22 citations · 61 across the 6 of their papers we have counts for
6 papers
Inductive biases in deep learning models for weather prediction
Jannik Thuemmel, Matthias Karlbauer, Sebastian Otte +8
Deep learning has gained immense popularity in the Earth sciences as it enables us to formulate purely data-driven models of complex Earth system processes. Deep learning-based wea…
Analytical Uncertainty Propagation for Multi-Period Stochastic Optimal Power Flow
Rebecca Bauer, Tillmann Mühlpfordt, Nicole Ludwig +1
The increase in renewable energy sources (RESs), like wind or solar power, results in growinguncertainty also in transmission grids. This affects grid stability through fluctuating…
Analytical Uncertainty Propagation for Multi-Period Stochastic Optimal Power Flow
Rebecca Bauer, Tillmann Mühlpfordt, Nicole Ludwig +1
The increase in renewable energy sources (RESs), like wind or solar power, results in growing uncertainty also in transmission grids. This affects grid stability through fluctuatin…
A Collection and Categorization of Open-Source Wind and Wind Power Datasets
Nina Effenberger, Nicole Ludwig
Wind power and other forms of renewable energy sources play an ever more important role in the energy supply of today's power grids. Forecasting renewable energy sources has theref…
pyWATTS: Python Workflow Automation Tool for Time Series
Benedikt Heidrich, Andreas Bartschat, Marian Turowski +7
Time series data are fundamental for a variety of applications, ranging from financial markets to energy systems. Due to their importance, the number and complexity of tools and me…
Evaluating Ensemble Post-Processing for Wind Power Forecasts
Kaleb Phipps, Sebastian Lerch, Maria Andersson +3
Capturing the uncertainty in probabilistic wind power forecasts is challenging, especially when uncertain input variables, such as the weather, play a role. Since ensemble weather…