Stochastic optimal design of integrated energy systems considering seismic hazards

Though seismic hazards are infrequent, their occurrence can lead to severe destruction. To understand how low-probability, high-impact seismic hazards would affect the stability of integrated energy systems (IES), this paper develops a seismic-resilient integrated energy system (SRIES) design optimization model. The model employs a bi-level Monte Carlo method to capture the low probability of seismic scenarios, monetize the hazard damage, and stochastically optimize IES design and operation. A representative case study in Fujian Province, a region frequently affected by seismic activity in the Taiwan Strait, reveals that: (1) incorporating seismic hazards into IES design leads to a 2% increase in net present cost, with 98% of this increment attributed to hazard-induced unmet energy demands; (2) as the resilience requirement increases, the investment-effectiveness for resilience reinforcement initially rises and then declines, indicating a clear turning point between the costs of resilience reinforcement and its associated benefits; (3) among all technologies within an IES, the electricity grid and combined heating and power (CHP) contribute the most to the system's resilience. Overall, this study is expected to provide quantitative insights for the seismic-resilient design of IES.