Matches in SemOpenAlex for { <https://semopenalex.org/work/W3211666621> ?p ?o ?g. }
- W3211666621 abstract "In recent years, the ML community has seen surges of interest in both adversarially robust learning and implicit layers, but connections between these two areas have seldom been explored. In this work, we combine innovations from these areas to tackle the problem of N-k security-constrained optimal power flow (SCOPF). N-k SCOPF is a core problem for the operation of electrical grids, and aims to schedule power generation in a manner that is robust to potentially k simultaneous equipment outages. Inspired by methods in adversarially robust training, we frame N-k SCOPF as a minimax optimization problem - viewing power generation settings as adjustable parameters and equipment outages as (adversarial) attacks - and solve this problem via gradient-based techniques. The loss function of this minimax problem involves resolving implicit equations representing grid physics and operational decisions, which we differentiate through via the implicit function theorem. We demonstrate the efficacy of our framework in solving N-3 SCOPF, which has traditionally been considered as prohibitively expensive to solve given that the problem size depends combinatorially on the number of potential outages." @default.
- W3211666621 created "2021-11-22" @default.
- W3211666621 creator A5027185547 @default.
- W3211666621 creator A5033242808 @default.
- W3211666621 creator A5075035644 @default.
- W3211666621 creator A5075620331 @default.
- W3211666621 creator A5088565614 @default.
- W3211666621 date "2021-11-12" @default.
- W3211666621 modified "2023-09-27" @default.
- W3211666621 title "Adversarially Robust Learning for Security-Constrained Optimal Power Flow" @default.
- W3211666621 cites W1542343170 @default.
- W3211666621 cites W1585773866 @default.
- W3211666621 cites W1866987985 @default.
- W3211666621 cites W2015050404 @default.
- W3211666621 cites W2040884647 @default.
- W3211666621 cites W2131116400 @default.
- W3211666621 cites W2166107799 @default.
- W3211666621 cites W2342709508 @default.
- W3211666621 cites W2587752930 @default.
- W3211666621 cites W2751681791 @default.
- W3211666621 cites W2752814746 @default.
- W3211666621 cites W2765201768 @default.
- W3211666621 cites W2766493915 @default.
- W3211666621 cites W2887448005 @default.
- W3211666621 cites W2891122218 @default.
- W3211666621 cites W2891638642 @default.
- W3211666621 cites W2907670343 @default.
- W3211666621 cites W2913848079 @default.
- W3211666621 cites W2947138043 @default.
- W3211666621 cites W2950321944 @default.
- W3211666621 cites W2950398529 @default.
- W3211666621 cites W2962756936 @default.
- W3211666621 cites W2962826047 @default.
- W3211666621 cites W2962943487 @default.
- W3211666621 cites W2963207607 @default.
- W3211666621 cites W2963496101 @default.
- W3211666621 cites W2963626025 @default.
- W3211666621 cites W2963755523 @default.
- W3211666621 cites W2963850168 @default.
- W3211666621 cites W2963970238 @default.
- W3211666621 cites W2964253222 @default.
- W3211666621 cites W2964346299 @default.
- W3211666621 cites W2970791107 @default.
- W3211666621 cites W2970900903 @default.
- W3211666621 cites W3013520104 @default.
- W3211666621 cites W3030068507 @default.
- W3211666621 cites W3097104515 @default.
- W3211666621 cites W3101071828 @default.
- W3211666621 cites W3110946112 @default.
- W3211666621 cites W42717677 @default.
- W3211666621 cites W2290452516 @default.
- W3211666621 hasPublicationYear "2021" @default.
- W3211666621 type Work @default.
- W3211666621 sameAs 3211666621 @default.
- W3211666621 citedByCount "0" @default.
- W3211666621 crossrefType "posted-content" @default.
- W3211666621 hasAuthorship W3211666621A5027185547 @default.
- W3211666621 hasAuthorship W3211666621A5033242808 @default.
- W3211666621 hasAuthorship W3211666621A5075035644 @default.
- W3211666621 hasAuthorship W3211666621A5075620331 @default.
- W3211666621 hasAuthorship W3211666621A5088565614 @default.
- W3211666621 hasConcept C111919701 @default.
- W3211666621 hasConcept C121332964 @default.
- W3211666621 hasConcept C126255220 @default.
- W3211666621 hasConcept C14036430 @default.
- W3211666621 hasConcept C149728462 @default.
- W3211666621 hasConcept C163258240 @default.
- W3211666621 hasConcept C187691185 @default.
- W3211666621 hasConcept C2524010 @default.
- W3211666621 hasConcept C2986056383 @default.
- W3211666621 hasConcept C33923547 @default.
- W3211666621 hasConcept C38349280 @default.
- W3211666621 hasConcept C41008148 @default.
- W3211666621 hasConcept C62520636 @default.
- W3211666621 hasConcept C68387754 @default.
- W3211666621 hasConcept C78458016 @default.
- W3211666621 hasConcept C86803240 @default.
- W3211666621 hasConcept C89227174 @default.
- W3211666621 hasConceptScore W3211666621C111919701 @default.
- W3211666621 hasConceptScore W3211666621C121332964 @default.
- W3211666621 hasConceptScore W3211666621C126255220 @default.
- W3211666621 hasConceptScore W3211666621C14036430 @default.
- W3211666621 hasConceptScore W3211666621C149728462 @default.
- W3211666621 hasConceptScore W3211666621C163258240 @default.
- W3211666621 hasConceptScore W3211666621C187691185 @default.
- W3211666621 hasConceptScore W3211666621C2524010 @default.
- W3211666621 hasConceptScore W3211666621C2986056383 @default.
- W3211666621 hasConceptScore W3211666621C33923547 @default.
- W3211666621 hasConceptScore W3211666621C38349280 @default.
- W3211666621 hasConceptScore W3211666621C41008148 @default.
- W3211666621 hasConceptScore W3211666621C62520636 @default.
- W3211666621 hasConceptScore W3211666621C68387754 @default.
- W3211666621 hasConceptScore W3211666621C78458016 @default.
- W3211666621 hasConceptScore W3211666621C86803240 @default.
- W3211666621 hasConceptScore W3211666621C89227174 @default.
- W3211666621 hasLocation W32116666211 @default.
- W3211666621 hasOpenAccess W3211666621 @default.
- W3211666621 hasPrimaryLocation W32116666211 @default.
- W3211666621 hasRelatedWork W1488989473 @default.
- W3211666621 hasRelatedWork W2611423960 @default.