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Spatial Risk Analysis of Power Systems Resilience During Extreme Events

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  • Dimitris N. Trakas
  • Mathaios Panteli
  • Nikos D. Hatziargyriou
  • Pierluigi Mancarella

Abstract

The increased frequency of extreme events in recent years highlights the emerging need for the development of methods that could contribute to the mitigation of the impact of such events on critical infrastructures, as well as boost their resilience against them. This article proposes an online spatial risk analysis capable of providing an indication of the evolving risk of power systems regions subject to extreme events. A Severity Risk Index (SRI) with the support of real‐time monitoring assesses the impact of the extreme events on the power system resilience, with application to the effect of windstorms on transmission networks. The index considers the spatial and temporal evolution of the extreme event, system operating conditions, and the degraded system performance during the event. SRI is based on probabilistic risk by condensing the probability and impact of possible failure scenarios while the event is spatially moving across a power system. Due to the large number of possible failures during an extreme event, a scenario generation and reduction algorithm is applied in order to reduce the computation time. SRI provides the operator with a probabilistic assessment that could lead to effective resilience‐based decisions for risk mitigation. The IEEE 24‐bus Reliability Test System has been used to demonstrate the effectiveness of the proposed online risk analysis, which was embedded in a sequential Monte Carlo simulation for capturing the spatiotemporal effects of extreme events and evaluating the effectiveness of the proposed method.

Suggested Citation

  • Dimitris N. Trakas & Mathaios Panteli & Nikos D. Hatziargyriou & Pierluigi Mancarella, 2019. "Spatial Risk Analysis of Power Systems Resilience During Extreme Events," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 195-211, January.
    • Handle: RePEc:wly:riskan:v:39:y:2019:i:1:p:195-211
    DOI: 10.1111/risa.13220
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    Cited by:

    1. Mishra, Dillip Kumar & Ghadi, Mojtaba Jabbari & Li, Li & Zhang, Jiangfeng & Hossain, M.J., 2022. "Active distribution system resilience quantification and enhancement through multi-microgrid and mobile energy storage," Applied Energy, Elsevier, vol. 311(C).
    2. Hou, Hui & Tang, Junyi & Zhang, Zhiwei & Wang, Zhuo & Wei, Ruizeng & Wang, Lei & He, Huan & Wu, Xixiu, 2023. "Resilience enhancement of distribution network under typhoon disaster based on two-stage stochastic programming," Applied Energy, Elsevier, vol. 338(C).
    3. Habibollah Raoufi & Vahid Vahidinasab & Kamyar Mehran, 2020. "Power Systems Resilience Metrics: A Comprehensive Review of Challenges and Outlook," Sustainability, MDPI, vol. 12(22), pages 1-24, November.
    4. Hossain, Eklas & Roy, Shidhartho & Mohammad, Naeem & Nawar, Nafiu & Dipta, Debopriya Roy, 2021. "Metrics and enhancement strategies for grid resilience and reliability during natural disasters," Applied Energy, Elsevier, vol. 290(C).
    5. Minhui Qian & Ning Chen & Yuge Chen & Changming Chen & Weiqiang Qiu & Dawei Zhao & Zhenzhi Lin, 2021. "Optimal Coordinated Dispatching Strategy of Multi-Sources Power System with Wind, Hydro and Thermal Power Based on CVaR in Typhoon Environment," Energies, MDPI, vol. 14(13), pages 1-35, June.
    6. Nikolaos Argyris & Valentina Ferretti & Simon French & Seth Guikema & Gilberto Montibeller, 2019. "Advances in Spatial Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 1-8, January.
    7. Younesi, Abdollah & Shayeghi, Hossein & Safari, Amin & Siano, Pierluigi, 2020. "Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation," Energy, Elsevier, vol. 207(C).
    8. Umunnakwe, A. & Huang, H. & Oikonomou, K. & Davis, K.R., 2021. "Quantitative analysis of power systems resilience: Standardization, categorizations, and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).

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