Plug-and-play control and optimization in microgrids

Abstract

A hierarchical layering of primary, secondary, and tertiary control is the standard operation paradigm for bulk power systems. Similar hierarchical decision architectures have been proposed for microgrids. However, the control objectives in microgrids must be achieved while allowing for robust plug-and-play operation and maximal flexibility, without hierarchical decision making, time-scale separations, and central authorities. Here, we explore control and optimization strategies for the three decision layers and illuminate some possibly-unexpected connections and dependencies among them. Our analysis builds upon first-principle models and decentralized droop control. We investigate distributed architectures for secondary frequency regulation and find that averaging-based distributed controllers using communication among the generation units offer the best combination of flexibility and performance. We further leverage these results to study constrained AC economic dispatch in a tertiary control layer. We show that the minimizers of the economic dispatch problem are in one-to-one correspondence with the set of steady-states reachable by droop control. This equivalence results in simple guidelines to select the droop coefficients, which include the known criteria for load sharing.