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An Energy Cost Assessment of Future Energy Scenarios: A Case Study on San Pietro Island

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  • Alberto Vargiu

    (MOREnergy Lab, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
    Dipartimento di Ingegneria Meccanica e Aerospaziale, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy)

  • Riccardo Novo

    (MOREnergy Lab, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
    Dipartimento di Ingegneria Meccanica e Aerospaziale, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
    Energy Center Lab, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy)

  • Claudio Moscoloni

    (MOREnergy Lab, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
    Dipartimento di Ingegneria Meccanica e Aerospaziale, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy)

  • Enrico Giglio

    (MOREnergy Lab, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
    Dipartimento di Ingegneria Meccanica e Aerospaziale, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
    Energy Center Lab, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy)

  • Giuseppe Giorgi

    (MOREnergy Lab, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
    Dipartimento di Ingegneria Meccanica e Aerospaziale, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy)

  • Giuliana Mattiazzo

    (MOREnergy Lab, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
    Dipartimento di Ingegneria Meccanica e Aerospaziale, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
    Energy Center Lab, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy)

Abstract

The need for a clean and affordable energy supply is a major challenge of the current century. The tough shift toward a sustainable energy mix becomes even more problematic when facing realities that lack infrastructures and financing, such as small islands. Energy modeling and planning is crucial at this early stage of the ecological transition. For this reason, this article aims to improve an established long-run energy model framework, known as “OSeMOSYS,” with an add-on tool able to estimate different types of Levelized Cost Of Electricity (LCOE): a real and theoretical LCOE of each technology and a real and theoretical system LCOE. This tool fills a gap in most modeling frameworks characterized by a lack of information when evaluating energy costs and aims at guiding policymakers to the most appropriate solution. The model is then used to predict future energy scenarios for the island of San Pietro, in Sardinia, which was chosen as a case study. Four energy scenarios with a time horizon from 2020 to 2050—the Business-As-Usual (BAU) scenario, the Current Policy Projection (CPP) scenario, the Sustainable Growth (SG) scenario, and the Self-Sufficient-Renewable (SSR) scenario—are explored and ranked according to the efforts made in them to achieve an energy transition. Results demonstrates the validity of the tool, showing that, in the long run, the average LCOE of the system benefits from the installation of RES plants, passing from 49.1 €/MWh in 2050 in the BAU scenario to 48.8 €/MWh in the ambitious SG scenario. On the other hand, achieving carbon neutrality and the island’s energy independence brings the LCOE to 531.5 €/MWh, questioning the convenience of large storage infrastructures in San Pietro and opening up future work on the exploration of different storage systems.

Suggested Citation

  • Alberto Vargiu & Riccardo Novo & Claudio Moscoloni & Enrico Giglio & Giuseppe Giorgi & Giuliana Mattiazzo, 2022. "An Energy Cost Assessment of Future Energy Scenarios: A Case Study on San Pietro Island," Energies, MDPI, vol. 15(13), pages 1-23, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:13:p:4535-:d:844240
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    References listed on IDEAS

    as
    1. Riccardo Novo & Francesco Demetrio Minuto & Giovanni Bracco & Giuliana Mattiazzo & Romano Borchiellini & Andrea Lanzini, 2022. "Supporting Decarbonization Strategies of Local Energy Systems by De-Risking Investments in Renewables: A Case Study on Pantelleria Island," Energies, MDPI, vol. 15(3), pages 1-25, February.
    2. Bellocchi, Sara & Manno, Michele & Noussan, Michel & Prina, Matteo Giacomo & Vellini, Michela, 2020. "Electrification of transport and residential heating sectors in support of renewable penetration: Scenarios for the Italian energy system," Energy, Elsevier, vol. 196(C).
    3. Pfenninger, Stefan & Hirth, Lion & Schlecht, Ingmar & Schmid, Eva & Wiese, Frauke & Brown, Tom & Davis, Chris & Gidden, Matthew & Heinrichs, Heidi & Heuberger, Clara & Hilpert, Simon & Krien, Uwe & Ma, 2018. "Opening the black box of energy modelling: Strategies and lessons learned," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 19, pages 63-71.
    4. Mélusine Boon-Falleur & Aurore Grandin & Nicolas Baumard & Coralie Chevallier, 2022. "Leveraging social cognition to promote effective climate change mitigation," Nature Climate Change, Nature, vol. 12(4), pages 332-338, April.
    5. Reichenberg, Lina & Hedenus, Fredrik & Odenberger, Mikael & Johnsson, Filip, 2018. "The marginal system LCOE of variable renewables – Evaluating high penetration levels of wind and solar in Europe," Energy, Elsevier, vol. 152(C), pages 914-924.
    6. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.
    7. Ueckerdt, Falko & Hirth, Lion & Luderer, Gunnar & Edenhofer, Ottmar, 2013. "System LCOE: What are the costs of variable renewables?," Energy, Elsevier, vol. 63(C), pages 61-75.
    8. Timmons, D. & Dhunny, A.Z. & Elahee, K. & Havumaki, B. & Howells, M. & Khoodaruth, A. & Lema-Driscoll, A.K. & Lollchund, M.R. & Ramgolam, Y.K. & Rughooputh, S.D.D.V. & Surroop, D., 2019. "Cost minimization for fully renewable electricity systems: A Mauritius case study," Energy Policy, Elsevier, vol. 133(C).
    9. Van der Voort, E, 1982. "The EFOM 12C energy supply model within the EC modelling system," Omega, Elsevier, vol. 10(5), pages 507-523.
    10. Howells, Mark & Rogner, Holger & Strachan, Neil & Heaps, Charles & Huntington, Hillard & Kypreos, Socrates & Hughes, Alison & Silveira, Semida & DeCarolis, Joe & Bazillian, Morgan & Roehrl, Alexander, 2011. "OSeMOSYS: The Open Source Energy Modeling System: An introduction to its ethos, structure and development," Energy Policy, Elsevier, vol. 39(10), pages 5850-5870, October.
    11. Welsch, M. & Howells, M. & Bazilian, M. & DeCarolis, J.F. & Hermann, S. & Rogner, H.H., 2012. "Modelling elements of Smart Grids – Enhancing the OSeMOSYS (Open Source Energy Modelling System) code," Energy, Elsevier, vol. 46(1), pages 337-350.
    12. Volker Krey, 2014. "Global energy-climate scenarios and models: a review," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 3(4), pages 363-383, July.
    13. Comodi, G. & Cioccolanti, L. & Gargiulo, M., 2012. "Municipal scale scenario: Analysis of an Italian seaside town with MarkAL-TIMES," Energy Policy, Elsevier, vol. 41(C), pages 303-315.
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