5 citations · 9 across the 15 of their papers we have counts for
4 papers · 1 filter
Physics-inspired machine learning for power grid frequency modelling
Johannes Kruse, Eike Cramer, Benjamin Schäfer +1
The operation of power systems is affected by diverse technical, economic and social factors. Social behaviour determines load patterns, electricity markets regulate the generation…
Multivariate Probabilistic Forecasting of Intraday Electricity Prices using Normalizing Flows
Eike Cramer, Dirk Witthaut, Alexander Mitsos +1
Electricity is traded on various markets with different time horizons and regulations. Short-term intraday trading becomes increasingly important due to the higher penetration of r…
Normalizing Flow-based Day-Ahead Wind Power Scenario Generation for Profitable and Reliable Delivery Commitments by Wind Farm Operators
Eike Cramer, Leonard Paeleke, Alexander Mitsos +1
We present a specialized scenario generation method that utilizes forecast information to generate scenarios for day-ahead scheduling problems. In particular, we use normalizing fl…
Nonlinear Isometric Manifold Learning for Injective Normalizing Flows
Eike Cramer, Felix Rauh, Alexander Mitsos +2
To model manifold data using normalizing flows, we employ isometric autoencoders to design embeddings with explicit inverses that do not distort the probability distribution. Using…