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Shrinking and receding horizon approaches for long-term operational planning of energy storage and supply systems

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  • Wakui, Tetsuya
  • Akai, Kazuki
  • Yokoyama, Ryohei

Abstract

To efficiently solve long-term operational planning problems of energy storage and supply systems, a near-optimal solution method based on the shrinking and receding horizon approaches was developed. A lower bound of the original problem is first calculated by solving a simplified problem, in which the number of binary variables is reduced and the related constraints are simplified. Then, a short-term operational planning problem, with a shrunken planning horizon length, is solved by providing the simplified problem results as the terminal condition for stored energy. Within this problem, the original binary variables and constraints are considered. The short-term operational planning is updated using a receding horizon approach, in which the initial and terminal conditions are provided by the previous short-term operational planning results and simplified problem results, respectively. The solution, obtained by connecting the solutions in all the updating horizons, is regarded as a near-optimal solution of the original problem. The developed method was applied to solve a long-term operational planning problem for an energy storage and supply system, which includes a photovoltaic unit and a metal hydride tank with a water electrolyzer. The results showed that the developed method could find a better solution in a shorter computation time than the conventional methods.

Suggested Citation

  • Wakui, Tetsuya & Akai, Kazuki & Yokoyama, Ryohei, 2022. "Shrinking and receding horizon approaches for long-term operational planning of energy storage and supply systems," Energy, Elsevier, vol. 239(PD).
    • Handle: RePEc:eee:energy:v:239:y:2022:i:pd:s0360544221023148
    DOI: 10.1016/j.energy.2021.122066
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    as
    1. Kotzur, Leander & Markewitz, Peter & Robinius, Martin & Stolten, Detlef, 2018. "Time series aggregation for energy system design: Modeling seasonal storage," Applied Energy, Elsevier, vol. 213(C), pages 123-135.
    2. Yokoyama, Ryohei & Wakui, Tetsuya & Kamakari, Junya & Takemura, Kazuhisa, 2010. "Performance analysis of a CO2 heat pump water heating system under a daily change in a standardized demand," Energy, Elsevier, vol. 35(2), pages 718-728.
    3. de Souza Dutra, Michael David & Anjos, Miguel F. & Le Digabel, Sébastien, 2019. "A general framework for customized transition to smart homes," Energy, Elsevier, vol. 189(C).
    4. 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).
    5. Murray, Portia & Orehounig, Kristina & Grosspietsch, David & Carmeliet, Jan, 2018. "A comparison of storage systems in neighbourhood decentralized energy system applications from 2015 to 2050," Applied Energy, Elsevier, vol. 231(C), pages 1285-1306.
    6. Wakui, Tetsuya & Kawayoshi, Hiroki & Yokoyama, Ryohei, 2016. "Optimal structural design of residential power and heat supply devices in consideration of operational and capital recovery constraints," Applied Energy, Elsevier, vol. 163(C), pages 118-133.
    7. Argyrou, Maria C. & Christodoulides, Paul & Kalogirou, Soteris A., 2018. "Energy storage for electricity generation and related processes: Technologies appraisal and grid scale applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 804-821.
    8. Petkov, Ivalin & Gabrielli, Paolo, 2020. "Power-to-hydrogen as seasonal energy storage: an uncertainty analysis for optimal design of low-carbon multi-energy systems," Applied Energy, Elsevier, vol. 274(C).
    9. Mubbashir Ali & Jussi Ekström & Matti Lehtonen, 2018. "Sizing Hydrogen Energy Storage in Consideration of Demand Response in Highly Renewable Generation Power Systems," Energies, MDPI, vol. 11(5), pages 1-11, May.
    10. Luz, Thiago & Moura, Pedro, 2019. "100% Renewable energy planning with complementarity and flexibility based on a multi-objective assessment," Applied Energy, Elsevier, vol. 255(C).
    11. van der Heijde, Bram & Vandermeulen, Annelies & Salenbien, Robbe & Helsen, Lieve, 2019. "Representative days selection for district energy system optimisation: a solar district heating system with seasonal storage," Applied Energy, Elsevier, vol. 248(C), pages 79-94.
    12. Tschiggerl, Karin & Sledz, Christian & Topic, Milan, 2018. "Considering environmental impacts of energy storage technologies: A life cycle assessment of power-to-gas business models," Energy, Elsevier, vol. 160(C), pages 1091-1100.
    13. Bischi, Aldo & Taccari, Leonardo & Martelli, Emanuele & Amaldi, Edoardo & Manzolini, Giampaolo & Silva, Paolo & Campanari, Stefano & Macchi, Ennio, 2019. "A rolling-horizon optimization algorithm for the long term operational scheduling of cogeneration systems," Energy, Elsevier, vol. 184(C), pages 73-90.
    14. Blanco, Herib & Faaij, André, 2018. "A review at the role of storage in energy systems with a focus on Power to Gas and long-term storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1049-1086.
    15. Fred Glover, 1975. "Improved Linear Integer Programming Formulations of Nonlinear Integer Problems," Management Science, INFORMS, vol. 22(4), pages 455-460, December.
    16. Wakui, Tetsuya & Kawayoshi, Hiroki & Yokoyama, Ryohei & Aki, Hirohisa, 2016. "Operation management of residential energy-supplying networks based on optimization approaches," Applied Energy, Elsevier, vol. 183(C), pages 340-357.
    17. Wakui, Tetsuya & Sawada, Kento & Yokoyama, Ryohei & Aki, Hirohisa, 2019. "Predictive management for energy supply networks using photovoltaics, heat pumps, and battery by two-stage stochastic programming and rule-based control," Energy, Elsevier, vol. 179(C), pages 1302-1319.
    18. Wakui, Tetsuya & Yokoyama, Ryohei, 2015. "Impact analysis of sampling time interval and battery installation on optimal operational planning of residential cogeneration systems without electric power export," Energy, Elsevier, vol. 81(C), pages 120-136.
    19. Gabrielli, Paolo & Gazzani, Matteo & Martelli, Emanuele & Mazzotti, Marco, 2018. "Optimal design of multi-energy systems with seasonal storage," Applied Energy, Elsevier, vol. 219(C), pages 408-424.
    20. Luthander, Rasmus & Widén, Joakim & Nilsson, Daniel & Palm, Jenny, 2015. "Photovoltaic self-consumption in buildings: A review," Applied Energy, Elsevier, vol. 142(C), pages 80-94.
    21. Köfinger, M. & Schmidt, R.R. & Basciotti, D. & Terreros, O. & Baldvinsson, I. & Mayrhofer, J. & Moser, S. & Tichler, R. & Pauli, H., 2018. "Simulation based evaluation of large scale waste heat utilization in urban district heating networks: Optimized integration and operation of a seasonal storage," Energy, Elsevier, vol. 159(C), pages 1161-1174.
    22. Abdollahi, Elnaz & Lahdelma, Risto, 2020. "Decomposition method for optimizing long-term multi-area energy production with heat and power storages," Applied Energy, Elsevier, vol. 260(C).
    23. Baumgärtner, Nils & Shu, David & Bahl, Björn & Hennen, Maike & Hollermann, Dinah Elena & Bardow, André, 2020. "DeLoop: Decomposition-based Long-term operational optimization of energy systems with time-coupling constraints," Energy, Elsevier, vol. 198(C).
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