Inequality Constraints Based Method for Fast Estimation of Droop Slope Stability Regions for MMC-Based MTDC Systems

This paper proposes an inequality constraints based method to efficiently and quickly estimate stability regions of droop control slopes for modular multilevel converter (MMC)-based multi-terminal dc (MTDC) systems. At first, a general small-signal model of the MMC-MTDC system is developed, which consists of the dc network and the MMCs with dq controllers and multiple droop controllers. When deriving corresponding nonlinear state-space models, the edge-node matrix is introduced for the dc network modeling with arbitrary grid topology and transmission line model. Then, based on the eigenvalues sensitivity and the Taylor Series of eigenvalues, a set of inequality constraints are proposed to expeditiously estimate the suprema of the droop slopes and identify the droop slope stability regions for the MMC-MTDC system. To verify the state-space model, a comparison of dynamic responses between the math model calculation in MATLAB and the EMT simulation in PSCAD/EMTDC is conducted, which demonstrates the accuracy and the correctness of the developed small-signal model. The effectiveness of the proposed parameter stability region estimation method is demonstrated by several examinations including the supremum tests of droop slopes, the stability region sketches on accuracy, and the predicted unstable operations in PSCAD/EMTDC.

Automated summary

This paper introduces an inequality constraints based method to estimate stability regions of droop control slopes for modular multilevel converter (MMC)-based multi-terminal dc (MTDC) systems efficiently and quickly. The method utilizes edge-node matrix and eigenvalues sensitivity to propose a set of inequality constraints for expeditiously estimating the suprema of droop slopes and identifying the droop slope stability regions in the MMC-MTDC system. The state-space model accuracy is validated through dynamic response comparison between math model calculation and EMT simulation, demonstrating the effectiveness of the proposed parameter stability region estimation method.