IDEAS home Printed from https://ideas.repec.org/r/gam/jeners/v13y2020i3p641-d315871.html
   My bibliography  Save this item

A Review on Time Series Aggregation Methods for Energy System Models

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. de Guibert, Paul & Shirizadeh, Behrang & Quirion, Philippe, 2020. "Variable time-step: A method for improving computational tractability for energy system models with long-term storage," Energy, Elsevier, vol. 213(C).
  2. Hilbers, Adriaan P. & Brayshaw, David J. & Gandy, Axel, 2023. "Reducing climate risk in energy system planning: A posteriori time series aggregation for models with storage," Applied Energy, Elsevier, vol. 334(C).
  3. Shruthi Patil & Leander Kotzur & Detlef Stolten, 2022. "Advanced Spatial and Technological Aggregation Scheme for Energy System Models," Energies, MDPI, vol. 15(24), pages 1-26, December.
  4. Lüth, Alexandra & Seifert, Paul E. & Egging-Bratseth, Ruud & Weibezahn, Jens, 2023. "How to connect energy islands: Trade-offs between hydrogen and electricity infrastructure," Applied Energy, Elsevier, vol. 341(C).
  5. Reveron Baecker, Beneharo & Candas, Soner, 2022. "Co-optimizing transmission and active distribution grids to assess demand-side flexibilities of a carbon-neutral German energy system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
  6. Clara Ceccolini & Roozbeh Sangi, 2022. "Benchmarking Approaches for Assessing the Performance of Building Control Strategies: A Review," Energies, MDPI, vol. 15(4), pages 1-30, February.
  7. ZareAfifi, Farzan & Mahmud, Zabir & Kurtz, Sarah, 2023. "Diurnal, physics-based strategy for computationally efficient capacity-expansion optimizations for solar-dominated grids," Energy, Elsevier, vol. 279(C).
  8. Göke, Leonard & Kendziorski, Mario, 2022. "Adequacy of time-series reduction for renewable energy systems," Energy, Elsevier, vol. 238(PA).
  9. Shirizadeh, Behrang & Quirion, Philippe, 2022. "Do multi-sector energy system optimization models need hourly temporal resolution? A case study with an investment and dispatch model applied to France," Applied Energy, Elsevier, vol. 305(C).
  10. Teichgraeber, Holger & Küpper, Lucas Elias & Brandt, Adam R., 2021. "Designing reliable future energy systems by iteratively including extreme periods in time-series aggregation," Applied Energy, Elsevier, vol. 304(C).
  11. Hoffmann, Maximilian & Kotzur, Leander & Stolten, Detlef, 2022. "The Pareto-optimal temporal aggregation of energy system models," Applied Energy, Elsevier, vol. 315(C).
  12. Klemm, Christian & Wiese, Frauke & Vennemann, Peter, 2023. "Model-based run-time and memory reduction for a mixed-use multi-energy system model with high spatial resolution," Applied Energy, Elsevier, vol. 334(C).
  13. Thomas Heggarty & Jean-Yves Bourmaud & Robin Girard & Georges Kariniotakis, 2024. "Assessing the relative impacts of maximum investment rate and temporal detail in capacity expansion models applied to power systems," Post-Print hal-04383397, HAL.
  14. Wang, Jing & Kang, Lixia & Liu, Yongzhong, 2022. "A multi-objective approach to determine time series aggregation strategies for optimal design of multi-energy systems," Energy, Elsevier, vol. 258(C).
  15. Theresa Liegl & Simon Schramm & Philipp Kuhn & Thomas Hamacher, 2023. "Considering Socio-Technical Parameters in Energy System Models—The Current Status and Next Steps," Energies, MDPI, vol. 16(20), pages 1-19, October.
  16. Kittel, Martin & Hobbie, Hannes & Dierstein, Constantin, 2022. "Temporal aggregation of time series to identify typical hourly electricity system states: A systematic assessment of relevant cluster algorithms," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 247, pages 1-15.
  17. Hassan, Muhammed A. & Khalil, Adel & Abubakr, Mohamed, 2021. "Selection methodology of representative meteorological days for assessment of renewable energy systems," Renewable Energy, Elsevier, vol. 177(C), pages 34-51.
  18. Chloi Syranidou & Jochen Linssen & Detlef Stolten & Martin Robinius, 2020. "Integration of Large-Scale Variable Renewable Energy Sources into the Future European Power System: On the Curtailment Challenge," Energies, MDPI, vol. 13(20), pages 1-23, October.
  19. Gonzato, Sebastian & Bruninx, Kenneth & Delarue, Erik, 2021. "Long term storage in generation expansion planning models with a reduced temporal scope," Applied Energy, Elsevier, vol. 298(C).
  20. Xiaojing Hu & Haoling Min & Sai Dai & Zhi Cai & Xiaonan Yang & Qiang Ding & Zhanyong Yang & Feng Xiao, 2022. "Research on Maintenance Strategies for Different Transmission Sections to Improve the Consumption Rate Based on a Renewable Energy Production Simulation," Energies, MDPI, vol. 15(24), pages 1-11, December.
  21. Thimet, P.J. & Mavromatidis, G., 2023. "What-where-when: Investigating the role of storage for the German electricity system transition," Applied Energy, Elsevier, vol. 351(C).
  22. Grochowicz, Aleksander & van Greevenbroek, Koen & Benth, Fred Espen & Zeyringer, Marianne, 2023. "Intersecting near-optimal spaces: European power systems with more resilience to weather variability," Energy Economics, Elsevier, vol. 118(C).
  23. Kittel, Martin & Hobbie, Hannes & Dierstein, Constantin, 2022. "Temporal aggregation of time series to identify typical hourly electricity system states: A systematic assessment of relevant cluster algorithms," Energy, Elsevier, vol. 247(C).
  24. Pöstges, Arne & Weber, Christoph, 2023. "Identifying key elements for adequate simplifications of investment choices – The case of wind energy expansion," Energy Economics, Elsevier, vol. 120(C).
  25. Yokoyama, Ryohei & Takeuchi, Kotaro & Shinano, Yuji & Wakui, Tetsuya, 2021. "Effect of model reduction by time aggregation in multiobjective optimal design of energy supply systems by a hierarchical MILP method," Energy, Elsevier, vol. 228(C).
  26. Teichgraeber, Holger & Brandt, Adam R., 2022. "Time-series aggregation for the optimization of energy systems: Goals, challenges, approaches, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
  27. Martínez-Gordón, R. & Morales-España, G. & Sijm, J. & Faaij, A.P.C., 2021. "A review of the role of spatial resolution in energy systems modelling: Lessons learned and applicability to the North Sea region," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
  28. Densing, Martin & Wan, Yi, 2022. "Low-dimensional scenario generation method of solar and wind availability for representative days in energy modeling," Applied Energy, Elsevier, vol. 306(PB).
  29. Pilotti, L. & Colombari, M. & Castelli, A.F. & Binotti, M. & Giaconia, A. & Martelli, E., 2023. "Simultaneous design and operational optimization of hybrid CSP-PV plants," Applied Energy, Elsevier, vol. 331(C).
  30. Arne Pöstges & Christoph Weber, "undated". "Identifying key elements for adequate simplifications of investment choices - The case of wind energy expansion," EWL Working Papers 2101, University of Duisburg-Essen, Chair for Management Science and Energy Economics.
  31. Jing, Rui & Li, Yubing & Wang, Meng & Chachuat, Benoit & Lin, Jianyi & Guo, Miao, 2021. "Coupling biogeochemical simulation and mathematical optimisation towards eco-industrial energy systems design," Applied Energy, Elsevier, vol. 290(C).
  32. Alexander J. Bogensperger & Yann Fabel & Joachim Ferstl, 2022. "Accelerating Energy-Economic Simulation Models via Machine Learning-Based Emulation and Time Series Aggregation," Energies, MDPI, vol. 15(3), pages 1-42, February.
  33. Hoffmann, Maximilian & Priesmann, Jan & Nolting, Lars & Praktiknjo, Aaron & Kotzur, Leander & Stolten, Detlef, 2021. "Typical periods or typical time steps? A multi-model analysis to determine the optimal temporal aggregation for energy system models," Applied Energy, Elsevier, vol. 304(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.