A5040295886- Energy Load and Power Forecasting
- Nonlinear Dynamics and Pattern Formation
- Electric Power System Optimization
- Power System Optimization and Stability
- Complex Systems and Time Series Analysis
- Smart Grid Energy Management
- Migraine and Headache Studies
- Computational Physics and Python Applications
- Power Systems and Renewable Energy
- Hydrological Forecasting Using AI
- Psychosomatic Disorders and Their Treatments
- Complex Network Analysis Techniques
- Reservoir Engineering and Simulation Methods
- Smart Grid Security and Resilience
- Microgrid Control and Optimization
- Chaos control and synchronization
- Integrated Energy Systems Optimization
- Energy Efficiency and Management
- Market Dynamics and Volatility
- Power Systems and Technologies
- Climate variability and models
- Time Series Analysis and Forecasting
- Opinion Dynamics and Social Influence
- stochastic dynamics and bifurcation
- Explainable Artificial Intelligence (XAI)
Karlsruhe Institute of Technology
2015-2025
Migräne Klinik Königstein
2015-2024
Robert Bosch Hospital
2023
Queen Mary University of London
2019-2022
Norwegian University of Life Sciences
2021-2022
TU Dresden
2017-2022
HES-SO Valais-Wallis
2022
Carl von Ossietzky Universität Oldenburg
2022
Oldenburger Institut für Informatik
2022
University of Twente
2022
Reliable functioning of infrastructure networks is essential for our modern society. Cascading failures are the cause most large-scale network outages. Although cascading often exhibit dynamical transients, modeling cascades has so far mainly focused on analysis sequences steady states. In this article, we focus electrical transmission and introduce a framework that takes into account both event-based nature essentials dynamics. We find transients order seconds in flows power grid play...
Stable operation of complex flow and transportation networks requires balanced supply demand. For the electric power grids—due to their increasing fraction renewable energy sources—a pressing challenge is fit fluctuations in decentralized distributed temporally varying demands. To achieve this goal, common smart grid concepts suggest collect consumer demand data, centrally evaluate them given current send price information back customers for decide about usage. Besides restrictions regarding...
Abstract The dynamics of power consumption constitutes an essential building block for planning and operating sustainable energy systems. Whereas variations in the renewable generation are reasonably well studied, a deeper understanding is still missing. Here, we analyse highly resolved residential electricity data Austrian, German UK households propose generally applicable data-driven load model. Specifically, disentangle average demand profiles from fluctuations based purely on time series...
Electricity prices in liberalized markets are determined by the supply and demand for electric power, which turn driven various external influences that vary strongly time. In perfect competition, merit order principle describes dispatchable power plants enter market of their marginal costs to meet residual load, i.e. difference load renewable generation. Various models based on this when attempting predict electricity prices, yet is fraught with assumptions simplifications thus limited...
Stable operation of an electric power system requires strict operational limits for the grid frequency. Fluctuations and external impacts can cause large frequency deviations increased control efforts. Although these complex interdependencies be modeled using machine learning algorithms, black box character many models insights applicability. In this article, we introduce explainable model that accurately predicts stability indicators three European synchronous areas. Using Shapley additive...
Abstract A new era in developmental biology has been ushered by recent advances the quantitative imaging of all-cell morphogenesis living organisms. Here we have developed a light-sheet fluorescence microscopy-based framework with single-cell resolution for identification and characterization subtle phenotypical changes millimeter-sized Such comparative study requires analyses entire ensembles to be able distinguish sample-to-sample variations from definitive changes. We present kinetic...
Shifting our electricity generation from fossil fuel to renewable energy sources introduces large fluctuations the power system. Here, we demonstrate how increased fluctuations, reduced damping and intertia may undermine dynamical robustness of grid networks. Focusing on fundamental noise models, derive analytic insights into which factors limit dynamic induce a system escape an operating state. Moreover, identify weak links in that make it particularly vulnerable fluctuations. These results...
The energy system is rapidly changing to accommodate the increasing number of renewable generators and general transition towards a more sustainable future. Simultaneously, business models market designs evolve, affecting power-grid operation frequency. Problems raised by this ongoing are increasingly addressed transdisciplinary research approaches, ranging from purely mathematical modelling applied case studies. These approaches require stochastic description consumer behaviour,...
The ongoing energy transition requires power grid extensions to connect renewable generators consumers and transfer among distant areas. process of extension a large investment resources is supposed make operation more robust. Yet, counter-intuitively, increasing the capacity existing lines or adding new may also reduce overall system performance even promote blackouts due Braess' paradox. paradox was theoretically modeled but not yet proven in realistically scaled grids. Here, we present an...
Human activities alter river water quality and quantity, with consequences for the ecosystems of urbanised rivers. Quantifying role human-induced drivers in controlling spatio-temporal patterns is critical to develop successful strategies improving ecological health urban Here, we analyse high-frequency electrical conductivity temperature data collected from River Chess South-East England during a Citizen Science project. Utilizing machine learning, find that boosted trees outperform GAM...
The increasing penetration of renewable energy sources, characterised by low inertia and intermittent disturbances, presents substantial challenges to power system stability. As critical indicators stability, frequency dynamics associated oscillatory phenomena have attracted significant research attention. While existing studies predominantly employ linearized models, our findings demonstrate that linear approximations exhibit considerable errors when predicting oscillation across multiple...
Power grids are essential for our society, connecting consumers and generators. Their frequency stability is impacted by supply demand changes, including deterministic stochastic dynamics, e.g., from market activities or fluctuating renewables. The first two Kramers–Moyal coefficients allow a description of both the (via drift) diffusion) aspects these dynamics. Such understanding could be critical to stabilizing power systems. However, how drift diffusion differ between synchronous areas,...
Abstract The aviation industry is of great importance for a globally connected economy. Customer satisfaction with airlines and airport performance considerably influenced by how much flights are delayed. But should the delay be quantified thousands each airline? Here, we present statistical analysis arrival delays at several UK airports between 2018 2020. We establish procedure to compare both mean extreme events among airports, identifying power-law decay large delays. Furthermore, note...
Abstract Air pollution is one of the leading causes death globally, and continues to have a detrimental effect on our health. In light these impacts, an extensive range statistical modelling approaches has been devised in order better understand air statistics. However, time-varying statistics different types pollutants are far from being fully understood. The observed probability density functions (PDFs) concentrations depend very much spatial location pollutant substance. this paper, we...
Abstract In the smart grid of future, accurate load forecasts on level individual clients can help to balance supply and demand locally prevent outages. While number monitored will increase with ongoing meter rollout, amount data per client always be limited. We evaluate whether a Transformer forecasting model benefits from transfer learning strategy, where global univariate is trained time series multiple clients. experiments two datasets containing several hundred clients, we find that...
A reliable supply of electricity is critical for our modern society, and any large-scale disturbance the electrical system causes substantial costs. In 2015, one overloaded transmission line caused a cascading failure in Turkish power grid, affecting about 75×106 people. Here, we analyze grid its dynamical statistical properties. Specifically, propose, first time, model that incorporates properties complex network topology to investigate failures. We find damage depends on load generation...
The power grid frequency is the central observable in system control, as it measures balance of electrical supply and demand. A reliable forecast can facilitate rapid control actions may thus greatly improve stability. Here, we develop a weighted-nearest-neighbour (WNN) predictor to investigate how predictable trajectories are. Our forecasts for up one hour are more precise than averaged daily profiles could increase efficiency actions. Furthermore, gain an increased understanding specific...