Abstract
Classical stability analysis techniques based on nominal models do not consider the uncertainty of system parameters, their interactions, and nonlinearity, which are important characteristics of practical highly coupled microgrids. In this work, variance-based sensitivity analysis is used to identify parameter combinations that have a significant impact on the small-signal stability of a microgrid featuring two parallel active loads. The analysis indicates that the effectiveness of source-side damping is reduced when resonant frequencies of load input filters become matched. Further results using derivative-based sensitivity analysis reveal that source-side resistance can exhibit drastically different effects on the stability if load input filter resonant frequencies are matched with respect to the case when they are well separated. These behaviours are verified using time-domain switching models.
Highlights
In small-signal modelling of conventional electrical power systems (EPSs), network dynamics are generally neglected since their time constants are much smaller than those of synchronous generators and their control loops
variance-based sensitivity analysis (VBSA) results for the system under study are shown in Figs. 3 and 4
The results show that the most influential parameter for both Re( 1,2) and Re( 3,4) is Rline, meaning that the reduction in the uncertainty of Rline will reduce the output variance the most
Summary
In small-signal modelling of conventional electrical power systems (EPSs), network dynamics are generally neglected since their time constants are much smaller than those of synchronous generators and their control loops. The work reported in [1] provides important insights into the complexity of coupling phenomena between the sources, loads, and network These techniques are prevailing, they are insufficient for describing how the interactions change under possible variations of parameters. Global SA techniques are reviewed in [8] and some considered for the importance ranking of uncertain parameters in power networks in [9, 10] Of interest are those that can help identify different interactions between system parameters, such as variance-based sensitivity analysis (VBSA) [11]. The main idea of this paper is to: (i) demonstrate the application of VBSA to MG EPSs under uncertainty to identify the critical parameters that exhibit nonlinear effects through their interactions on the small-signal stability; (ii) using the identified parameters from (1), present local SA results for selected uncertain system scenarios.
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