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Jan Meyer

Publications and source records attributed to Jan Meyer.

8 recordsLinked to original sources
arXiv2026

Identification and Visualization of Correlation Structures in Large-Scale Power Quality Data

Large-scale power quality (PQ) measurement campaigns generate vast amounts of multivariate data, in which systematic dependencies are difficult to identify using conventional analysis techniques. This paper presents a methodology for the automated analysis and visualization of correlation structures in large PQ datasets. Building on an existing framework, the approach is adapted for shorter observation periods and enhanced with aggregation and distance-based visualization techniques. Daily Spearman correlation coefficients are averaged via Fishers z-transformation and aggregated across phases, parameters, and sites. The resulting correlation structures are visualized using hierarchical clustering and multidimensional scaling to reveal consistent and recurring relationships. The methodology is demonstrated using data from 85 measurement sites within the German transmission system.

eess.SP↗
arXiv2026

Ensemble Forecasting of Power Quality Parameters

The growing integration of power electronic-based technologies has increased the necessity of power quality (PQ) monitoring in transmission systems. Although large datasets are collected by operators, their use is typically limited to compliance assessment. Medium- to long-term forecasting can enhance the value of these datasets by enabling proactive asset management and trend detection, despite challenges related to data heterogeneity and seasonality. This paper systematically evaluates individual and ensemble forecasting approaches for PQ parameters in transmission systems. More than 700 weekly time series from measurement campaigns in Germany and Estonia are analysed to assess various models and aggregation strategies within a structured ensemble framework. The results show that ensemble forecasts consistently outperform individual models in terms of accuracy and robustness, achieving significant improvements over seasonal naive benchmarks and the best-performing single models. Ensemble forecasting is therefore confirmed as a robust and scalable approach for long-term PQ prediction in transmission systems.

eess.SP↗
arXiv2025

3D atomic structure determination with ultrashort-pulse MeV electron diffraction

Understanding structure at the atomic scale is fundamental for the development of materials with improved properties. Compared to other probes providing atomic resolution, electrons offer the strongest interaction in combination with minimal radiation damage. Here, we report the successful implementation of MeV electron diffraction for ab initio 3D structure determination at atomic resolution. Using ultrashort electron pulses from the REGAE accelerator, we obtained high-quality diffraction data from muscovite and $1T-TaS_2$, enabling structure refinements according to the dynamical scattering theory and the accurate determination of hydrogen atom positions. The increased penetration depth of MeV electrons allows for structure determination from samples significantly thicker than those typically applicable in electron diffraction. These findings establish MeV electron diffraction as a viable approach for investigating a broad range of materials, including nanostructures and radiation-sensitive compounds, and open up new opportunities for in-situ and time-resolved experiments.

cond-mat.mtrl-sci↗
arXiv2025

Generalised Harmonic Domain Analysis for Transformer Core Hysteresis Modelling

This work identifies the general approach for linearising any power system component in the harmonic domain, that is with respect to its Fourier series coefficients. This ability enables detailed harmonic analysis, and is key as more power electronic devices inject harmonic currents into the power system to its shared detriment. The general approach requires a time domain model of the component, and is most applicable where a conversion to the frequency domain is impractical prior to linearisation. The outcome is a Norton equivalent current source, which expresses linear coupling between harmonic frequencies with admittance matrices. These are the so-called frequency coupling matrices. The general approach is demonstrated for magnetic hysteresis, where a Preisach model has been developed for this purpose. A new data driven approach is used to fit the test results of a small physical transformer to the Preisach model. Results show an improved accuracy in the frequency coupling matrices over models that only considered magnetic saturation. Maximum improvement is observed in the odd harmonic current to odd harmonic voltage couplings.

eess.SY↗
arXiv2024

Deterministic and stochastic aspects of current-induced magnetization reversal in perpendicular nanomagnets

We study the incubation and transition times that characterize the magnetization switching induced by spin-orbit torques in nanomagnets with perpendicular anisotropy. We present a phenomenological model to interpret the dependence of the incubation time on the amplitude of the voltage pulse and assisting magnetic field and estimate the volume of the seed domain that triggers the switching. Our measurements evidence a correlation between the incubation and transition times that is mediated by the temperature variation during the electric pulse. In addition, we discuss the stochastic distributions of the two times in terms of the energy barriers opposing the nucleation and expansion of the seed domain. We propose two models based on the log-normal and gamma functions to account for the different origin of the variability of the incubation and transition times, which are associated with a single nucleation barrier and multiple pinning sites, respectively.

cond-mat.mes-hall↗
arXiv2023

Data-Driven Modelling for Harmonic Current Emission in Low-Voltage Grid Using MCReSANet with Interpretability Analysis

Even though the use of power electronics PE loads offers enhanced electrical energy conversion efficiency and control, they remain the primary sources of harmonics in grids. When diverse loads are connected in the distribution system, their interactions complicate establishing analytical models for the relationship between harmonic voltages and currents. To solve this, our paper presents a data-driven model using MCReSANet to construct the highly nonlinear between harmonic voltage and current. Two datasets from PCCs in Finland and Germany are utilized, which demonstrates that MCReSANet is capable of establishing accurate nonlinear mappings, even in the presence of various network characteristics for selected Finland and Germany datasets. The model built by MCReSANet can improve the MAE by 10% and 14% compared to the CNN, and by 8% and 17% compared to the MLP for both Finnish and German datasets, also showing much lower model uncertainty than others. This is a crucial prerequisite for more precise SHAP value-based feature importance analysis, which is a method for the model interpretability analysis in this paper. The results by feature importance analysis show the detailed relationships between each order of harmonic voltage and current in the distribution system. There is an interactive impact on each order of harmonic current, but some orders of harmonic voltages have a dominant influence on harmonic current emissions: positive sequence and zero sequence harmonics have the dominant importance in the Finnish and German networks, respectively, which conforms to the pattern of connected load types in two selected Finnish and German datasets. This paper enhances the potential for understanding and predicting harmonic current emissions by diverse PE loads in distribution systems, which is beneficial to more effective management for optimizing power quality in diverse grid environments.

eess.SY↗
arXiv2014

Rolling, sliding & torsion of micron-sized silica particles - Experimental, numerical and theoretical analysis

The contact mechanics of individual, very small particles with other particles and walls is studied using a nanoindenter setup that allows normal and lateral displacement control and measurement of the respective forces. The sliding, rolling and torsional forces and torques are tested with borosilicate microspheres, featuring radii of about 10$μ$m. The contacts are with flat silicon substrates of different roughness for pure sliding and rolling and with silicon based, ion-beam crafted rail systems for combined rolling and torsion. The experimental results are discussed and compared to various analytical predictions and contact models, allowing for two concurrent interpretations of the effects of surface roughness, plasticity and adhesion. This enables us to determine both rolling and torsion friction coefficients together with their associated length scales. Interestingly, even though normal contacts behave elastically (Hertzian), all other modes of motion display effects due to surface roughness and consequent plastic deformation. The influence of adhesion is interpreted in the framework of different models and is very different for different degrees of freedom, being largest for rolling.

cond-mat.mtrl-sci↗