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Nicole Ludwig
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Putting Big Data analytics to work: Feature selection for forecasting electricity prices using the LASSO and random forests
N Ludwig, S Feuerriegel, D Neumann
Journal of Decision Systems 24 (1), 19-36, 2015
1032015
Data analytics in the electricity sector–a quantitative and qualitative literature review
F vom Scheidt, H Medinová, N Ludwig, B Richter, P Staudt, C Weinhardt
Energy and AI 1, 100009, 2020
442020
A comprehensive modelling framework for demand side flexibility in smart grids
L Barth, N Ludwig, E Mengelkamp, P Staudt
Computer Science-Research and Development 33 (1), 13-23, 2018
332018
Mining flexibility patterns in energy time series from industrial processes
N Ludwig, S Waczowicz, R Mikut, V Hagenmeyer, F Hoffmann, ...
Proceedings. 27. Workshop Computational Intelligence Dortmund, 23. - 24 …, 2017
212017
How much demand side flexibility do we need? Analyzing where to exploit flexibility in industrial processes
L Barth, V Hagenmeyer, N Ludwig, D Wagner
Proceedings of the Ninth International Conference on Future Energy Systems …, 2018
162018
Concept and benchmark results for Big Data energy forecasting based on Apache Spark
JÁ González Ordiano, A Bartschat, N Ludwig, E Braun, S Waczowicz, ...
Journal of Big Data 5 (1), 1-11, 2018
152018
Industrial demand-side flexibility: a benchmark data set
N Ludwig, L Barth, D Wagner, V Hagenmeyer
Proceedings of the Tenth ACM International Conference on Future Energy …, 2019
122019
Towards coding strategies for forecasting-based scheduling in smart grids and the energy lab 2.0
W Jakob, JÁG Ordiano, N Ludwig, R Mikut, V Hagenmeyer
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2017
102017
Forecasting energy time series with profile neural networks
B Heidrich, M Turowski, N Ludwig, R Mikut, V Hagenmeyer
Proceedings of the Eleventh ACM International Conference on Future Energy …, 2020
92020
Pywatts: Python workflow automation tool for time series
B Heidrich, A Bartschat, M Turowski, O Neumann, K Phipps, ...
arXiv preprint arXiv:2106.10157, 2021
72021
A method for sizing centralised energy storage systems using standard patterns
S Karrari, N Ludwig, V Hagenmeyer, M Noe
2019 IEEE Milan PowerTech, 1-6, 2019
72019
Sciber: A new public data set of municipal building consumption
P Staudt, N Ludwig, J Huber, V Hagenmeyer, C Weinhardt
Proceedings of the Ninth International Conference on Future Energy Systems …, 2018
52018
Evaluating ensemble post‐processing for wind power forecasts
K Phipps, S Lerch, M Andersson, R Mikut, V Hagenmeyer, N Ludwig
Wind Energy, 2022
42022
Assessment of unsupervised standard pattern recognition methods for industrial energy time series
N Ludwig, S Waczowicz, R Mikut, V Hagenmeyer
Proceedings of the Ninth International Conference on Future Energy Systems …, 2018
42018
Data-Driven Methods for Demand-Side Flexibility in Energy Systems
NN Ludwig
Dissertation, Karlsruhe, Karlsruher Institut für Technologie (KIT), 2020, 2020
32020
Time series analysis for big data: evaluating Bayesian structural time series using electricity prices
N Ludwig, S Feuerriegel, D Neumann
Multikonferenz Wirtschaftsinformatik (MKWI) 3, 1569-1580, 2016
32016
Sizing of Hybrid Energy Storage Systems Using Recurring Daily Patterns
S Karrari, N Ludwig, G De Carne, M Noe
IEEE Transactions on Smart Grid 13 (4), 3290-3300, 2022
12022
Potential of ensemble copula coupling for wind power forecasting
K Phipps, N Ludwig, V Hagenmeyer, R Mikut
Proceedings-30. Workshop Computational Intelligence: Berlin, 26.-27 …, 2020
12020
Probabilistic load forecasting using post-processed weather ensemble predictions
N Ludwig, S Arora, JW Taylor
Journal of the Operational Research Society (submitted), 2020
12020
Auction design to use flexibility potentials in the energy-intensive industry
N Ludwig, R Mikut, V Hagenmeyer
2018 15th International Conference on the European Energy Market (EEM), 1-5, 2018
12018
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