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k-MILP: A novel clustering approach to select typical and extreme days for multi-energy systems design optimization

Citations

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Cited by:

  1. 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).
  2. Ikäheimo, Jussi & Weiss, Robert & Kiviluoma, Juha & Pursiheimo, Esa & Lindroos, Tomi J., 2022. "Impact of power-to-gas on the cost and design of the future low-carbon urban energy system," Applied Energy, Elsevier, vol. 305(C).
  3. Moretti, Luca & Martelli, Emanuele & Manzolini, Giampaolo, 2020. "An efficient robust optimization model for the unit commitment and dispatch of multi-energy systems and microgrids," Applied Energy, Elsevier, vol. 261(C).
  4. Giovanniello, Michael Anthony & Wu, Xiao-Yu, 2023. "Hybrid lithium-ion battery and hydrogen energy storage systems for a wind-supplied microgrid," Applied Energy, Elsevier, vol. 345(C).
  5. 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.
  6. Hoffmann, Maximilian & Kotzur, Leander & Stolten, Detlef, 2022. "The Pareto-optimal temporal aggregation of energy system models," Applied Energy, Elsevier, vol. 315(C).
  7. Gómez-Gardars, Emanuel Birkir & Rodríguez-Macias, Antonio & Tena-García, Jorge Luis & Fuentes-Cortés, Luis Fabián, 2022. "Assessment of the water–energy–carbon nexus in energy systems: A multi-objective approach," Applied Energy, Elsevier, vol. 305(C).
  8. Li, Yiming & Liu, Che & Zhang, Lizhi & Sun, Bo, 2021. "A partition optimization design method for a regional integrated energy system based on a clustering algorithm," Energy, Elsevier, vol. 219(C).
  9. 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.
  10. Hou, Rui & Deng, Guangzhi & Wu, Minrong & Wang, Wei & Gao, Wei & Chen, Kang & Liu, Lijun & Dehan, Sim, 2023. "Optimum exploitation of an integrated energy system considering renewable sources and power-heat system and energy storage," Energy, Elsevier, vol. 282(C).
  11. Martelli, Emanuele & Freschini, Marco & Zatti, Matteo, 2020. "Optimization of renewable energy subsidy and carbon tax for multi energy systems using bilevel programming," Applied Energy, Elsevier, vol. 267(C).
  12. 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).
  13. 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).
  14. 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).
  15. Niu, Jide & Li, Xiaoyuan & Tian, Zhe & Yang, Hongxing, 2023. "A framework for quantifying the value of information to mitigate risk in the optimal design of distributed energy systems under uncertainty," Applied Energy, Elsevier, vol. 350(C).
  16. 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).
  17. 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).
  18. Bahlawan, Hilal & Losi, Enzo & Manservigi, Lucrezia & Morini, Mirko & Pinelli, Michele & Spina, Pier Ruggero & Venturini, Mauro, 2022. "Optimization of a renewable energy plant with seasonal energy storage for the transition towards 100% renewable energy supply," Renewable Energy, Elsevier, vol. 198(C), pages 1296-1306.
  19. 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).
  20. Domínguez, R. & Vitali, S., 2021. "Multi-chronological hierarchical clustering to solve capacity expansion problems with renewable sources," Energy, Elsevier, vol. 227(C).
  21. 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.
  22. Fan Li & Jingxi Su & Bo Sun, 2023. "An Optimal Scheduling Method for an Integrated Energy System Based on an Improved k-Means Clustering Algorithm," Energies, MDPI, vol. 16(9), pages 1-22, April.
  23. Alabi, Tobi Michael & Lu, Lin & Yang, Zaiyue, 2021. "A novel multi-objective stochastic risk co-optimization model of a zero-carbon multi-energy system (ZCMES) incorporating energy storage aging model and integrated demand response," Energy, Elsevier, vol. 226(C).
  24. Helistö, Niina & Kiviluoma, Juha & Reittu, Hannu, 2020. "Selection of representative slices for generation expansion planning using regular decomposition," Energy, Elsevier, vol. 211(C).
  25. Bahlawan, Hilal & Morini, Mirko & Spina, Pier Ruggero & Venturini, Mauro, 2021. "Inventory scaling, life cycle impact assessment and design optimization of distributed energy plants," Applied Energy, Elsevier, vol. 304(C).
  26. 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).
  27. Ikäheimo, Jussi & Lindroos, Tomi J. & Kiviluoma, Juha, 2023. "Impact of climate and geological storage potential on feasibility of hydrogen fuels," Applied Energy, Elsevier, vol. 342(C).
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