LU Shuai, GU Wei, YU Ruizhi, et al. Multi-scale Simulation of Cascading Failures in Integrated Electricity-gas-heat Systems: Challenges and Prospects[J]. 2026, 46(7): 2865-2881.
DOI:
LU Shuai, GU Wei, YU Ruizhi, et al. Multi-scale Simulation of Cascading Failures in Integrated Electricity-gas-heat Systems: Challenges and Prospects[J]. 2026, 46(7): 2865-2881.DOI: 10.13334/j.0258-8013.pcsee.251814.
Multi-scale Simulation of Cascading Failures in Integrated Electricity-gas-heat Systems: Challenges and Prospects
Integrated electricity-gas-heat energy systems can improve energy efficiency and support the integration of renewable energy by utilizing multi-energy synergy
serving as a central carrier to facilitate the transition of the energy structure and the "dual-carbon" strategy. However
the close coupling of electricity
gas
and heat systems increases the risk of fault propagation
where a local fault in a single subsystem can develop into a widespread multi-energy cascading failure (MECF). Considering this
this paper focuses on multi-scale simulation technologies for MECFs
systematically analyzing their typical features and scientific challenges
reviewing current research domestically and internationally
and identifying research gaps in dynamic failure modeling
efficient simulation computation
and cross-system awareness and prediction. Based on this
three key future research directions are proposed: 1) developing multi-scale simulation models for MECFs to capture the physics of local fault evolution and network-wide propagation; 2) advancing efficient and robust computational methods to solve high-dimensional
strongly stiff
and non-smooth systems; 3) establishing awareness and prediction techniques under significant information barriers to enable failure backtracking and assessment with limited data. This research aims to provide essential insights for establishing the safety defense theory of next-generation energy and power systems
offering theoretical support to ensure the secure operation of integrated energy and power systems.
Graph Reinforcement Learning-based Collaborative Optimization for Dynamic Reconfiguration and Reactive Power Compensation in Active Distribution Networks
Federated Split Reinforcement Learning-driven Privacy-preserving Coordinated Operation Method for Distribution Network and Buildings
A Review of Power System Planning Method and Impact Assessment of “Source-grid-load” Integrating Electric Meteorology
Series-capacitor-transformer Hybrid High Step-down Ratio Buck Converter
Entrepreneurship drives breakthrough innovation and enterprise total factor productivity