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Identification of Critical Clusters in Inverter-based Microgrids

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In this paper, we investigate the stability properties of inverter-based microgrids by establishing the possible presence of the so-called critical clusters - groups of inverters with their control settings being close to the stability boundary. For this, we consider the spectrum of the weighted admittance matrix of the network and show that its distinct eigenvalues correspond to inverter clusters, whose structure can be revealed by the corresponding eigenvector. We show that the maximum eigenvalue of the weighted admittance matrix corresponds to the cluster, closest to stability boundary. We also establish, that there exists a boundary on the value of this eigenvalue, that corresponds to the stability of the overall system. Thus, we make it possible to certify the stability of the system and find the groups of inverters which control settings are closest to the stability boundary.


Andrey Gorbunov    
National University of Singapore

Petr Vorobev    
Skolkovo Institute of Science and Technology
Russian Federation

Jimmy Peng    
National University of Singapore


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