arXiv subjects

Werner van Westering

Publications and source records attributed to Werner van Westering.

2 recordsLinked to original sources

arXiv2026

Quantum Resource Estimation for Minimising Energy Grid Losses

Distribution network reconfiguration (DNR) can minimise power losses by identifying the optimal topology of the electricity grid. Determining the minimum loss configuration is NP-hard, and classical optimisation methods struggle to scale to real-world distribution grids. This paper explores the use of gate-based quantum computing to solve DNR for power loss reduction. We formulate DNR as a higher-order unconstrained binary optimisation (HUBO) problem, avoiding the need for auxiliary variables, thereby reducing the required number of qubits. This is applied to a real medium voltage (MV) network operated by Alliander, a Dutch distribution system operator (DSO). For each biconnected component in the network graph, we construct the corresponding HUBO, derive the cost and mixer operators, and determine the number of required logical qubits and rotation gates. These are then mapped to physical qubits and execution time estimates using quantum resource estimation (QRE). The results suggest that the quantum resource requirements depend not only on component size but also on structural characteristics such as connectivity and cyclicity. Overall, the novelty of this work lies in directly framing the optimisation problem as a HUBO, applying it to real-world MV networks, and performing a QRE to assess future feasibility.

quant-ph↗

arXiv2018

Linear Single- and Three-Phase Voltage Forecasting and Bayesian State Estimation with Limited Sensing

Implementing state estimation in low and medium voltage power distribution is still challenging given the scale of many networks and the reliance of traditional methods on a large number of measurements. This paper proposes a method to improve voltage predictions in real-time by leveraging a limited set of real-time measurements. The method relies on Bayesian estimation formulated as a linear least squares estimation problem, which resembles the classical weighted least-squares (WLS) approach for scenarios where full network observability is not available. We build on recently developed linear approximations for unbalanced three-phase power flow to construct voltage predictions as a linear mapping of load predictions constructed with Gaussian processes. The estimation step to update the voltage forecasts in real-time is a linear computation allowing fast high-resolution state estimate updates. The uncertainty in forecasts can be determined a priori and smoothed a posteriori, making the method useful for both planning, operation and post-hoc analysis. The method outperforms conventional WLS and is applied to different test feeders and validated on a real test feeder with the utility Alliander in The Netherlands.

eess.SY↗