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Solving Distribution Grid State-Estimation to Near-zero Optimality Gap

Panthee, Bikram
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Abstract
Distributed energy resources and active networks require a highly accurate Distribution Grid State Estimation (DGSE). Traditional methods often fail because the power flow equations are non-convex, meaning solvers can get stuck in "local minima" and provide incorrect grid states. This paper introduces a new framework that solves the DGSE problem with a near-zero optimality gap. We reformulate the standard non-convex state estimation problem into an exact bilinear program (BLP) using an equivalent circuit formulation. To find the global solution, we use a spatial branch-and-bound (sB&B) algorithm. We also develop a Sequential Bound Tightening (SBT) routine that uses variable filtering and decomposition to speed up the process. This routine tightens the bounds on state variables, allowing the solver to converge faster on large-scale systems.
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Date
1/1/2026
Student Status
Graduate Student
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Type of presentation
Poster
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UVM Student Research Conference
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URI
https://hdl.handle.net/20.500.14849/10336
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Advisor(s)
Amritanshu Pandey
Department
Program/Major
Electrical Engineering
College/School
College of Engineering and Mathematical Sciences
Organization
Research Category
Engineering
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