Modeling and evaluating nodal resilience of multi-energy systems under windstorms
Minglei Bao,
Yi Ding,
Maosheng Sang,
Daqing Li,
Changzheng Shao and
Jinyue Yan
Applied Energy, 2020, vol. 270, issue C, No S0306261920306486
Abstract:
With the growing frequency and extent of extreme weather events, the resilient operation of multi-energy systems (MESs) has drawn attention nowadays. However, there is little study on the methodology with a set of key indicators to quantify the resilience of MESs with the consideration of the impacts of extreme weather. To address the problem, this paper proposes a framework to evaluate the time-dependent resilience of MESs considering energy interactions during extreme weather events, such as windstorms. Firstly, the multi-phase performance curve is utilized to describe the response behavior of MESs at different phases under the impacts of windstorms. Secondly, a service-based optimal energy flow model is developed to minimize the consequences caused by windstorms through the coordination among different energy subsystems. In order to model the chaotic failures and restoration of components, the Monte-Carlo simulation technique is applied. Furthermore, nodal resilience metrics for different energy carriers are proposed to quantify the resilience in MESs. Numerical studies demonstrate the capability of the proposed technique to quantify the resilience of MESs under windstorms. The results show that the resilience performance level of MESs can differ in different regions with the impacts of windstorms. The findings can provide a useful reference for system operators to constitute targeted resilience improvement measures.
Keywords: Multi-energy systems; Windstorms; Optimal energy flow model; Nodal resilience; Monte-Carlo simulation method (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (24)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:270:y:2020:i:c:s0306261920306486
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DOI: 10.1016/j.apenergy.2020.115136
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