Modern energy resilience studies with artificial intelligence for energy transitions

Climate change and multifaceted energy crises necessitate resilient power systems for sustainable and smart energy transitions. However, correlations among energy efficiency, energy reliability, robustness, flexibility, and energy resilience remain unclear. This review employs bibliometric analysis to evaluate AI-driven solutions, particularly generative AI, in enhancing urban energy resilience. We quantify energy resilience metrics, as well as highlight the synergy among energy efficiency, energy reliability, robustness, flexibility, energy resilience with carbon neutrality, and multi-sector strategies across supply, demand, storage, and grid systems. The analysis demonstrates the capacity of AI to improve climate change adaptation during extreme events, illustrated as bio-inspired frameworks that emulate human self-regulation and self-healing. The integration of end-user participation and techno-economic-social benefits are emphasized. Big data technology facilitates information communications and inter-component interactions, while generative AI enables automatic city-scale information modeling and real-time decision-making. To conclude, we highlight challenges in smart energy transitions and suggest pathways to harmonize resilience with energy efficiency and reliability under climate challenges.