Optimization based Integrated Adaptive Control Architecture for Grid Connected Inverter (GCI)

This paper presents an optimization-based integrated control architecture for grid-connected inverters (GCIs). The overall objective is to augment existing inverter controllers to improve the quality and performance of GCIs during changing dynamics from DERs or grid. Using an energy decomposition methodology from measurements, the proposed architecture, first, develop high frequency and low-frequency energy signals. Then a dynamic control gain is designed based on an optimization methodology that minimizes error dynamics. The optimization function derived in this work considers both the state energy and controller effect. Then, an integrated control architecture that augments the device-level controller is designed. Coordination between controllers is based on the frequency decomposition of the energy function. The proposed framework was validated via simulation on a power grid model with GCIs. The results prove that the proposed architecture can provide improved control performance during variable operating conditions.