Stability Constrained Gain Optimization of Droop Controlled Converters in DC Nanogrids

Abstract

Autonomous operation of the dc grids with converter interfaced renewable energy sources and energy storage with droop based control can lead to instability. This paper analyzes the stability of droop based closed loop controllers in a dc nanogrid. Linear state space modeling approach is used to model the small signal model of the droop controlled dc-dc converters. The dominant eigenvalues are analyzed, and the effect of closed-loop gains of the converters are investigated. Detailed parametric sensitivity analysis and participation factor of the system parasitics and the controller gains are also presented. Based on that, a segmented droop strategy is proposed to divide the operating ranges into segments with adaptive controller gains to ensure system stability in all of them. A particle swarm optimization algorithm is used to optimize for the converter gains of individual segments.