mlsanityData to 14 Oct 2026

Towards Online Optimization for Power Grids

arXiv 2109.12510 ↗First posted 26 Sep 2021math.OCcited by 1

Not on the map. Why?

Abstract (arXiv)

In this note, we discuss potential advantages in extending distributed optimization frameworks to enhance support for power grid operators managing an influx of online sequential decisions. First, we review the state-of-the-art distributed optimization frameworks for electric power systems, and explain how distributed algorithms deliver scalable solutions. Next, we introduce key concepts and paradigms for online optimization, and present a distributed online optimization framework highlighting important performance characteristics. Finally, we discuss the connection and difference between offline and online distributed optimization, showcasing the suitability of such optimization techniques for power grid applications.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 26 Sep 2021.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2022: 1.

1 paper.