Enhancing Gas Distribution Network Resilience Utilizing a Mixed Social Network Analysis-Simulation Approach: Application of Artificial Intelligence

This study introduces a resilience-oriented framework to enhance the performance of energy distribution networks under partial high workload conditions with a particular emphasis on natural gas systems. Given the critical role of gas delivery in economic stability and societal well-being, ensuring the reliability and robustness of its network design is imperative. This research adopts a Social Network Analysis (SNA) methodology, augmented by an artificial intelligence-based approach, to appraise the dynamics and interdependencies of gas distribution networks under varying operational conditions. The proposed framework integrates SNA with simulation-based network analysis to enhance resilience by identifying critical nodes and edges susceptible to disruption, especially during demand fluctuations periods. A key advantage of this approach lies in its applicability as a consumer vulnerability mitigation strategy during high-demand scenarios, thereby reinforcing network robustness. The findings offer significant insights and methodological contributions applicable across gas networks, ultimately promoting smarter and more resilient energy solutions. Overall, this research provides a comprehensive strategy for strengthening network resilience, supporting the broader objectives of energy security and sustainability.