IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v239y2019icp1283-1293.html
   My bibliography  Save this item

Clustering methods to find representative periods for the optimization of energy systems: An initial framework and comparison

Citations

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


Cited by:

  1. Zhang, Chao & Lasaulce, Samson & Hennebel, Martin & Saludjian, Lucas & Panciatici, Patrick & Poor, H. Vincent, 2021. "Decision-making oriented clustering: Application to pricing and power consumption scheduling," Applied Energy, Elsevier, vol. 297(C).
  2. Teichgraeber, Holger & Lindenmeyer, Constantin P. & Baumgärtner, Nils & Kotzur, Leander & Stolten, Detlef & Robinius, Martin & Bardow, André & Brandt, Adam R., 2020. "Extreme events in time series aggregation: A case study for optimal residential energy supply systems," Applied Energy, Elsevier, vol. 275(C).
  3. Chunxia Gao & Zhaoyan Zhang & Peiguang Wang, 2023. "Day-Ahead Scheduling Strategy Optimization of Electric–Thermal Integrated Energy System to Improve the Proportion of New Energy," Energies, MDPI, vol. 16(9), pages 1-30, April.
  4. 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).
  5. Göke, Leonard & Kendziorski, Mario, 2022. "Adequacy of time-series reduction for renewable energy systems," Energy, Elsevier, vol. 238(PA).
  6. Zhang, Zhaoyan & Wang, Peiguang & Jiang, Ping & Liu, Zhiheng & Fu, Lei, 2022. "Energy management of ultra-short-term optimal scheduling of integrated energy system considering the characteristics of heating network," Energy, Elsevier, vol. 240(C).
  7. Rigo-Mariani, Rémy, 2022. "Optimized time reduction models applied to power and energy systems planning – Comparison with existing methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
  8. Xia, Tian & Huang, Wujing & Lu, Xi & Zhang, Ning & Kang, Chongqing, 2020. "Planning district multiple energy systems considering year-round operation," Energy, Elsevier, vol. 213(C).
  9. Kenjiro Yagi & Ramteen Sioshansi, 2023. "Simplifying capacity planning for electricity systems with hydroelectric and renewable generation," Computational Management Science, Springer, vol. 20(1), pages 1-28, December.
  10. Maximilian Hoffmann & Leander Kotzur & Detlef Stolten & Martin Robinius, 2020. "A Review on Time Series Aggregation Methods for Energy System Models," Energies, MDPI, vol. 13(3), pages 1-61, February.
  11. 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).
  12. Hoffmann, Maximilian & Kotzur, Leander & Stolten, Detlef, 2022. "The Pareto-optimal temporal aggregation of energy system models," Applied Energy, Elsevier, vol. 315(C).
  13. He, Zhenglei & Liu, Chang & Wang, Yutao & Wang, Xu & Man, Yi, 2023. "Optimal operation of wind-solar-thermal collaborative power system considering carbon trading and energy storage," Applied Energy, Elsevier, vol. 352(C).
  14. Tso, William W. & Demirhan, C. Doga & Heuberger, Clara F. & Powell, Joseph B. & Pistikopoulos, Efstratios N., 2020. "A hierarchical clustering decomposition algorithm for optimizing renewable power systems with storage," Applied Energy, Elsevier, vol. 270(C).
  15. Brandt, Adam R. & Teichgraeber, Holger & Kang, Charles A. & Barnhart, Charles J. & Carbajales-Dale, Michael A. & Sgouridis, Sgouris, 2021. "Blow wind blow: Capital deployment in variable energy systems," Energy, Elsevier, vol. 224(C).
  16. Zhouchun Huang & Qipeng P. Zheng & Andrew L. Liu, 2022. "A Nested Cross Decomposition Algorithm for Power System Capacity Expansion with Multiscale Uncertainties," INFORMS Journal on Computing, INFORMS, vol. 34(4), pages 1919-1939, July.
  17. Yeganefar, Ali & Amin-Naseri, Mohammad Reza & Sheikh-El-Eslami, Mohammad Kazem, 2020. "Improvement of representative days selection in power system planning by incorporating the extreme days of the net load to take account of the variability and intermittency of renewable resources," Applied Energy, Elsevier, vol. 272(C).
  18. Li, Can & Conejo, Antonio J. & Liu, Peng & Omell, Benjamin P. & Siirola, John D. & Grossmann, Ignacio E., 2022. "Mixed-integer linear programming models and algorithms for generation and transmission expansion planning of power systems," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1071-1082.
  19. Zatti, Matteo & Gabba, Marco & Freschini, Marco & Rossi, Michele & Gambarotta, Agostino & Morini, Mirko & Martelli, Emanuele, 2019. "k-MILP: A novel clustering approach to select typical and extreme days for multi-energy systems design optimization," Energy, Elsevier, vol. 181(C), pages 1051-1063.
  20. Daniel J. Sambor & Michelle Wilber & Erin Whitney & Mark Z. Jacobson, 2020. "Development of a Tool for Optimizing Solar and Battery Storage for Container Farming in a Remote Arctic Microgrid," Energies, MDPI, vol. 13(19), pages 1-18, October.
  21. 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.
  22. Ghaemi, Zahra & Tran, Thomas T.D. & Smith, Amanda D., 2022. "Comparing classical and metaheuristic methods to optimize multi-objective operation planning of district energy systems considering uncertainties," Applied Energy, Elsevier, vol. 321(C).
  23. Vidya Krishnan Mololoth & Saguna Saguna & Christer Åhlund, 2023. "Blockchain and Machine Learning for Future Smart Grids: A Review," Energies, MDPI, vol. 16(1), pages 1-39, January.
  24. Pavičević, Matija & Kavvadias, Konstantinos & Pukšec, Tomislav & Quoilin, Sylvain, 2019. "Comparison of different model formulations for modelling future power systems with high shares of renewables – The Dispa-SET Balkans model," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
  25. Jun Dong & Peiwen Yang & Shilin Nie, 2019. "Day-Ahead Scheduling Model of the Distributed Small Hydro-Wind-Energy Storage Power System Based on Two-Stage Stochastic Robust Optimization," Sustainability, MDPI, vol. 11(10), pages 1-27, May.
  26. 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).
  27. 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).
  28. James H. Merrick & John E. T. Bistline & Geoffrey J. Blanford, 2021. "On representation of energy storage in electricity planning models," Papers 2105.03707, arXiv.org, revised May 2021.
  29. 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).
  30. Stefanie Buchholz & Mette Gamst & David Pisinger, 2020. "Finding a Portfolio of Near-Optimal Aggregated Solutions to Capacity Expansion Energy System Models," SN Operations Research Forum, Springer, vol. 1(1), pages 1-40, March.
  31. 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).
  32. 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).
  33. Prina, Matteo Giacomo & Nastasi, Benedetto & Groppi, Daniele & Misconel, Steffi & Garcia, Davide Astiaso & Sparber, Wolfram, 2022. "Comparison methods of energy system frameworks, models and scenario results," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
  34. Wang, Wei & Cova, Gregorio & Zio, Enrico, 2022. "A clustering-based framework for searching vulnerabilities in the operation dynamics of Cyber-Physical Energy Systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
  35. Chen, Youliang & Huang, Xiaoguang & Li, Wei & Fan, Rong & Zi, Pingyang & Wang, Xin, 2023. "Application of deep learning modelling of the optimal operation conditions of auxiliary equipment of combined cycle gas turbine power station," Energy, Elsevier, vol. 285(C).
  36. Chen, Xiao & Zanocco, Chad & Flora, June & Rajagopal, Ram, 2022. "Constructing dynamic residential energy lifestyles using Latent Dirichlet Allocation," Applied Energy, Elsevier, vol. 318(C).
  37. Domínguez, R. & Vitali, S., 2021. "Multi-chronological hierarchical clustering to solve capacity expansion problems with renewable sources," Energy, Elsevier, vol. 227(C).
  38. 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.
  39. Buchholz, Stefanie & Gamst, Mette & Pisinger, David, 2020. "Sensitivity analysis of time aggregation techniques applied to capacity expansion energy system models," Applied Energy, Elsevier, vol. 269(C).
  40. 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).
  41. Helistö, Niina & Kiviluoma, Juha & Reittu, Hannu, 2020. "Selection of representative slices for generation expansion planning using regular decomposition," Energy, Elsevier, vol. 211(C).
  42. Oriol Raventós & Julian Bartels, 2020. "Evaluation of Temporal Complexity Reduction Techniques Applied to Storage Expansion Planning in Power System Models," Energies, MDPI, vol. 13(4), pages 1-18, February.
  43. 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).
  44. Thiago Eliandro de Oliveira Gomes & André Ross Borniatti & Vinícius Jacques Garcia & Laura Lisiane Callai dos Santos & Nelson Knak Neto & Rui Anderson Ferrarezi Garcia, 2023. "Clustering Electrical Customers with Source Power and Aggregation Constraints: A Reliability-Based Approach in Power Distribution Systems," Energies, MDPI, vol. 16(5), pages 1-20, March.
  45. Kuepper, Lucas Elias & Teichgraeber, Holger & Baumgärtner, Nils & Bardow, André & Brandt, Adam R., 2022. "Wind data introduce error in time-series reduction for capacity expansion modelling," Energy, Elsevier, vol. 256(C).
  46. Jefferson A. Riera & Ricardo M. Lima & Ibrahim Hoteit & Omar Knio, 2022. "Simulated co-optimization of renewable energy and desalination systems in Neom, Saudi Arabia," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.