Reliability-oriented Stochastic Optimization of Integrated Energy Systems Under Extreme Weather Conditions: A Case Study in Ningbo, China

As extreme weather events become more frequent and severe, energy systems face growing challenges from increasing demand and equipment failures. This study presents a climate-resilient design framework through a case study of Ningbo, China—a coastal city facing typhoon risks. Using real energy demand data and operational parameters from a Ningbo energy center, a multi- scenario analytical model is developed to evaluate combined effects between extreme weather patterns, equipment vulnerability, and demand fluctuations. Three adaptation strategies are explored: equipment addition, energy storage integration, and active load optimization. The methodology employs NSGA-II multi-objective optimization and robust analysis techniques to systematically evaluate solutions under extreme conditions. Results show that equipment addition consistently achieves the best cost-reliability trade-off, while energy storage becomes more valuable under severe typhoon conditions. The active load strategy offers moderate improvements but is limited under extreme events. This work integrates real-world data and coordinates multi-strategy evaluation, providing quantitative insights into the resilience benefits of each approach. The proposed framework can be adapted to other regions and extreme weather types, offering practical guidance for designing robust energy systems in the face of climate change.