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New rolling horizon optimization approaches to balance short-term and long-term decisions: An application to energy planning

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  • Cuisinier, Étienne
  • Lemaire, Pierre
  • Penz, Bernard
  • Ruby, Alain
  • Bourasseau, Cyril

Abstract

The planning of complex systems such as energy systems calls for multiple and recurrent operational decisions depending on the present situation as well as future trends. Such decisions can be optimized with rolling-horizon approaches where most immediate decisions are fixed, based on current previsions, while next decisions are made at further optimization steps with updated information. In this paper, focus on cases where long-term decisions have to be balanced with detailed short-term decisions to insure operational realism. On such problems, standard rolling horizon approaches are hard to solve due to the substantial increase of the temporal dimension. To overstep this issue, new approaches to balance short and long-term decisions. Two modelling approaches, based on aggregated time steps, are proposed and tested on an energy production problem where energy can be stored seasonally. Approaches are compared to benchmarks approaches (myopic and a posteriori optimization), and a sensitivity analysis is performed. Both approaches are promising and correspond to different compromises between the model complexity, computation times and solution quality.

Suggested Citation

  • Cuisinier, Étienne & Lemaire, Pierre & Penz, Bernard & Ruby, Alain & Bourasseau, Cyril, 2022. "New rolling horizon optimization approaches to balance short-term and long-term decisions: An application to energy planning," Energy, Elsevier, vol. 245(C).
    • Handle: RePEc:eee:energy:v:245:y:2022:i:c:s036054422103022x
    DOI: 10.1016/j.energy.2021.122773
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    References listed on IDEAS

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    1. Schulze, Tim & McKinnon, Ken, 2016. "The value of stochastic programming in day-ahead and intra-day generation unit commitment," Energy, Elsevier, vol. 101(C), pages 592-605.
    2. Zhou, Min & Wang, Bo & Watada, Junzo, 2019. "Deep learning-based rolling horizon unit commitment under hybrid uncertainties," Energy, Elsevier, vol. 186(C).
    3. Shin, Joohyun & Lee, Jay H. & Realff, Matthew J., 2017. "Operational planning and optimal sizing of microgrid considering multi-scale wind uncertainty," Applied Energy, Elsevier, vol. 195(C), pages 616-633.
    4. Lamaison, Nicolas & Collette, Simon & Vallée, Mathieu & Bavière, Roland, 2019. "Storage influence in a combined biomass and power-to-heat district heating production plant," Energy, Elsevier, vol. 186(C).
    5. Ignacio Blanco & Daniela Guericke & Anders N. Andersen & Henrik Madsen, 2018. "Operational Planning and Bidding for District Heating Systems with Uncertain Renewable Energy Production," Energies, MDPI, vol. 11(12), pages 1-26, November.
    6. Suresh Chand & Vernon Ning Hsu & Suresh Sethi, 2002. "Forecast, Solution, and Rolling Horizons in Operations Management Problems: A Classified Bibliography," Manufacturing & Service Operations Management, INFORMS, vol. 4(1), pages 25-43, September.
    7. Ommen, Torben & Markussen, Wiebke Brix & Elmegaard, Brian, 2014. "Comparison of linear, mixed integer and non-linear programming methods in energy system dispatch modelling," Energy, Elsevier, vol. 74(C), pages 109-118.
    8. Awi Federgruen & Michal Tzur, 1994. "Minimal Forecast Horizons and a New Planning Procedure for the General Dynamic Lot Sizing Model: Nervousness Revisited," Operations Research, INFORMS, vol. 42(3), pages 456-468, June.
    9. Gijs J. H. de Goeijen & Gerard J. M. Smit & Johann L. Hurink, 2017. "Improving an Integer Linear Programming Model of an Ecovat Buffer by Adding Long-Term Planning," Energies, MDPI, vol. 10(12), pages 1-18, December.
    10. 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.
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    1. Cuisinier, E. & Lemaire, P. & Ruby, A. & Bourasseau, C. & Penz, B., 2023. "Impact of operational modelling choices on techno-economic modelling of local energy systems," Energy, Elsevier, vol. 276(C).

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