IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i12p3255-d375510.html
   My bibliography  Save this article

Multi-Objective Optimization Model EPLANopt for Energy Transition Analysis and Comparison with Climate-Change Scenarios

Author

Listed:
  • Matteo Giacomo Prina

    (EURAC Research, Institute for Renewable Energy, Viale Druso 1, I-39100 Bolzano, Italy)

  • Giampaolo Manzolini

    (Dipartimento di energia, Politecnico di Milano, Via Lambruschini, 4, 20156 Milano (MI), Italy)

  • David Moser

    (EURAC Research, Institute for Renewable Energy, Viale Druso 1, I-39100 Bolzano, Italy)

  • Roberto Vaccaro

    (EURAC Research, Institute for Renewable Energy, Viale Druso 1, I-39100 Bolzano, Italy)

  • Wolfram Sparber

    (EURAC Research, Institute for Renewable Energy, Viale Druso 1, I-39100 Bolzano, Italy)

Abstract

The modeling of energy systems with high penetration of renewables is becoming more relevant due to environmental and security issues. Researchers need to support policy makers in the development of energy policies through results from simulating tools able to guide them. The EPLANopt model couples a multi-objective evolutionary algorithm to EnergyPLAN simulation software to study the future best energy mix. In this study, EPLANopt is applied at country level to the Italian case study to assess the best configurations of the energy system in 2030. A scenario, the result of the optimization, is selected and compared to the Italian integrated energy and climate action plan scenario. It allows a further reduction of CO 2 emissions equal to 10% at the same annual costs of the Italian integrated energy and climate action plan scenario. Both these results are then compared to climate change scenarios through the carbon budget indicator. This comparison shows the difficulties to meet the Paris Agreement target of limiting the temperature increase to 1.5 °C. The results also show that this target can only be met through an increase in the total annual costs in the order of 25% with respect to the integrated energy and climate action plan scenario. However, the study also shows how the shift in expenditure from fossil fuels, external expenses, to investment on the national territory represents an opportunity to enhance the national economy.

Suggested Citation

  • Matteo Giacomo Prina & Giampaolo Manzolini & David Moser & Roberto Vaccaro & Wolfram Sparber, 2020. "Multi-Objective Optimization Model EPLANopt for Energy Transition Analysis and Comparison with Climate-Change Scenarios," Energies, MDPI, vol. 13(12), pages 1-22, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3255-:d:375510
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/12/3255/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/12/3255/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Connolly, D. & Lund, H. & Mathiesen, B.V., 2016. "Smart Energy Europe: The technical and economic impact of one potential 100% renewable energy scenario for the European Union," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1634-1653.
    2. Alves, M. & Segurado, R. & Costa, M., 2019. "Increasing the penetration of renewable energy sources in isolated islands through the interconnection of their power systems. The case of Pico and Faial islands, Azores," Energy, Elsevier, vol. 182(C), pages 502-510.
    3. Mahbub, Md Shahriar & Viesi, Diego & Crema, Luigi, 2016. "Designing optimized energy scenarios for an Italian Alpine valley: the case of Giudicarie Esteriori," Energy, Elsevier, vol. 116(P1), pages 236-249.
    4. Joeri Rogelj & Piers M. Forster & Elmar Kriegler & Christopher J. Smith & Roland Séférian, 2019. "Estimating and tracking the remaining carbon budget for stringent climate targets," Nature, Nature, vol. 571(7765), pages 335-342, July.
    5. Mahbub, Md Shahriar & Cozzini, Marco & Østergaard, Poul Alberg & Alberti, Fabrizio, 2016. "Combining multi-objective evolutionary algorithms and descriptive analytical modelling in energy scenario design," Applied Energy, Elsevier, vol. 164(C), pages 140-151.
    6. Mazzoni, Stefano & Ooi, Sean & Nastasi, Benedetto & Romagnoli, Alessandro, 2019. "Energy storage technologies as techno-economic parameters for master-planning and optimal dispatch in smart multi energy systems," Applied Energy, Elsevier, vol. 254(C).
    7. Andrea Herbst & Felipe Andrés Toro & Felix Reitze & Eberhard Jochem, 2012. "Introduction to Energy Systems Modelling," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 148(II), pages 111-135, June.
    8. Komušanac, Ivan & Ćosić, Boris & Duić, Neven, 2016. "Impact of high penetration of wind and solar PV generation on the country power system load: The case study of Croatia," Applied Energy, Elsevier, vol. 184(C), pages 1470-1482.
    9. Connolly, D. & Lund, H. & Mathiesen, B.V. & Pican, E. & Leahy, M., 2012. "The technical and economic implications of integrating fluctuating renewable energy using energy storage," Renewable Energy, Elsevier, vol. 43(C), pages 47-60.
    10. Prina, Matteo Giacomo & Manzolini, Giampaolo & Moser, David & Nastasi, Benedetto & Sparber, Wolfram, 2020. "Classification and challenges of bottom-up energy system models - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 129(C).
    11. Francesco Mancini & Benedetto Nastasi, 2020. "Solar Energy Data Analytics: PV Deployment and Land Use," Energies, MDPI, vol. 13(2), pages 1-18, January.
    12. Groppi, D. & Astiaso Garcia, D. & Lo Basso, G. & De Santoli, L., 2019. "Synergy between smart energy systems simulation tools for greening small Mediterranean islands," Renewable Energy, Elsevier, vol. 135(C), pages 515-524.
    13. Prina, Matteo Giacomo & Fanali, Lorenzo & Manzolini, Giampaolo & Moser, David & Sparber, Wolfram, 2018. "Incorporating combined cycle gas turbine flexibility constraints and additional costs into the EPLANopt model: The Italian case study," Energy, Elsevier, vol. 160(C), pages 33-43.
    14. Nastasi, Benedetto & Lo Basso, Gianluigi, 2016. "Hydrogen to link heat and electricity in the transition towards future Smart Energy Systems," Energy, Elsevier, vol. 110(C), pages 5-22.
    15. Konak, Abdullah & Coit, David W. & Smith, Alice E., 2006. "Multi-objective optimization using genetic algorithms: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 992-1007.
    16. Prina, Matteo Giacomo & Cozzini, Marco & Garegnani, Giulia & Manzolini, Giampaolo & Moser, David & Filippi Oberegger, Ulrich & Pernetti, Roberta & Vaccaro, Roberto & Sparber, Wolfram, 2018. "Multi-objective optimization algorithm coupled to EnergyPLAN software: The EPLANopt model," Energy, Elsevier, vol. 149(C), pages 213-221.
    17. Connolly, D. & Lund, H. & Mathiesen, B.V. & Leahy, M., 2011. "The first step towards a 100% renewable energy-system for Ireland," Applied Energy, Elsevier, vol. 88(2), pages 502-507, February.
    18. Michel Noussan & Roberta Roberto & Benedetto Nastasi, 2018. "Performance Indicators of Electricity Generation at Country Level—The Case of Italy," Energies, MDPI, vol. 11(3), pages 1-14, March.
    19. Prina, Matteo Giacomo & Lionetti, Matteo & Manzolini, Giampaolo & Sparber, Wolfram & Moser, David, 2019. "Transition pathways optimization methodology through EnergyPLAN software for long-term energy planning," Applied Energy, Elsevier, vol. 235(C), pages 356-368.
    20. Fernandes, Liliana & Ferreira, Paula, 2014. "Renewable energy scenarios in the Portuguese electricity system," Energy, Elsevier, vol. 69(C), pages 51-57.
    21. Marczinkowski, Hannah Mareike & Østergaard, Poul Alberg, 2019. "Evaluation of electricity storage versus thermal storage as part of two different energy planning approaches for the islands Samsø and Orkney," Energy, Elsevier, vol. 175(C), pages 505-514.
    22. Poncelet, Kris & Delarue, Erik & Six, Daan & Duerinck, Jan & D’haeseleer, William, 2016. "Impact of the level of temporal and operational detail in energy-system planning models," Applied Energy, Elsevier, vol. 162(C), pages 631-643.
    23. Batas Bjelić, Ilija & Rajaković, Nikola, 2015. "Simulation-based optimization of sustainable national energy systems," Energy, Elsevier, vol. 91(C), pages 1087-1098.
    24. Michel Noussan & Benedetto Nastasi, 2018. "Data Analysis of Heating Systems for Buildings—A Tool for Energy Planning, Policies and Systems Simulation," Energies, MDPI, vol. 11(1), pages 1-15, January.
    25. Connolly, D. & Lund, H. & Mathiesen, B.V. & Leahy, M., 2010. "Modelling the existing Irish energy-system to identify future energy costs and the maximum wind penetration feasible," Energy, Elsevier, vol. 35(5), pages 2164-2173.
    26. Thiel, Christian & Perujo, Adolfo & Mercier, Arnaud, 2010. "Cost and CO2 aspects of future vehicle options in Europe under new energy policy scenarios," Energy Policy, Elsevier, vol. 38(11), pages 7142-7151, November.
    27. Lund, H. & Mathiesen, B.V., 2009. "Energy system analysis of 100% renewable energy systems—The case of Denmark in years 2030 and 2050," Energy, Elsevier, vol. 34(5), pages 524-531.
    28. Ćosić, Boris & Krajačić, Goran & Duić, Neven, 2012. "A 100% renewable energy system in the year 2050: The case of Macedonia," Energy, Elsevier, vol. 48(1), pages 80-87.
    29. Mathiesen, B.V. & Lund, H. & Connolly, D. & Wenzel, H. & Østergaard, P.A. & Möller, B. & Nielsen, S. & Ridjan, I. & Karnøe, P. & Sperling, K. & Hvelplund, F.K., 2015. "Smart Energy Systems for coherent 100% renewable energy and transport solutions," Applied Energy, Elsevier, vol. 145(C), pages 139-154.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Herc, Luka & Pfeifer, Antun & Duić, Neven, 2022. "Optimization of the possible pathways for gradual energy system decarbonization," Renewable Energy, Elsevier, vol. 193(C), pages 617-633.
    2. Herc, Luka & Pfeifer, Antun & Duić, Neven & Wang, Fei, 2022. "Economic viability of flexibility options for smart energy systems with high penetration of renewable energy," Energy, Elsevier, vol. 252(C).
    3. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    4. Chang, Miguel & Lund, Henrik & Thellufsen, Jakob Zinck & Østergaard, Poul Alberg, 2023. "Perspectives on purpose-driven coupling of energy system models," Energy, Elsevier, vol. 265(C).
    5. He, Zhenglei & Liu, Chang & Wang, Yutao & Wang, Xu & Man, Yi, 2023. "Optimal operation of wind-solar-thermal collaborative power system considering carbon trading and energy storage," Applied Energy, Elsevier, vol. 352(C).
    6. Finke, Jonas & Bertsch, Valentin, 2023. "Implementing a highly adaptable method for the multi-objective optimisation of energy systems," Applied Energy, Elsevier, vol. 332(C).
    7. Besagni, Giorgio & Premoli Vilà, Lidia & Borgarello, Marco & Trabucchi, Andrea & Merlo, Marco & Rodeschini, Jacopo & Finazzi, Francesco, 2021. "Electrification pathways of the Italian residential sector under socio-demographic constrains: Looking towards 2040," Energy, Elsevier, vol. 217(C).
    8. Johannsen, Rasmus Magni & Prina, Matteo Giacomo & Østergaard, Poul Alberg & Mathiesen, Brian Vad & Sparber, Wolfram, 2023. "Municipal energy system modelling – A practical comparison of optimisation and simulation approaches," Energy, Elsevier, vol. 269(C).
    9. Finke, Jonas & Bertsch, Valentin, 2022. "Implementing a highly adaptable method for the multi-objective optimisation of energy systems," MPRA Paper 115504, University Library of Munich, Germany.
    10. Thimet, P.J. & Mavromatidis, G., 2022. "Review of model-based electricity system transition scenarios: An analysis for Switzerland, Germany, France, and Italy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    11. Benedetto Nastasi & Massimiliano Manfren & Michel Noussan, 2021. "Open Data and Models for Energy and Environment," Energies, MDPI, vol. 14(15), pages 1-2, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    2. Prina, Matteo Giacomo & Groppi, Daniele & Nastasi, Benedetto & Garcia, Davide Astiaso, 2021. "Bottom-up energy system models applied to sustainable islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    3. Prina, Matteo Giacomo & Fanali, Lorenzo & Manzolini, Giampaolo & Moser, David & Sparber, Wolfram, 2018. "Incorporating combined cycle gas turbine flexibility constraints and additional costs into the EPLANopt model: The Italian case study," Energy, Elsevier, vol. 160(C), pages 33-43.
    4. Prina, Matteo Giacomo & Manzolini, Giampaolo & Moser, David & Nastasi, Benedetto & Sparber, Wolfram, 2020. "Classification and challenges of bottom-up energy system models - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 129(C).
    5. Prina, Matteo Giacomo & Casalicchio, Valeria & Kaldemeyer, Cord & Manzolini, Giampaolo & Moser, David & Wanitschke, Alexander & Sparber, Wolfram, 2020. "Multi-objective investment optimization for energy system models in high temporal and spatial resolution," Applied Energy, Elsevier, vol. 264(C).
    6. Prina, Matteo Giacomo & Cozzini, Marco & Garegnani, Giulia & Manzolini, Giampaolo & Moser, David & Filippi Oberegger, Ulrich & Pernetti, Roberta & Vaccaro, Roberto & Sparber, Wolfram, 2018. "Multi-objective optimization algorithm coupled to EnergyPLAN software: The EPLANopt model," Energy, Elsevier, vol. 149(C), pages 213-221.
    7. Bellocchi, S. & De Iulio, R. & Guidi, G. & Manno, M. & Nastasi, B. & Noussan, M. & Prina, M.G. & Roberto, R., 2020. "Analysis of smart energy system approach in local alpine regions - A case study in Northern Italy," Energy, Elsevier, vol. 202(C).
    8. Chang, Miguel & Lund, Henrik & Thellufsen, Jakob Zinck & Østergaard, Poul Alberg, 2023. "Perspectives on purpose-driven coupling of energy system models," Energy, Elsevier, vol. 265(C).
    9. Doepfert, Markus & Castro, Rui, 2021. "Techno-economic optimization of a 100% renewable energy system in 2050 for countries with high shares of hydropower: The case of Portugal," Renewable Energy, Elsevier, vol. 165(P1), pages 491-503.
    10. Viesi, Diego & Crema, Luigi & Mahbub, Md Shahriar & Verones, Sara & Brunelli, Roberto & Baggio, Paolo & Fauri, Maurizio & Prada, Alessandro & Bello, Andrea & Nodari, Benedetta & Silvestri, Silvia & To, 2020. "Integrated and dynamic energy modelling of a regional system: A cost-optimized approach in the deep decarbonisation of the Province of Trento (Italy)," Energy, Elsevier, vol. 209(C).
    11. Borasio, M. & Moret, S., 2022. "Deep decarbonisation of regional energy systems: A novel modelling approach and its application to the Italian energy transition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    12. Arévalo, Paúl & Cano, Antonio & Jurado, Francisco, 2022. "Mitigation of carbon footprint with 100% renewable energy system by 2050: The case of Galapagos islands," Energy, Elsevier, vol. 245(C).
    13. Maruf, Md. Nasimul Islam, 2021. "Open model-based analysis of a 100% renewable and sector-coupled energy system–The case of Germany in 2050," Applied Energy, Elsevier, vol. 288(C).
    14. 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).
    15. Ma, Weiwu & Xue, Xinpei & Liu, Gang, 2018. "Techno-economic evaluation for hybrid renewable energy system: Application and merits," Energy, Elsevier, vol. 159(C), pages 385-409.
    16. Finke, Jonas & Bertsch, Valentin, 2023. "Implementing a highly adaptable method for the multi-objective optimisation of energy systems," Applied Energy, Elsevier, vol. 332(C).
    17. Diesendorf, Mark & Elliston, Ben, 2018. "The feasibility of 100% renewable electricity systems: A response to critics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 318-330.
    18. Groppi, Daniele & Nastasi, Benedetto & Prina, Matteo Giacomo, 2022. "The EPLANoptMAC model to plan the decarbonisation of the maritime transport sector of a small island," Energy, Elsevier, vol. 254(PA).
    19. Bačeković, Ivan & Østergaard, Poul Alberg, 2018. "A smart energy system approach vs a non-integrated renewable energy system approach to designing a future energy system in Zagreb," Energy, Elsevier, vol. 155(C), pages 824-837.
    20. Pastore, Lorenzo Mario & Lo Basso, Gianluigi & Cristiani, Laura & de Santoli, Livio, 2022. "Rising targets to 55% GHG emissions reduction – The smart energy systems approach for improving the Italian energy strategy," Energy, Elsevier, vol. 259(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3255-:d:375510. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.