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ORCIDNicole Ludwig 0002
Person information
- affiliation: University of Tübingen, Germany
- affiliation: Karlsruhe Institute of Technology (KIT), Germany
Other persons with the same name
- Nicole Ludwig
- Nicole Ludwig 0001
![[0000-0003-4703-7567]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0003-4703-7567")
— Saarland University, Germany
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2020 – today
- 2024
[c12]Florian Ebmeier, Nicole Ludwig, Georg Martius, Volker H. Franz:
PaSTS An Operational Dataset for Domestic Solar Thermal Systems. e-Energy 2024- [i7]Nina Effenberger, Nicole Ludwig:
Towards turbine-location-aware multi-decadal wind power predictions with CMIP6. CoRR abs/2408.14889 (2024) - 2023
- [j7]Oliver Neumann, Marian Turowski, Ralf Mikut, Veit Hagenmeyer, Nicole Ludwig:
Using weather data in energy time series forecasting: the benefit of input data transformations. Energy Inform. 6(1): 44 (2023) - [j6]Nicole Ludwig, Siddharth Arora, James W. Taylor:
Probabilistic load forecasting using post-processed weather ensemble predictions. J. Oper. Res. Soc. 74(3): 1008-1020 (2023) - [i6]Jannik Thümmel, Matthias Karlbauer, Sebastian Otte, Christiane Zarfl, Georg Martius, Nicole Ludwig, Thomas Scholten, Ulrich Friedrich, Volker Wulfmeyer, Bedartha Goswami, Martin V. Butz:
Inductive biases in deep learning models for weather prediction. CoRR abs/2304.04664 (2023) - 2022
- [j5]Maximilian Beichter, Kaleb Phipps, Martha Maria Frysztacki, Ralf Mikut, Veit Hagenmeyer, Nicole Ludwig:
Net load forecasting using different aggregation levels. Energy Inform. 5 (2022) - [j4]Shahab Karrari, Nicole Ludwig, Giovanni De Carne, Mathias Noe:
Sizing of Hybrid Energy Storage Systems Using Recurring Daily Patterns. IEEE Trans. Smart Grid 13(4): 3290-3300 (2022) - [c11]Benedikt Heidrich, Nicole Ludwig, Marian Turowski, Ralf Mikut, Veit Hagenmeyer:
Adaptively coping with concept drifts in energy time series forecasting using profiles. e-Energy 2022: 459-470 - [c10]Rebecca Bauer, Tillmann Mühlpfordt, Nicole Ludwig, Veit Hagenmeyer:
Analytical uncertainty propagation and storage usage in a high RES Turkish transmission grid scenario. e-Energy 2022: 489-495 - [i5]Nina Effenberger, Nicole Ludwig:
A Collection and Categorization of Open-Source Wind and Wind Power Datasets. CoRR abs/2202.08524 (2022) - [i4]Rebecca Bauer, Tillmann Mühlpfordt, Nicole Ludwig, Veit Hagenmeyer:
Analytical Uncertainty Propagation for Multi-Period Stochastic Optimal Power Flow. CoRR abs/2204.05883 (2022) - [i3]Rebecca Bauer, Tillmann Mühlpfordt, Nicole Ludwig, Veit Hagenmeyer:
Analytical Uncertainty Propagation for Multi-Period Stochastic Optimal Power Flow. CoRR abs/2212.03097 (2022) - 2021
- [c9]Nicole Ludwig:
KIU-2021 Keynote: Uncertainty in Machine Learning for Environmental Research. GI-Jahrestagung 2021: 227 - [i2]Benedikt Heidrich, Andreas Bartschat, Marian Turowski, Oliver Neumann, Kaleb Phipps, Stefan Meisenbacher, Kai Schmieder, Nicole Ludwig, Ralf Mikut, Veit Hagenmeyer:
pyWATTS: Python Workflow Automation Tool for Time Series. CoRR abs/2106.10157 (2021) - [i1]Oliver Neumann, Nicole Ludwig, Marian Turowski, Benedikt Heidrich, Veit Hagenmeyer, Ralf Mikut:
Smart Data Representations: Impact on the Accuracy of Deep Neural Networks. CoRR abs/2111.09128 (2021) - 2020
- [b1]Nicole Ludwig:
Data-Driven Methods for Demand-Side Flexibility in Energy Systems. Karlsruhe University, Germany, 2020 - [c8]Benedikt Heidrich, Marian Turowski, Nicole Ludwig, Ralf Mikut, Veit Hagenmeyer:
Forecasting energy time series with profile neural networks. e-Energy 2020: 220-230
2010 – 2019
- 2019
- [c7]Nicole Ludwig, Lukas Barth, Dorothea Wagner, Veit Hagenmeyer:
Industrial Demand-Side Flexibility: A Benchmark Data Set. e-Energy 2019: 460-473 - 2018
- [j3]Lukas Barth, Nicole Ludwig, Esther Mengelkamp, Philipp Staudt:
A comprehensive modelling framework for demand side flexibility in smart grids. Comput. Sci. Res. Dev. 33(1-2): 13-23 (2018) - [j2]Jorge Ángel González Ordiano, Andreas Bartschat, Nicole Ludwig, Eric Braun, Simon Waczowicz, Nicolas Renkamp, Nico Peter, Clemens Düpmeier, Ralf Mikut, Veit Hagenmeyer:
Concept and benchmark results for Big Data energy forecasting based on Apache Spark. J. Big Data 5: 11 (2018) - [c6]Lukas Barth, Veit Hagenmeyer, Nicole Ludwig, Dorothea Wagner:
How much demand side flexibility do we need?: Analyzing where to exploit flexibility in industrial processes. e-Energy 2018: 43-62 - [c5]Simon Waczowicz, Nicole Ludwig, Jorge Ángel González Ordiano, Ralf Mikut, Veit Hagenmeyer:
Demand Response clustering: Automatically finding optimal cluster hyper-parameter values. e-Energy 2018: 429-430 - [c4]Nicole Ludwig, Simon Waczowicz, Ralf Mikut, Veit Hagenmeyer:
Assessment of Unsupervised Standard Pattern Recognition Methods for Industrial Energy Time Series. e-Energy 2018: 434-435 - [c3]Philipp Staudt, Nicole Ludwig, Julian Huber, Veit Hagenmeyer, Christof Weinhardt:
SCiBER: A new public data set of municipal building consumption. e-Energy 2018: 618-621 - 2017
- [c2]Wilfried Jakob, Jorge Ángel González Ordiano, Nicole Ludwig, Ralf Mikut, Veit Hagenmeyer:
Towards coding strategies for forecasting-based scheduling in smart grids and the energy lab 2.0. GECCO (Companion) 2017: 1271-1278 - 2016
- [c1]Nicole Ludwig, Stefan Feuerriegel, Dirk Neumann:
Time Series Analysis for Big Data: Evaluating Bayesian Structural Time Series using Electricity Prices. MKWI 2016: 1569-1580 - 2015
- [j1]Nicole Ludwig, Stefan Feuerriegel, Dirk Neumann:
Putting Big Data analytics to work: Feature selection for forecasting electricity prices using the LASSO and random forests. J. Decis. Syst. 24(1): 19-36 (2015)
Coauthor Index
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