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Holger Teichgräber
Holger Teichgräber
Department of Energy Resources Engineering, Stanford University
Verified email at stanford.edu - Homepage
Title
Cited by
Cited by
Year
Clustering methods to find representative periods for the optimization of energy systems: An initial framework and comparison
H Teichgraeber, A Brandt
Applied Energy 239, 1283-1293, 2019
2182019
An economic receding horizon optimization approach for energy management in the chlor-alkali process with hybrid renewable energy generation
X Wang, H Teichgraeber, A Palazoglu, NH El-Farra
Journal of Process Control 24 (8), 1318-1327, 2014
862014
Time-series aggregation for the optimization of energy systems: Goals, challenges, approaches, and opportunities
H Teichgraeber, AR Brandt
Renewable and Sustainable Energy Reviews 157, 111984, 2022
662022
Extreme events in time series aggregation: A case study for optimal residential energy supply systems
H Teichgraeber, C Lindenmeyer, N Baumgärtner, L Kotzur, D Stolten, ...
Applied Energy 275 (2020), 115223, 2020
482020
Optimal design and operations of a flexible oxyfuel natural gas plant
H Teichgraeber, PG Brodrick, AR Brandt
Energy 141, 506-518, 2017
362017
Design and operations optimization of membrane-based flexible carbon capture
M Yuan, H Teichgraeber, J Wilcox, AR Brandt
International Journal of Greenhouse Gas Control 84, 154-163, 2019
322019
Optimal design of an electricity-intensive industrial facility subject to electricity price uncertainty: stochastic optimization and scenario reduction
H Teichgraeber, AR Brandt
Chemical Engineering Research and Design, 2020
222020
Designing reliable future energy systems by iteratively including extreme periods in time-series aggregation
H Teichgraeber, LE Küpper, AR Brandt
Applied Energy 304, 117696, 2021
182021
TimeSeriesClustering: An extensible framework in Julia
H Teichgraeber, LE Kuepper, AR Brandt
Journal of Open Source Software 4 (41), 1573, 2019
132019
Wind data introduce error in time-series reduction for capacity expansion modelling
LE Kuepper, H Teichgraeber, N Baumgärtner, A Bardow, AR Brandt
Energy 256, 124467, 2022
122022
Blow wind blow: Capital deployment in variable energy systems
AR Brandt, H Teichgraeber, CA Kang, CJ Barnhart, MA Carbajales-Dale, ...
Energy 224, 120198, 2021
62021
Identifying and Evaluating New Market Opportunities with Capacity Expansion Models
H Teichgraeber, AR Brandt
Stanford Clean Energy Finance Forum ( https://energy.stanford.edu/sites …, 2017
62017
CO2 vs Biomass: Identification of Environmentally Beneficial Processes for Platform Chemicals from Renewable Carbon Sources
A Sternberg, H Teichgräber, P Voll, A Bardow
Computer Aided Chemical Engineering 37, 1361-1366, 2015
62015
CapacityExpansion: A capacity expansion modeling framework in Julia
LE Kuepper, H Teichgraeber, AR Brandt
Journal of Open Source Software 5 (52), 2034, 2020
42020
Temporal resolution in energy systems optimization models
H Teichgraeber
Stanford University ( https://stacks.stanford.edu/file/druid:jh261zf4637 …, 2020
42020
Determining the value of more accurate wind power forecasting in global electricity markets
P Storck, E Grimit, H Teichgraeber
Proceedings of the EWEA Technical Workshop on Wind Power Forecasting, Leuven …, 2015
32015
The Interplay between Operations Research and Machine Learning
A Subramanian, H Teichgraeber
https://doi.org/10.1287/orms.2023.02.02, 2023
2023
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