Nicole Ludwig

According to our database, Nicole Ludwig authored at least 25 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Towards turbine-location-aware multi-decadal wind power predictions with CMIP6.

Nina Effenberger, Nicole Ludwig

CoRR, 2024

2023

Probabilistic load forecasting using post-processed weather ensemble predictions.

Nicole Ludwig, Siddharth Arora, James W. Taylor

J. Oper. Res. Soc., March, 2023

Using weather data in energy time series forecasting: the benefit of input data transformations.

Oliver Neumann, Marian Turowski, Ralf Mikut, Veit Hagenmeyer, Nicole Ludwig

Energy Inform., January, 2023

Inductive biases in deep learning models for weather prediction.

Jannik Thümmel, Matthias Karlbauer, Sebastian Otte, Christiane Zarfl, Georg Martius, Nicole Ludwig, Thomas Scholten, Ulrich Friedrich, Volker Wulfmeyer, Bedartha Goswami, Martin V. Butz

CoRR, 2023

2022

Sizing of Hybrid Energy Storage Systems Using Recurring Daily Patterns.

Shahab Karrari, Nicole Ludwig, Giovanni De Carne, Mathias Noe

IEEE Trans. Smart Grid, 2022

Net load forecasting using different aggregation levels.

Maximilian Beichter, Kaleb Phipps, Martha Maria Frysztacki, Ralf Mikut, Veit Hagenmeyer, Nicole Ludwig

Energy Inform., 2022

Analytical Uncertainty Propagation for Multi-Period Stochastic Optimal Power Flow.

Rebecca Bauer, Tillmann Mühlpfordt, Nicole Ludwig, Veit Hagenmeyer

CoRR, 2022

A Collection and Categorization of Open-Source Wind and Wind Power Datasets.

Nina Effenberger, Nicole Ludwig

CoRR, 2022

Adaptively coping with concept drifts in energy time series forecasting using profiles.

Benedikt Heidrich, Nicole Ludwig, Marian Turowski, Ralf Mikut, Veit Hagenmeyer

Proceedings of the e-Energy '22: The Thirteenth ACM International Conference on Future Energy Systems, Virtual Event, 28 June 2022, 2022

Analytical uncertainty propagation and storage usage in a high RES Turkish transmission grid scenario.

Rebecca Bauer, Tillmann Mühlpfordt, Nicole Ludwig, Veit Hagenmeyer

Proceedings of the e-Energy '22: The Thirteenth ACM International Conference on Future Energy Systems, Virtual Event, 28 June 2022, 2022

2021

Smart Data Representations: Impact on the Accuracy of Deep Neural Networks.

Oliver Neumann, Nicole Ludwig, Marian Turowski, Benedikt Heidrich, Veit Hagenmeyer, Ralf Mikut

CoRR, 2021

pyWATTS: Python Workflow Automation Tool for Time Series.

Benedikt Heidrich, Andreas Bartschat, Marian Turowski, Oliver Neumann, Kaleb Phipps, Stefan Meisenbacher, Kai Schmieder, Nicole Ludwig, Ralf Mikut, Veit Hagenmeyer

CoRR, 2021

KIU-2021 Keynote: Uncertainty in Machine Learning for Environmental Research.

Nicole Ludwig

Proceedings of the 51. Jahrestagung der Gesellschaft für Informatik, INFORMATIK 2021 - Computer Science & Sustainability, Berlin, Germany, 27. September, 2021

2020

Data-Driven Methods for Demand-Side Flexibility in Energy Systems

Nicole Ludwig

PhD thesis, 2020

Forecasting energy time series with profile neural networks.

Benedikt Heidrich, Marian Turowski, Nicole Ludwig, Ralf Mikut, Veit Hagenmeyer

Proceedings of the e-Energy '20: The Eleventh ACM International Conference on Future Energy Systems, 2020

2019

Industrial Demand-Side Flexibility: A Benchmark Data Set.

Nicole Ludwig, Lukas Barth, Dorothea Wagner, Veit Hagenmeyer

Proceedings of the Tenth ACM International Conference on Future Energy Systems, 2019

2018

Concept and benchmark results for Big Data energy forecasting based on Apache Spark.

Jorge Ángel González Ordiano, Andreas Bartschat, Nicole Ludwig, Eric Braun, Simon Waczowicz, Nicolas Renkamp, Nico Peter, Clemens Düpmeier, Ralf Mikut, Veit Hagenmeyer

J. Big Data, 2018

A comprehensive modelling framework for demand side flexibility in smart grids.

Lukas Barth, Nicole Ludwig, Esther Mengelkamp, Philipp Staudt

Comput. Sci. Res. Dev., 2018

Demand Response clustering: Automatically finding optimal cluster hyper-parameter values.

Simon Waczowicz, Nicole Ludwig, Jorge Ángel González Ordiano, Ralf Mikut, Veit Hagenmeyer

Proceedings of the Ninth International Conference on Future Energy Systems, 2018

SCiBER: A new public data set of municipal building consumption.

Philipp Staudt, Nicole Ludwig, Julian Huber, Veit Hagenmeyer, Christof Weinhardt

Proceedings of the Ninth International Conference on Future Energy Systems, 2018

How much demand side flexibility do we need?: Analyzing where to exploit flexibility in industrial processes.

Lukas Barth, Veit Hagenmeyer, Nicole Ludwig, Dorothea Wagner

Proceedings of the Ninth International Conference on Future Energy Systems, 2018

Assessment of Unsupervised Standard Pattern Recognition Methods for Industrial Energy Time Series.

Nicole Ludwig, Simon Waczowicz, Ralf Mikut, Veit Hagenmeyer

Proceedings of the Ninth International Conference on Future Energy Systems, 2018

2017

Towards coding strategies for forecasting-based scheduling in smart grids and the energy lab 2.0.

Wilfried Jakob, Jorge Ángel González Ordiano, Nicole Ludwig, Ralf Mikut, Veit Hagenmeyer

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

2016

Time Series Analysis for Big Data: Evaluating Bayesian Structural Time Series using Electricity Prices.

Nicole Ludwig, Stefan Feuerriegel, Dirk Neumann

Proceedings of the Multikonferenz Wirtschaftsinformatik, 2016

2015

Putting Big Data analytics to work: Feature selection for forecasting electricity prices using the LASSO and random forests.

Nicole Ludwig, Stefan Feuerriegel, Dirk Neumann

J. Decis. Syst., 2015