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Stochastic optimal design of integrated energy systems considering seismic hazards

Hu, X; Xiao, Y; Wu, N; Tan, J; Miao, H; Wang, M; Jing, R; (2025) Stochastic optimal design of integrated energy systems considering seismic hazards. Applied Energy , 383 , Article 125363. 10.1016/j.apenergy.2025.125363.

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Abstract

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.

Type: Article
Title: Stochastic optimal design of integrated energy systems considering seismic hazards
DOI: 10.1016/j.apenergy.2025.125363
Publisher version: https://doi.org/10.1016/j.apenergy.2025.125363
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Seismic hazards, Low probability high impact, Fragility curves, Stochastic optimization, Monte Carlo
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources
URI: https://discovery.ucl.ac.uk/id/eprint/10204290
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