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 | 230 | 2019 |
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 | 85 | 2014 |
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 | 75 | 2022 |
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 | 51 | 2020 |
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 | 37 | 2019 |
Optimal design and operations of a flexible oxyfuel natural gas plant H Teichgraeber, PG Brodrick, AR Brandt Energy 141, 506-518, 2017 | 37 | 2017 |
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 | 24 | 2020 |
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 | 19 | 2021 |
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 | 13 | 2022 |
TimeSeriesClustering: An extensible framework in Julia H Teichgraeber, LE Kuepper, AR Brandt Journal of Open Source Software 4 (41), 1573, 2019 | 12 | 2019 |
Blow wind blow: Capital deployment in variable energy systems AR Brandt, H Teichgraeber, CA Kang, CJ Barnhart, MA Carbajales-Dale, ... Energy 224, 120198, 2021 | 6 | 2021 |
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 | 6 | 2017 |
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 | 6 | 2015 |
CapacityExpansion: A capacity expansion modeling framework in Julia LE Kuepper, H Teichgraeber, AR Brandt Journal of Open Source Software 5 (52), 2034, 2020 | 4 | 2020 |
Temporal resolution in energy systems optimization models H Teichgraeber Stanford University ( https://stacks.stanford.edu/file/druid:jh261zf4637 …, 2020 | 4 | 2020 |
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 | 3 | 2015 |
The Interplay between Operations Research and Machine Learning A Subramanian, H Teichgraeber https://doi.org/10.1287/orms.2023.02.02, 2023 | | 2023 |