In this workshop, we will understand how numerical optimization algorithms can be converted into feedback controllers to enable robust “closed-loop optimization”. First, we will review different existing approaches of online optimization applied to problems in energy systems, with particular focus on microgrids, and we will discuss their pros and cons. Second, we will review various optimization algorithms to then show how they can be formulated as dynamical systems. Third, we will discuss how to use the aforementioned background to design optimization algorithms in closed loop with physical systems, or feedback-based optimization algorithms [1], that steer the physical system towards the solution of an underlying constrained optimization problem. Finally, we will discuss a few specific applications of feedback optimization to the control and operation of microgrids, and also other possible applications of feedback optimization to energy systems.