{
  "abstract": "Probabilistic voltage assessment under multiple contingencies involves numerous network topologies and uncertain operating conditions, resulting in substantial surrogate modeling and computational costs. To address this problem, this paper proposes a voltage-increment-based low-rank (LR) representation with polynomial chaos expansion (PCE), denoted as LR-PCE-ΔV, for a unified multi-contingency voltage assessment. For each model-construction realization, the voltage increment ΔV is calculated as the difference between the post-contingency and pre-contingency bus voltages. The voltage increments under all contingencies are then stacked to form a joint multi-contingency voltage-increment response matrix. Singular value decomposition (SVD) is applied to extract the dominant modes, and one PCE surrogate is constructed for the coefficient of each retained mode. For a new input realization, the predicted modal coefficients are used to reconstruct the voltage increments under all contingencies, after which the corresponding pre-contingency voltages are added to recover the post-contingency voltages. The method is verified on the IEEE 118-bus system with 231 N − 1 contingencies against conventional Monte Carlo simulation (MCS), comprising the pre-contingency AC optimal power flow (ACOPF) and post-contingency AC power flow calculations (ACPF). The proposed method reduces the number of required PCE surrogates from 231 to 21. Compared with the corresponding low-rank model constructed directly from the post-contingency voltages, it reduces the RMSE by 85.9% and achieves a 7.7-fold speedup over conventional MCS while accurately reproducing voltage distributions.",
  "abstract_shown": true,
  "affiliations": [
    "State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University, Chongqing 401331, China",
    "State Grid Gansu Electric Power Research Institute, Lanzhou 730070, China"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Yuzhi Wang"
    },
    {
      "affs": [
        0
      ],
      "name": "Xingyu Lin",
      "orcid": "0000-0002-7713-5208"
    },
    {
      "affs": [
        0
      ],
      "name": "Junzhou Wang"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Liu Zhu"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Chen Liang"
    },
    {
      "affs": [
        0
      ],
      "name": "Junjie Tang",
      "orcid": "0000-0003-3066-3211"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/f6hxy7wa6f1jp.bib",
  "cited_by": 0,
  "doi": "10.3390/math14193576",
  "fulltext_url": null,
  "id": "f6hxy7wa6f1jp",
  "issns": [
    "2227-7390"
  ],
  "landing_url": "https://www.mdpi.com/2227-7390/14/19/3576",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2208|Optimal Power Flow Distribution"
    ]
  ],
  "openalex": "W7215979264",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-02",
  "publisher": "MDPI AG",
  "ris": "https://research.draconitic.com/paper/f6hxy7wa6f1jp.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:29Z",
      "native_id": "10.3390/math14193576",
      "source": "crossref",
      "url": "https://www.mdpi.com/2227-7390/14/19/3576"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "issn:2227-7390",
      "subfield": "general"
    }
  ],
  "title": "Voltage-Increment-Based Low-Rank Representation with Polynomial Chaos Expansions for Probabilistic Voltage Assessment Under Multiple Contingencies",
  "title_text": "Voltage-Increment-Based Low-Rank Representation with Polynomial Chaos Expansions for Probabilistic Voltage Assessment Under Multiple Contingencies",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:29Z",
  "url": "https://research.draconitic.com/paper/f6hxy7wa6f1jp",
  "venue": "Mathematics",
  "versions": []
}