Identification of Critical Parameters Affecting the Small-Signal Stability of Converter-based Microgrids

摘要

The analysis of the small-signal stability of converter-based microgrids is well established, but the existing deterministic approaches cannot fully capture the impact of random parameters resulting from complex converter control structures and stochastic operation scenarios. Accurate assessment of the relevance of different parameters can facilitate efficient modeling, online monitoring and control design of the microgrids. In this paper, a global sensitivity analysis (GSA) framework is proposed to identify the most relevant parameters that affect the small-signal stability of converter-based microgrids. First, the systematic approach to derive the complete small-signal state-space model of the microgrid is introduced and the stability index is defined. Then, the system operating states, the control and the network parameters are chosen as input variables, and the priority ranking procedure based on GSA is explained. Next, the Levenberg-Marquardt based power flow calculation is adopted to determine the steady-state operation point. The polynomial chaos expansion and the low-rank approximation methods are introduced into the GSA to further improve computation efficiency. Finally, the proposed methodology is applied to an exemplary microgrid. The critical parameters influencing the system small-signal stability are identified, and the results are compared with those of the conventional local sensitivity analysis. The correctness and effectiveness of the proposed methodology are verified by real-time simulation results.