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Evaluation of Cyprus’ Electricity Generation Planning Using Mean-Variance Portfolio Theory

Author

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  • Neoklis Rodoulis

    (PwC London, UK)

Abstract

This paper utilises Mean-Variance Portfolio (MVP) theory, originally developed for financial portfolios, to evaluate the planned electricity generation mix for the country of Cyprus. The current generation mix, which consists entirely of oil, was found to be highly inefficient, exposing the country to unnecessary price risk and higher costs. Results show that if 60% of the oil in the generation mix is replaced with natural gas, the cost of electricity generation will be reduced by 30% and the variability of the cost will be reduced by 15%. The addition of a 10% share of wind to the oil-gas portfolio was found to reduce the overall risk by up to 8%, without imposing any extra cost. The potential diversification into coal was deemed to be doubtful due to its sensitivity to the price of carbon dioxide (CO2) and its environmental impact.

Suggested Citation

  • Neoklis Rodoulis, 2010. "Evaluation of Cyprus’ Electricity Generation Planning Using Mean-Variance Portfolio Theory," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 4(2), pages 25-42, December.
    • Handle: RePEc:erc:cypepr:v:4:y:2010:i:2:p:25-42
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    File URL: https://www.ucy.ac.cy/erc/documents/Rodoulis_Full_Text.pdf
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    Citations

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    Cited by:

    1. deLlano-Paz, Fernando & Martínez Fernandez, Paulino & Soares, Isabel, 2016. "Addressing 2030 EU policy framework for energy and climate: Cost, risk and energy security issues," Energy, Elsevier, vol. 115(P2), pages 1347-1360.
    2. 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.
    3. Unni, Arjun C. & Ongsakul, Weerakorn & Madhu M., Nimal, 2020. "Fuzzy-based novel risk and reward definition applied for optimal generation-mix estimation," Renewable Energy, Elsevier, vol. 148(C), pages 665-673.
    4. Yongbum Kwon & Hyeji Lee & Heekwan Lee, 2018. "Implication of the cluster analysis using greenhouse gas emissions of Asian countries to climate change mitigation," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 23(8), pages 1225-1249, December.
    5. deLlano-Paz, Fernando & Calvo-Silvosa, Anxo & Antelo, Susana Iglesias & Soares, Isabel, 2017. "Energy planning and modern portfolio theory: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 636-651.
    6. Fernando deLlano-Paz & Paulino Martinez Fernandez & Isabel Soares, 2016. "The effects of different CCS technological scenarios on EU low-carbon generation mix," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 18(5), pages 1477-1500, October.
    7. de-Llano Paz, Fernando & Antelo, Susana Iglesias & Calvo Silvosa, Anxo & Soares, Isabel, 2014. "The technological and environmental efficiency of the EU-27 power mix: An evaluation based on MPT," Energy, Elsevier, vol. 69(C), pages 67-81.

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