  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.
