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 Plus annual

Presents the access of premium content as premium feature

Premium Content

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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

For a timely decarbonization of our economy, power systems need toaccommodate increasing numbers of clean but stochastic resources. This requiresnew operational methods that internalize this stochasticity to ensure safetyand efficiency. This paper proposes a novel approach to compute adaptive safetyintervals for each stochastic resource that internalize power flow physics andoptimize the expected cost of system operations, making them ``prescriptive''.The resulting intervals are interpretable and can be used in a tractable robustoptimal power flow problem as uncertainty sets. We use stochastic gradientdescent with differentiable optimization layers to compute a mapping thatobtains these intervals from a given vector of context parameters that capturesthe expected system state. We demonstrate and discuss the proposed approach ontwo case studies.

Prescribed Robustness in Optimal Power Flow