Small-Signal Stability Modeling, Sensitivity Analysis, and Parameter Optimization of Improved Virtual Synchronous Machine Based Standalone Inverter

Abstract

The virtual synchronous machine (VSM) concept is emerging as a flexible approach for controlling power electronic converters in grid-connected and standalone applications. In this study, we have used the mathematical model of a Virtual machine with a virtual exciter and governor for the standalone inverter to optimize the parameter for small-signal stability. Firstly, the small-signal models of virtual synchronous generator with load have developed, and subsequently, the system eigenvalues were obtained by solving the state Jacobian matrix. Next, the sensitivity of the eigenvalue location on controller parameters has been studied. The parameters are optimized on the basis of the location of dominant eigenvalues using a genetic algorithm. Finally, the optimal controller parameters are used to test the system’s dynamics by solving the model equations with Ordinary Differential Equation (ODE) solver. Moreover, our conclusions were also tested using the actual switching devices on Matlab/Simulink. The results indicate that the frequency stability can be enhanced drastically by optimizing a wide range of VSM parameters. The frequency stability sensitivity with respect to load variation has been improved. The transient settling time of system response for optimized values is 0.25 sec which is only 5% of that for general values. The results of this work are relevant for the VSM-based microgrid small-signal stability analysis.