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The paper proposes a Quadratic Unconstrained Binary Optimization (QUBO) formulation in a bipartite power grid fault location problem using sparse measurements. The sparse approximation problem consists of solving an underdetermined system of complex-valued equations. Through enforcement of the grid-depending sparsity of the problem, the amount of quantum bits necessary to solve the system is reduced, opening possibilities for industrial, large grid applications with lowered computational cost.

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QUBO Formulation for Fault Location on Power Grid with Sparse Measurements

  • 会议论文

  • 发表日期：

    2026年

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  • Eloi Gravot,
  • Beatriz Moya,
  • Sergio Torregrosa,
  • Nicolas Hascöet,
  • Xavier Kestelyn,
  • Francisco Chinesta,
  • Fikri Hafid,
  • Paul-Henri Langlois

摘要

The paper proposes a Quadratic Unconstrained Binary Optimization (QUBO) formulation in a bipartite power grid fault location problem using sparse measurements. The sparse approximation problem consists of solving an underdetermined system of complex-valued equations. Through enforcement of the grid-depending sparsity of the problem, the amount of quantum bits necessary to solve the system is reduced, opening possibilities for industrial, large grid applications with lowered computational cost.