{
  "abstract": "In a series of three papers, we propose a distributed intraday scenario planner for energy management in 16.7-Hz single-phase railway power systems, which is realized and tested as open-source Python package \\texttt{bahnstrom\\_ems v0.9.1}~\\cite{noroozi2026bahnstromems}. The first part of our work develops the mathematical foundation of a two-layer energy management system for a 16.7-Hz single-phase railway power network, where the network is an interconnection of several control areas. Given a day-ahead plan, last measurement of stored energy in wayside batteries, and forecasts of the tractive, available regenerative and renewable energy, we provide a mathematical modeling of the 16.7-Hz single-phase railway power network in intraday time-scale. Then the intraday energy planning is formulated as a risk-neutral convex stochastic optimization problem. The overall intraday planning is shown to be a sparse convex quadratic program. Hence, this problem is solved recursively by adopting a distributed scenario model predictive control (MPC) setting. The corresponding area problems, coordination updates, convergence conditions, and closed-loop key-performance-index accumulation are derived. In practice, detailed train-motion and microscopic motoring and regenerative-power profiles are usually needed for accurate simulations and numerical validation purposes. Due to data privacy and security concerns, detailed train-motion and microscopic motoring and regenerative-power profiles in a real power network may not be publicly available. Therefore, we also propose a mathematically-solid approach to estimate such microscopic information by converting causally timetable and train-motion information into quarter-hour motoring and regenerative-power profiles while exactly preserving each hourly energy target.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.21808",
  "author_total": 1,
  "authors": [
    {
      "name": "Navid Noroozi"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9x2dk52s0y44y.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.21808",
  "fulltext_url": null,
  "id": "9x2dk52s0y44y",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.21808",
  "language": null,
  "licence": "CC-BY-SA-4.0",
  "licence_label": "CC BY-SA 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by-sa/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "math.OC"
    ],
    [
      "openalex",
      "2209|Railway Systems and Energy Efficiency"
    ]
  ],
  "openalex": "W7213879674",
  "pdf_url": "https://arxiv.org/pdf/2609.21808",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-18",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/9x2dk52s0y44y.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:23:07Z",
      "native_id": "2609.21808",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.21808"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.OC",
      "subfield": "optimisation-control"
    }
  ],
  "title": "Distributed Intraday Energy Management for 16.7-Hz Railway Power Systems---Part I: Theoretical Foundations",
  "title_text": "Distributed Intraday Energy Management for 16.7-Hz Railway Power Systems---Part I: Theoretical Foundations",
  "type": "preprint",
  "updated_at": "2026-10-30T12:23:07Z",
  "url": "https://research.draconitic.com/paper/9x2dk52s0y44y",
  "venue": "arXiv",
  "versions": []
}