IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v106y2017icp335-342.html
   My bibliography  Save this article

Exploring the mean-variance portfolio optimization approach for planning wind repowering actions in Spain

Author

Listed:
  • Santos-Alamillos, F.J.
  • Thomaidis, N.S.
  • Usaola-García, J.
  • Ruiz-Arias, J.A.
  • Pozo-Vázquez, D.

Abstract

The repowering of already installed wind farms is considered one of the most promising and cost-effective short-term strategies to scale-up wind capacity. In this study, we apply Markowitz's mean-variance (MV) portfolio optimization theory to explore alternative repowering actions in Spain. The efficient portfolios – a direct outcome of the MV optimization – offer optimal repowering alternatives to current wind farm generation mixes. They deliver the highest possible average power output (yield) for a given level of supply risk. Different repowering scenarios are considered in this paper that range from a full restructuring of the existing wind generation mix to restricting by certain amounts the percentage of down-/uprating of each reference region. Results show that, depending on the configuration of the MV portfolio optimization problem, hourly fluctuations in the aggregate power supply can be reduced as much as 12–31%, while retaining the current level of energy productivity. In addition, for the level of energy supply risk experienced with the existing portfolio of Spanish wind farms; we can derive more efficient mixes that boost-up productivity by 16–55%. This work aims at providing valuable insight for energy policy-making in the direction of optimally repowering future renewable generation.

Suggested Citation

  • Santos-Alamillos, F.J. & Thomaidis, N.S. & Usaola-García, J. & Ruiz-Arias, J.A. & Pozo-Vázquez, D., 2017. "Exploring the mean-variance portfolio optimization approach for planning wind repowering actions in Spain," Renewable Energy, Elsevier, vol. 106(C), pages 335-342.
    • Handle: RePEc:eee:renene:v:106:y:2017:i:c:p:335-342
    DOI: 10.1016/j.renene.2017.01.041
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148117300514
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2017.01.041?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Santos-Alamillos, F.J. & Thomaidis, N.S. & Quesada-Ruiz, S. & Ruiz-Arias, J.A. & Pozo-Vázquez, D., 2016. "Do current wind farms in Spain take maximum advantage of spatiotemporal balancing of the wind resource?," Renewable Energy, Elsevier, vol. 96(PA), pages 574-582.
    2. Roques, Fabien & Hiroux, Céline & Saguan, Marcelo, 2010. "Optimal wind power deployment in Europe--A portfolio approach," Energy Policy, Elsevier, vol. 38(7), pages 3245-3256, July.
    3. Jacobson, Mark Z. & Delucchi, Mark A., 2011. "Providing all global energy with wind, water, and solar power, Part I: Technologies, energy resources, quantities and areas of infrastructure, and materials," Energy Policy, Elsevier, vol. 39(3), pages 1154-1169, March.
    4. Mathiesen, Brian Vad & Lund, Henrik & Karlsson, Kenneth, 2011. "100% Renewable energy systems, climate mitigation and economic growth," Applied Energy, Elsevier, vol. 88(2), pages 488-501, February.
    5. Hirth, Lion & Müller, Simon, 2016. "System-friendly wind power," Energy Economics, Elsevier, vol. 56(C), pages 51-63.
    6. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    7. Sperling, Karl & Hvelplund, Frede & Mathiesen, Brian Vad, 2010. "Evaluation of wind power planning in Denmark – Towards an integrated perspective," Energy, Elsevier, vol. 35(12), pages 5443-5454.
    8. del Río, Pablo & Calvo Silvosa, Anxo & Iglesias Gómez, Guillermo, 2011. "Policies and design elements for the repowering of wind farms: A qualitative analysis of different options," Energy Policy, Elsevier, vol. 39(4), pages 1897-1908, April.
    9. Santos-Alamillos, F.J. & Pozo-Vázquez, D. & Ruiz-Arias, J.A. & Lara-Fanego, V. & Tovar-Pescador, J., 2014. "A methodology for evaluating the spatial variability of wind energy resources: Application to assess the potential contribution of wind energy to baseload power," Renewable Energy, Elsevier, vol. 69(C), pages 147-156.
    10. Meyerhoff, Jürgen & Ohl, Cornelia & Hartje, Volkmar, 2010. "Landscape externalities from onshore wind power," Energy Policy, Elsevier, vol. 38(1), pages 82-92, January.
    11. Santos-Alamillos, F.J. & Pozo-Vázquez, D. & Ruiz-Arias, J.A. & Von Bremen, L. & Tovar-Pescador, J., 2015. "Combining wind farms with concentrating solar plants to provide stable renewable power," Renewable Energy, Elsevier, vol. 76(C), pages 539-550.
    Full references (including those not matched with items on IDEAS)

    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. Santos-Alamillos, F.J. & Thomaidis, N.S. & Quesada-Ruiz, S. & Ruiz-Arias, J.A. & Pozo-Vázquez, D., 2016. "Do current wind farms in Spain take maximum advantage of spatiotemporal balancing of the wind resource?," Renewable Energy, Elsevier, vol. 96(PA), pages 574-582.
    2. Thomaidis, Nikolaos S. & Christodoulou, Theodoros & Santos-Alamillos, Francisco J., 2023. "Handling the risk dimensions of wind energy generation," Applied Energy, Elsevier, vol. 339(C).
    3. Álvarez-García, Francisco J. & Fresno-Schmolk, Gonzalo & OrtizBevia, María J. & Cabos, William & RuizdeElvira, Antonio, 2020. "Reduction of aggregate wind power variability using Empirical Orthogonal Teleconnections: An application in the Iberian Peninsula," Renewable Energy, Elsevier, vol. 159(C), pages 151-161.
    4. Santos-Alamillos, F.J. & Pozo-Vázquez, D. & Ruiz-Arias, J.A. & Lara-Fanego, V. & Tovar-Pescador, J., 2014. "A methodology for evaluating the spatial variability of wind energy resources: Application to assess the potential contribution of wind energy to baseload power," Renewable Energy, Elsevier, vol. 69(C), pages 147-156.
    5. Engeland, Kolbjørn & Borga, Marco & Creutin, Jean-Dominique & François, Baptiste & Ramos, Maria-Helena & Vidal, Jean-Philippe, 2017. "Space-time variability of climate variables and intermittent renewable electricity production – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 600-617.
    6. Ladenburg, Jacob & Termansen, Mette & Hasler, Berit, 2013. "Assessing acceptability of two onshore wind power development schemes: A test of viewshed effects and the cumulative effects of wind turbines," Energy, Elsevier, vol. 54(C), pages 45-54.
    7. Enevoldsen, Peter, 2016. "Onshore wind energy in Northern European forests: Reviewing the risks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1251-1262.
    8. Isabel C. Gil-García & Ana Fernández-Guillamón & M. Socorro García-Cascales & Angel Molina-García, 2021. "A Multi-Factorial Review of Repowering Wind Generation Strategies," Energies, MDPI, vol. 14(19), pages 1-25, October.
    9. Santos-Alamillos, F.J. & Pozo-Vázquez, D. & Ruiz-Arias, J.A. & Von Bremen, L. & Tovar-Pescador, J., 2015. "Combining wind farms with concentrating solar plants to provide stable renewable power," Renewable Energy, Elsevier, vol. 76(C), pages 539-550.
    10. Allan, Grant & Eromenko, Igor & McGregor, Peter & Swales, Kim, 2011. "The regional electricity generation mix in Scotland: A portfolio selection approach incorporating marine technologies," Energy Policy, Elsevier, vol. 39(1), pages 6-22, January.
    11. Sperling, K. & Arler, F., 2020. "Local government innovation in the energy sector: A study of key actors’ strategies and arguments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 126(C).
    12. 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.
    13. 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.
    14. deLlano-Paz, Fernando & Calvo-Silvosa, Anxo & Iglesias Antelo, Susana & Soares, Isabel, 2015. "The European low-carbon mix for 2030: The role of renewable energy sources in an environmentally and socially efficient approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 49-61.
    15. Tafarte, Philip & Lehmann, Paul, 2021. "Quantifying trade-offs for the spatial allocation of onshore wind generation capacity: A case study for Germany," UFZ Discussion Papers 2/2021, Helmholtz Centre for Environmental Research (UFZ), Division of Social Sciences (ÖKUS).
    16. Paulino Martinez-Fernandez & Fernando deLlano-Paz & Anxo Calvo-Silvosa & Isabel Soares, 2018. "Pollutant versus non-pollutant generation technologies: a CML-analogous analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(1), pages 199-212, December.
    17. Chu, Cheng-Ta & Hawkes, Adam D., 2020. "Optimal mix of climate-related energy in global electricity systems," Renewable Energy, Elsevier, vol. 160(C), pages 955-963.
    18. Marrero, Gustavo A. & Puch, Luis A. & Ramos-Real, Francisco J., 2015. "Mean-variance portfolio methods for energy policy risk management," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 246-264.
    19. Zerrahn, Alexander, 2017. "Wind Power and Externalities," Ecological Economics, Elsevier, vol. 141(C), pages 245-260.
    20. Schyska, Bruno U. & Kies, Alexander, 2020. "How regional differences in cost of capital influence the optimal design of power systems," Applied Energy, Elsevier, vol. 262(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:eee:renene:v:106:y:2017:i:c:p:335-342. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.