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Impact of operational modelling choices on techno-economic modelling of local energy systems

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  • Cuisinier, E.
  • Lemaire, P.
  • Ruby, A.
  • Bourasseau, C.
  • Penz, B.

Abstract

Many techno-economic studies for the pre-design of local energy systems rely on mathematical programming. This comes with several modelling choices including simplified technological and economical models, temporal and spatial resolutions, or perfect foresight assumptions. On the basis of a single case study with complex decision making due to interdependent time scales, this paper shows the importance of evaluating and comparing the (cross-)impacts of the different modelling choices. The modelling choices tested are the inclusion of flexibility costs and constraints, the use of representative periods, the use of different methods to optimise operational decisions (including various rolling horizon methods), and the consideration of forecasts errors or not. The results illustrate the impact that flexibility costs and constraints can have and how they determine alternative modelling choices. They show under which condition representative periods can be used without introducing strong biases on the results. Finally, different rolling horizon strategies are compared, concluding on the validity of the perfect foresight assumption on the case. Results are discussed in terms of performance, validity, and computation times.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:276:y:2023:i:c:s0360544223009933
    DOI: 10.1016/j.energy.2023.127599
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    References listed on IDEAS

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    1. Renaldi, Renaldi & Friedrich, Daniel, 2017. "Multiple time grids in operational optimisation of energy systems with short- and long-term thermal energy storage," Energy, Elsevier, vol. 133(C), pages 784-795.
    2. Pfenninger, Stefan, 2017. "Dealing with multiple decades of hourly wind and PV time series in energy models: A comparison of methods to reduce time resolution and the planning implications of inter-annual variability," Applied Energy, Elsevier, vol. 197(C), pages 1-13.
    3. Frew, Bethany A. & Jacobson, Mark Z., 2016. "Temporal and spatial tradeoffs in power system modeling with assumptions about storage: An application of the POWER model," Energy, Elsevier, vol. 117(P1), pages 198-213.
    4. Felten, Björn & Weber, Christoph, 2018. "The value(s) of flexible heat pumps – Assessment of technical and economic conditions," Applied Energy, Elsevier, vol. 228(C), pages 1292-1319.
    5. Alanne, Kari & Saari, Arto, 2006. "Distributed energy generation and sustainable development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(6), pages 539-558, December.
    6. Yokoyama, Ryohei & Shinano, Yuji & Wakayama, Yuki & Wakui, Tetsuya, 2019. "Model reduction by time aggregation for optimal design of energy supply systems by an MILP hierarchical branch and bound method," Energy, Elsevier, vol. 181(C), pages 782-792.
    7. Lund, Henrik & Østergaard, Poul Alberg & Connolly, David & Mathiesen, Brian Vad, 2017. "Smart energy and smart energy systems," Energy, Elsevier, vol. 137(C), pages 556-565.
    8. Nérot, B. & Lamaison, N. & Mabrouk, M.T. & Bavière, R. & Lacarrière, B., 2023. "Optimization framework for evaluating urban thermal systems potential," Energy, Elsevier, vol. 270(C).
    9. 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.
    10. 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).
    11. Gabrielli, Paolo & Fürer, Florian & Mavromatidis, Georgios & Mazzotti, Marco, 2019. "Robust and optimal design of multi-energy systems with seasonal storage through uncertainty analysis," Applied Energy, Elsevier, vol. 238(C), pages 1192-1210.
    12. 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).
    Full references (including those not matched with items on IDEAS)

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