{
  "abstract": "This article presents a data-driven approach to minimally adjust forecast-based steady-state generation dispatch in electrical transmission networks. The goal is to manage congestion caused by uncertainty in demand and renewable generation under a fixed automatic generation control (AGC) policy operating without saturation. Under this policy, we first show that the post-AGC residual injection distribution is invariant to the scheduled generation dispatch. This result separates line loading into a dispatch-dependent baseline and an uncertainty-induced residual component. Using historical forecast errors, we then apply split conformal prediction to construct transmission-line margins with distribution-free, finite-sample linewise or joint coverage guarantees. We also calibrate the aggregate pre-AGC mismatch to determine the generation headroom required for the prescribed AGC response. We incorporate these calibrated quantities into a convex secure re-dispatch problem that minimally adjusts the nominal schedule while reserving sufficient transmission capacity and AGC headroom. The resulting corrected dispatch provides finite-sample probabilistic guarantees on per-line security and unsaturated AGC operation. Case studies on the RTS-GMLC system demonstrate substantial reductions in out-of-sample line-limit violations with modest operating-cost increases.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.11823",
  "author_total": 3,
  "authors": [
    {
      "name": "Sushanth Balaraman"
    },
    {
      "name": "Shriram Srinivasan"
    },
    {
      "name": "Kaarthik Sundar"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4mfh92f7gk6ax.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.11823",
  "fulltext_url": null,
  "id": "4mfh92f7gk6ax",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.11823",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "math.OC"
    ],
    [
      "openalex",
      "2208|Electric Power System Optimization"
    ]
  ],
  "openalex": "W7212239908",
  "pdf_url": "https://arxiv.org/pdf/2609.11823",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-16",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/4mfh92f7gk6ax.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:22:04Z",
      "native_id": "2609.11823",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.11823"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.OC",
      "subfield": "optimisation-control"
    }
  ],
  "title": "Conformal Margins for Electrical Transmission Capacity Under Fixed Balancing Policies",
  "title_text": "Conformal Margins for Electrical Transmission Capacity Under Fixed Balancing Policies",
  "type": "preprint",
  "updated_at": "2026-10-30T12:22:04Z",
  "url": "https://research.draconitic.com/paper/4mfh92f7gk6ax",
  "venue": "arXiv",
  "versions": []
}