A two-stage decision-making approach for optimal design and operation of integrated energy systems considering multiple uncertainties and diverse resilience needs

Hang Lv, Qiong Wu, Hongbo Ren, Qifen Li and Weisheng Zhou

Energy, 2024, vol. 305, issue C

Abstract: The enhancement of energy system resilience from a planning perspective is crucial. In this study, a two-stage resilience optimization model is developed to determine the optimal additional configuration and scheduling plan for an integrated energy system, taking into account economic costs, loss of load, and various resilience indicators. Considering the uncertainty of disaster occurrence and component vulnerability, probabilities of multiple energy interruption scenarios are introduced, and a comprehensive system configuration optimization model targeting annual energy supply cost and loss of load is developed. Following which, accounting for the personalized energy demands of end-users, three resilience indicators, namely load importance, energy interruption duration, and the maximum degree of system damage, are proposed. According to the simulation results of an illustrative example, the proposed method effectively improve system resilience. Compared to the baseline solution from pure economic perspective, the total cost increases by 0.38 %, while the load loss decreases by 6.84 %. From the demand-side viewpoints, three resilience indicators are improved by 12.17 %, 11.8 %, and 20 %, respectively. Moreover, the capacity of renewable energy is recognized as the most critical factor determining the load loss over the planning period. Storage devices are more beneficial in reducing the duration of energy interruptions and lowering the maximum damage degree.

Keywords: Integrated energy system; Multiple uncertainties; Diversified resilience needs; Two-stage optimization; Extreme natural disaster (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:305:y:2024:i:c:s0360544224021492

DOI: 10.1016/j.energy.2024.132375

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