Optimisation algorithm for under-determined grid state calculations in distribution grids

The transition in energy systems from conventional, centralized power plants to distributed, renewable energy resources leads to challenges in the grids of the medium and low voltage levels. A wide-range integration of measurement and automation technology is cost-technically not feasible, but necessary for using conventional State Estimation algorithms. In this paper, an algorithm based on the Optimal Power Flow is presented, which determines the complex grid state vector by using a minimal amount of measurements. This approach has been shown robust grid state calculations with high estimation quality, without relying on pseudo-measurements, grid reduction methods, or artificial training.

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Published
2025-06-29
DOI
https://doi.org/10.1109/powertech59965.2025.11180604
Primary Topic
Power Systems and Technologies
Type
article
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article

Optimisation algorithm for under-determined grid state calculations in distribution grids

Dominik Hilbrich, Christian Rehtanz, Sebastian Raczka
Power Systems and Technologies
article

Optimisation algorithm for under-determined grid state calculations in distribution grids

Dominik Hilbrich, Christian Rehtanz, Sebastian Raczka
article en

Abstract

The transition in energy systems from conventional, centralized power plants to distributed, renewable energy resources leads to challenges in the grids of the medium and low voltage levels. A wide-range integration of measurement and automation technology is cost-technically not feasible, but necessary for using conventional State Estimation algorithms. In this paper, an algorithm based on the Optimal Power Flow is presented, which determines the complex grid state vector by using a minimal amount of measurements. This approach has been shown robust grid state calculations with high estimation quality, without relying on pseudo-measurements, grid reduction methods, or artificial training.

TU Dortmund University (DE), Fraunhofer Institute for Energy Economics and Energy System Technology (DE)
Openalex Percentile: Top 72%
Power Systems and Technologies
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