{
  "id": "1711.07853",
  "version": "v1",
  "published": "2017-11-21T15:50:22.000Z",
  "updated": "2017-11-21T15:50:22.000Z",
  "title": "Accurate Semidefinite Programming Models for Optimal Power Flow in Distribution Systems",
  "authors": [
    "Zeyu Wang",
    "Daniel S. Kirschen",
    "Baosen Zhang"
  ],
  "categories": [
    "math.OC"
  ],
  "abstract": "In this paper, we develop semidefinite programming (SDP) models aimed at solving optimal power flow (OPF) problems in distribution systems. We propose two models: the symmetrical SDP model which modifies the existing BFM-SDP model. Then based on the symmetrical SDP model, we develop a voltage regulation model that solves OPF problems with binding voltage constraints. To evaluate the accuracy of our proposed OPF models, we rely on OpenDSS, a power flow solver, to generate power flow solutions as the benchmarks. Comprehensive case studies are conducted showing our SDP models have better numerical stability and yield more accurate results than existing approaches",
  "revisions": [
    {
      "version": "v1",
      "updated": "2017-11-21T15:50:22.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "accurate semidefinite programming models",
      "distribution systems",
      "symmetrical sdp model",
      "generate power flow solutions",
      "solving optimal power flow"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}