose a robust low-rankminimization approach to estimate sensitivity matrices based on measurements ofpower injections and power flows. An online proximal-gradient method isproposed to estimate sensitivities on-the-fly from real-time measurements. Theproposed method obtains meaningful estimates with fewer measurements when theregression model is underdetermined, in contrast with existing methods based onleast-squares approaches. In addition, our method can also identify faultymeasurements and handle missing data. In this work, convergence results interms of dynamic regret are presented. Numerical tests corroborate theeffectiveness of the novel approach and the robustness of missing measurementsand outliers.

Data-Driven and Online Estimation of Linear Sensitivity Distribution Factors: A Low-rank Approach