  Traditionally, offline optimization of power systems is acceptable due to the
largely predictable loads and reliable generation. The increasing penetration
of fluctuating renewable generation and Internet-of-Things devices allowing for
fine-grained controllability of loads have led to the diminishing applicability
of offline optimization in the power systems domain, and have redirected
attention to online optimization methods. However, online optimization is a
broad topic that can be applied in and motivated by different settings,
operated on different time scales, and built on different theoretical
foundations. This paper reviews the various types of online optimization
techniques used in the power systems domain and aims to make clear the
distinction between the most common techniques used. In particular, we
introduce and compare four distinct techniques used covering the breadth of
online optimization techniques used in the power systems domain, i.e.,
optimization-guided dynamic control, feedback optimization for single-period
problems, Lyapunov-based optimization, and online convex optimization
techniques for multi-period problems. Lastly, we recommend some potential
future directions for online optimization in the power systems domain.
