Control Optimization and Adaptive Tuning of Droop Controlled Systems for DC Bus Stability via Terminal Impedance Shaping

Andy Wong, University of South Carolina

Abstract

Many traditional AC systems have been moving towards DC in recent decades due to advancements in power electronics and semiconductor devices. DC power distribution systems, such as DC microgrids, have become increasing popular due to energy efficiency, resiliency, and renewable energy integration. However, with such systems which commonly utilize droop control, comes an issue of system stability due to the interconnection of multiple feedback-controlled converters to a common bus. To combat this issue, this thesis proposes a control optimization and adaptive tuning approach for maintaining DC bus stability and dynamic performance of droop controlled systems. First, a terminal impedance model was created to characterize the loading effect of closed loop converters attached to a common bus. From the terminal impedance model as well as the converter control model, various frequency domain features were extracted from these models to define objective variables for optimization. Using control optimization techniques, namely Gradient Descent and Particle Swarm Optimization, the control parameters of the system were optimized by shaping the converter terminal impedances to reduce bus resonance while maintaining dynamic performance. Lastly, an adaptive tuner was developed which utilizes the optimization algorithm to update the control parameters of source-side converters in steady state to maintain stability.