Propagation analysis of energy-flow fluctuations and cascading failures in integrated energy systems: Complex network theory-based methods and an intuitive statistical indication

• A weighted event coincidence analysis method is used to quantify and visualize node-level fluctuation correlations in IES. • A load-capacity model aims to simulate cascading failures, assessing the extent of propagation by two types of parameters. • Two rich-club coefficients are refined to capture the clustering tendencies of nodes within and between IES subnetworks. • Two rich-club coefficients aim to show the relation between topology and the propagation features of two scenarios in IES. In integrated energy systems (IES), energy-flow fluctuations can rapidly propagate across regions, even resulting in cascading failures. This study applies a series of complex network theory-based analysis methods to uncover the propagation features in above-mentioned scenarios and refines an intuitive statistical index to depict the potential relationship between topological variations and propagation patterns. For energy-flow fluctuations, a weighted event coincidence analysis method (WECA) is proposed to construct fluctuation-sensitivity and fluctuation-propagation correlation matrices, which are further integrated with node-location information to visualize fluctuation sensitivity and spatial propagation intensity. Furthermore, if energy-flow fluctuations trigger cascading failures, a load-capacity model is employed to simulate failure cascades triggered by a single-point failure, where the extent of propagation is quantified based on capacity redundancy and the proportion of non-critical nodes (PNN). To indicate the impact of topological changes on these propagation features, we refine two forms of rich-club coefficients as statistical indices to quantify clustering tendencies, both within intra-network and inter-network, respectively. Case studies demonstrate that the refined rich-club coefficients can strongly and intuitively reflect the relationship between topology and the propagation features of energy-flow fluctuations and cascading failures, highlighting the potential of topological interventions to mitigate such propagation.