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Can We Rely on Open-Source Energy System Optimization Models? The TEMOA-Italy Case Study

Author

Listed:
  • Matteo Nicoli

    (MAHTEP Group, Department of Energy “Galileo Ferraris”, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy)

  • Francesco Gracceva

    (Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Lungotevere Thaon di Revel 76, 00196 Rome, Italy)

  • Daniele Lerede

    (MAHTEP Group, Department of Energy “Galileo Ferraris”, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy)

  • Laura Savoldi

    (MAHTEP Group, Department of Energy “Galileo Ferraris”, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy)

Abstract

Energy system models have become crucial to assess the effectiveness of possible energy policies in pursuing the declared environmental objectives. Among bottom-up models, the tools most widely used by researchers and institutions to perform scenario analyses and policy evaluations rely on commercial software and closed databases, limiting the transparency of the studies. The purpose of this work is to demonstrate that open-source tools, relying on open databases, can be used as a valid alternative to commercial tools, getting equivalent results not only for simple case studies as done so far, but also for complex (national, regional, or multi-regional) reference energy systems. Working on the already available open TEMOA optimization framework, a bottom-up technology-rich model is developed here for the Italian reference energy system on an extended TEMOA version, comparable in detail and complexity to the equivalent TIMES framework. The accuracy of the novel TEMOA-Italy model in a business-as-usual scenario is assessed, showing that the average relative differences with respect to the consolidated TIMES-Italy results are in the order of few percent. The open-source model, available on Github, is now ready for the test and implementation of new optimization paradigms, which was not possible in the TIMES framework.

Suggested Citation

  • Matteo Nicoli & Francesco Gracceva & Daniele Lerede & Laura Savoldi, 2022. "Can We Rely on Open-Source Energy System Optimization Models? The TEMOA-Italy Case Study," Energies, MDPI, vol. 15(18), pages 1-37, September.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6505-:d:907889
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    References listed on IDEAS

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    1. Falke, Tobias & Krengel, Stefan & Meinerzhagen, Ann-Kathrin & Schnettler, Armin, 2016. "Multi-objective optimization and simulation model for the design of distributed energy systems," Applied Energy, Elsevier, vol. 184(C), pages 1508-1516.
    2. Dhakouani, Asma & Znouda, Essia & Bouden, Chiheb, 2019. "Impacts of energy efficiency policies on the integration of renewable energy," Energy Policy, Elsevier, vol. 133(C).
    3. Lerede, D. & Bustreo, C. & Gracceva, F. & Saccone, M. & Savoldi, L., 2021. "Techno-economic and environmental characterization of industrial technologies for transparent bottom-up energy modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    4. Anjo, João & Neves, Diana & Silva, Carlos & Shivakumar, Abhishek & Howells, Mark, 2018. "Modeling the long-term impact of demand response in energy planning: The Portuguese electric system case study," Energy, Elsevier, vol. 165(PA), pages 456-468.
    5. Antonio Oliva & Francesco Gracceva & Daniele Lerede & Matteo Nicoli & Laura Savoldi, 2021. "Projection of Post-Pandemic Italian Industrial Production through Vector AutoRegressive Models," Energies, MDPI, vol. 14(17), pages 1-18, September.
    6. Welsch, Manuel & Deane, Paul & Howells, Mark & Ó Gallachóir, Brian & Rogan, Fionn & Bazilian, Morgan & Rogner, Hans-Holger, 2014. "Incorporating flexibility requirements into long-term energy system models – A case study on high levels of renewable electricity penetration in Ireland," Applied Energy, Elsevier, vol. 135(C), pages 600-615.
    7. Daniele Lerede & Chiara Bustreo & Francesco Gracceva & Yolanda Lechón & Laura Savoldi, 2020. "Analysis of the Effects of Electrification of the Road Transport Sector on the Possible Penetration of Nuclear Fusion in the Long-Term European Energy Mix," Energies, MDPI, vol. 13(14), pages 1-25, July.
    8. Pfenninger, Stefan & DeCarolis, Joseph & Hirth, Lion & Quoilin, Sylvain & Staffell, Iain, 2017. "The importance of open data and software: Is energy research lagging behind?," Energy Policy, Elsevier, vol. 101(C), pages 211-215.
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