This paper proposes a three-layer optimization and an intelligent control algorithm for a microgrid with multiple renewable resources. A dual heuristic dynamic programmingbased system control layer is used to ensure the dynamic performance and voltage dynamics of the microgrid as the system operation conditions change. A local layer maximizes the capability of the photovoltaic (PV) wind power generators and battery systems, and a model predictive control-based device layer increases the tracking accuracy of the converter control. The proposed control scheme, system wide adaptive predictive supervisory control (SWAPSC) smooths the output of PV and wind generators under intermittencies, maintains bus voltage by providing dynamic reactive power support to the grid, and reduces the total system losses while minimizing degradation of battery life span. Performance comparisons are made with and without SWAPSC for an IEEE 13 node test system with a PV farm, a wind farm, and two battery-based energy storage systems.Index Terms-Adaptive critic design (ACD), coordination, model predictive control (MPC), nonlinear optimization control, photovoltaic (PV), wind farm.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.