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Power distribution network reconfiguration for distributed generation maximization

Sou, Kin Cheong LU ; Malmer, Gabriel LU orcid ; Thorin, Lovisa and Samuelsson, Olof LU (2026) In Electric Power Systems Research 255.
Abstract
Network reconfiguration can significantly increase the hosting capacity (HC) for distributed generation (DG) in radially operated systems, thereby reducing the need for costly infrastructure upgrades. However, when the objective is DG maximization, jointly optimizing topology and power dispatch remains computationally challenging. Existing approaches often rely on relaxations or approximations, yet we provide counterexamples showing that interior point methods, linearized DistFlow and second-order cone relaxations all yield erroneous results. To overcome this, we propose a solution framework based on the exact DistFlow equations, formulated as a bilinear program and solved using spatial branch-and-bound (SBB). Numerical studies on standard... (More)
Network reconfiguration can significantly increase the hosting capacity (HC) for distributed generation (DG) in radially operated systems, thereby reducing the need for costly infrastructure upgrades. However, when the objective is DG maximization, jointly optimizing topology and power dispatch remains computationally challenging. Existing approaches often rely on relaxations or approximations, yet we provide counterexamples showing that interior point methods, linearized DistFlow and second-order cone relaxations all yield erroneous results. To overcome this, we propose a solution framework based on the exact DistFlow equations, formulated as a bilinear program and solved using spatial branch-and-bound (SBB). Numerical studies on standard benchmarks and a 533-bus real-world system demonstrate that our proposed method reliably performs reconfiguration and dispatch within time frames compatible with real time operation. (Less)
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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Power distribution systems, Optimal power flow, Network reconfiguration, Distributed generation maximization
in
Electric Power Systems Research
volume
255
article number
112779
pages
11 pages
publisher
Elsevier
ISSN
1873-2046
DOI
10.1016/j.epsr.2026.112779
language
English
LU publication?
yes
id
b819e177-d8ce-4163-88ba-3a1a047be41f
date added to LUP
2026-02-02 13:50:14
date last changed
2026-02-06 09:15:13
@article{b819e177-d8ce-4163-88ba-3a1a047be41f,
  abstract     = {{Network reconfiguration can significantly increase the hosting capacity (HC) for distributed generation (DG) in radially operated systems, thereby reducing the need for costly infrastructure upgrades. However, when the objective is DG maximization, jointly optimizing topology and power dispatch remains computationally challenging. Existing approaches often rely on relaxations or approximations, yet we provide counterexamples showing that interior point methods, linearized DistFlow and second-order cone relaxations all yield erroneous results. To overcome this, we propose a solution framework based on the exact DistFlow equations, formulated as a bilinear program and solved using spatial branch-and-bound (SBB). Numerical studies on standard benchmarks and a 533-bus real-world system demonstrate that our proposed method reliably performs reconfiguration and dispatch within time frames compatible with real time operation.}},
  author       = {{Sou, Kin Cheong and Malmer, Gabriel and Thorin, Lovisa and Samuelsson, Olof}},
  issn         = {{1873-2046}},
  keywords     = {{Power distribution systems; Optimal power flow; Network reconfiguration; Distributed generation maximization}},
  language     = {{eng}},
  month        = {{01}},
  publisher    = {{Elsevier}},
  series       = {{Electric Power Systems Research}},
  title        = {{Power distribution network reconfiguration for distributed generation maximization}},
  url          = {{http://dx.doi.org/10.1016/j.epsr.2026.112779}},
  doi          = {{10.1016/j.epsr.2026.112779}},
  volume       = {{255}},
  year         = {{2026}},
}