Pith Number

pith:ZR4X3IED

pith:2026:ZR4X3IEDBESABBL4DMT4E2SOZ4

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A Resilience Evaluation Framework for Electric Distribution Systems: Historical Weather Conditioning, Sensitivity Analysis, and a Flooding-Aware Extension

Amir Shahin Kamjou, Caisheng Wang, Carol Miller, John Norton, Xuesong Wang

An extended graph-based framework evaluates electric distribution resilience using historical wind events, sensitivity tests, and coupled flooding simulations.

arxiv:2605.16811 v1 · 2026-05-16 · eess.SY · cs.SY

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Claims

C1strongest claim

The framework provides a practical basis for resilience assessment, comparative scenario analysis, and coupled power-flooding studies in a limited public-data setting. Wind-event resilience metrics stabilize at approximately 256 episodes, outage metrics change systematically with fragility parameters and repair strategies, and episodes with at least one flooded customer occur in 1.9% of episodes with flood intensity increasing with outage intensity.

C2weakest assumption

The fragility functions, restoration assumptions, and repair strategies used in the Monte Carlo simulations accurately capture real-world component failure and recovery behavior under wind and flooding hazards. This premise is invoked when historical weather events drive the simulations and when sensitivity studies vary these modeling choices.

C3one line summary

Extended Monte Carlo simulation framework for electric distribution resilience using historical wind events, sensitivity analysis on modeling parameters, and coupled power-flooding assessment showing 1.9% flood episodes.

References

18 extracted · 18 resolved · 0 Pith anchors

[1] A. Younesi, H. Shayeghi, Z. Wang, P. Siano, A. Mehrizi-Sani, A. Safari, Trends in modern power systems resilience: State-of-the-art review, Re- newable and Sustainable Energy Reviews 162 (2022) 112397 2022

[2] J. Potts, H. R. Tiedmann, K. K. Stephens, K. M. Faust, S. Castellanos, Enhancing power system resilience to extreme weather events: A quali- tative assessment of winter storm uri, International Journa 2024

[3] C.Brelsford, S.Tennille, A.Myers, S.Chinthavali, V.Tansakul, M.Den- man, M. Coletti, J. Grant, S. Lee, K. Allen, et al., A dataset of recorded electricity outages by united states county 2014–2022, Sc 2014

[4] K. Oikonomou, K. Mongird, J. S. Rice, J. S. Homer, Resilience of inter- dependent water and power systems: A literature review and conceptual modeling framework, Water 13 (20) (2021) 2846 2021

[5] D. K. Mishra, M. J. Ghadi, A. Azizivahed, L. Li, J. Zhang, A review on resilience studies in active distribution systems, Renewable and Sus- tainable Energy Reviews 135 (2021) 110201. 18 2021

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Receipt and verification

First computed	2026-05-20T00:03:23.572274Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

cc797da083092400857c1b27c26a4ecf2fadf14c938f236126f99a128628f6d7

Aliases

arxiv: 2605.16811 · arxiv_version: 2605.16811v1 · doi: 10.48550/arxiv.2605.16811 · pith_short_12: ZR4X3IEDBESA · pith_short_16: ZR4X3IEDBESABBL4 · pith_short_8: ZR4X3IED

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curl -sH 'Accept: application/ld+json' https://pith.science/pith/ZR4X3IEDBESABBL4DMT4E2SOZ4 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: cc797da083092400857c1b27c26a4ecf2fadf14c938f236126f99a128628f6d7

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "6f290513ed6f2b9c698c0b2ab10e897cc8fd2dbe8087377bde49c02973c8a136",
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      "cs.SY"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "eess.SY",
    "submitted_at": "2026-05-16T04:59:35Z",
    "title_canon_sha256": "38dd704ae9840a4d8fe1fecf376d44c4634955bcc80843410a62b6b866a8cd81"
  },
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  "source": {
    "id": "2605.16811",
    "kind": "arxiv",
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}