IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2025 (SCI-Expanded)
The increasing structural and operational interdependencies between power distribution networks (PDNs) and district heating networks (DHNs) have intensified the need for integrated and resilient contingency management strategies. This necessitates the development of advanced analytical frameworks for probabilistic N-1 and N-k security assessments that capture the temporal and spatial coupling of these networks throughout all phases of resilient operations. Owing to this necessity, this article proposes a novel contingency multicriteria assessment framework to quantify the interdependencies between the resilience of PDNs and DHNs, incorporating various phases of contingency chains. The methodology utilizes the simultaneous evaluation of criteria and alternatives (SECA) approach to systematically rank critical contingencies, thereby revealing the most severe potential cascading failures that threaten energy security. The following stage entails the presentation of a pioneering spatiotemporal cascading failure analytical model, which is developed to coordinate the withstand-and-recover phases across interdependent PDNs and DHNs. This model is supported by tailored operational resilience key performance indicators (KPIs) that trace power-induced heating service degradation across diverse backup configurations, including line-pack storage, energy storage systems (ESSs), and integrated demand-response programs (DRPs). As another unattainable novelty, the developed decision-making framework integrates static and dynamic resilience analyses to provide an all-encompassing comprehension of the integrated PDNs and DHNs' resilience. The proposed framework is validated through co-simulation of a modified IEEE 33-bus PDN and a 32-node DHN, employing analytical and empirical methodologies. The results indicate that the strategic implementation of backup flexibility resources, when synchronized with DHN service provision, can enhance DHN service continuity by up to 29%, while concurrently reducing the full recovery time by nearly 41%. Dynamic resilience analyses are further conducted in DIgSILENT PowerFactory to evaluate the real-time transient response under top-ranked contingency scenarios.