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The Benefit of Regional Diversification of Cogeneration Investments in Europe: A Mean-Variance Portfolio Analysis

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  • Westner, Günther

    (E.ON Energy Projects GmbH)

  • Madlener, Reinhard

    (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN))

Abstract

The EU Directive 2004/8/EC, concerning the promotion of cogeneration, established principles on how EU member states can support combined heat and power generation (CHP). Up to now, the implementation of these principles into national law has not been uniform, and has led to the adoption of different promotion schemes for CHP across the EU member states. In this paper, we first give an overview of the promotion schemes for CHP in various European countries. In a next step, we take two standard CHP technologies, combined-cycle gas turbines (CCGT-CHP) and engine-CHP, and apply exemplarily four selected support mechanisms used in the four largest European energy markets: feed-in tariffs in Germany; energy efficiency certificates in Italy; benefits through tax reduction in the UK; and purchase obligations for power from CHP generation in France. For contracting companies, it could be of interest to diversify their investment in new CHP facilities regionally over several countries in order to reduce country and regulatory risk. By applying Mean-Variance Portfolio (MVP) theory, we derive characteristic return-risk profiles of the selected CHP technologies in different countries. The results show that the returns on CHP investments differ significantly depending on the country, the support scheme, and the selected technology studied. While a regional diversification of investments in CCGT-CHP does not contribute to reducing portfolio risks, a diversification of investments in engine-CHP can decrease the risk exposure.

Suggested Citation

  • Westner, Günther & Madlener, Reinhard, 2009. "The Benefit of Regional Diversification of Cogeneration Investments in Europe: A Mean-Variance Portfolio Analysis," FCN Working Papers 5/2009, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Mar 2010.
  • Handle: RePEc:ris:fcnwpa:2009_005
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    Cited by:

    1. Hans-Joachim Naegele & Bernd Thomas & Christine Schrade & Andreas Lemmer & Hans Oechsner & Thomas Jungbluth, 2013. "Influence of Maintenance Intervals on Performance and Emissions of a 192 kW el Biogas Gas Otto CHP Unit and Results of Lubricating Oil Quality Tests—Outcome from a Continuous Two-Year Measuring Campai," Energies, MDPI, vol. 6(6), pages 1-21, June.
    2. Westner, Günther & Madlener, Reinhard, 2010. "The benefit of regional diversification of cogeneration investments in Europe: A mean-variance portfolio analysis," Energy Policy, Elsevier, vol. 38(12), pages 7911-7920, December.
    3. Paulino Martinez-Fernandez & Fernando deLlano-Paz & Anxo Calvo-Silvosa & Isabel Soares, 2019. "Assessing Renewable Energy Sources for Electricity (RES-E) Potential Using a CAPM-Analogous Multi-Stage Model," Energies, MDPI, vol. 12(19), pages 1-20, September.
    4. Dominik Kryzia & Marta Kuta & Dominika Matuszewska & Piotr Olczak, 2020. "Analysis of the Potential for Gas Micro-Cogeneration Development in Poland Using the Monte Carlo Method," Energies, MDPI, vol. 13(12), pages 1-24, June.
    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. Moreton, O.R. & Rowley, P.N., 2012. "The feasibility of biomass CHP as an energy and CO2 source for commercial glasshouses," Applied Energy, Elsevier, vol. 96(C), pages 339-346.
    7. Franco, Alessandro & Versace, Michele, 2017. "Optimum sizing and operational strategy of CHP plant for district heating based on the use of composite indicators," Energy, Elsevier, vol. 124(C), pages 258-271.
    8. Carlo Andrea Bollino & Philipp Galkin, 2021. "Energy Security and Portfolio Diversification: Conventional and Novel Perspectives," Energies, MDPI, vol. 14(14), pages 1-24, July.
    9. 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.
    10. Frank A. Wolak, 2016. "Level versus Variability Trade-offs in Wind and Solar Generation Investments: The Case of California," The Energy Journal, International Association for Energy Economics, vol. 0(Bollino-M).
    11. Frank A. Wolak, 2016. "Level versus Variability Trade-offs in Wind and Solar Generation Investments: The Case of California," NBER Working Papers 22494, National Bureau of Economic Research, Inc.
    12. Carlo Mari, 2018. "CO 2 Price Volatility Effects on Optimal Power System Portfolios," Energies, MDPI, vol. 11(7), pages 1-18, July.
    13. 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.
    14. Westner, Günther & Madlener, Reinhard, 2012. "Investment in new power generation under uncertainty: Benefits of CHP vs. condensing plants in a copula-based analysis," Energy Economics, Elsevier, vol. 34(1), pages 31-44.
    15. Adams, R. & Jamasb, J., 2016. "Optimal Power Generation Portfolios with Renewables: An Application to the UK," Cambridge Working Papers in Economics 1646, Faculty of Economics, University of Cambridge.
    16. Kim, Yeong Jae & Cho, Seong-Hoon & Sharma, Bijay P., 2021. "Constructing efficient portfolios of low-carbon technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    17. Palzer, Andreas & Westner, Günther & Madlener, Reinhard, 2013. "Evaluation of different hedging strategies for commodity price risks of industrial cogeneration plants," Energy Policy, Elsevier, vol. 59(C), pages 143-160.
    18. Westner, Günther & Madlener, Reinhard, 2011. "Development of cogeneration in Germany: A mean-variance portfolio analysis of individual technology’s prospects in view of the new regulatory framework," Energy, Elsevier, vol. 36(8), pages 5301-5313.
    19. 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.
    20. Lang, Joachim & Madlener, Reinhard, 2010. "Portfolio Optimization for Power Plants: The Impact of Credit Risk Mitigation and Margining," FCN Working Papers 11/2010, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    21. Daniel Ziegler & Katrin Schmitz & Christoph Weber, 2012. "Optimal electricity generation portfolios," Computational Management Science, Springer, vol. 9(3), pages 381-399, August.
    22. Comodi, Gabriele & Rossi, Mosè, 2016. "Energy versus economic effectiveness in CHP (combined heat and power) applications: Investigation on the critical role of commodities price, taxation and power grid mix efficiency," Energy, Elsevier, vol. 109(C), pages 124-136.
    23. Zeng, Ximei & Zhou, Zhongbao & Gong, Yeming & Liu, Wenbin, 2022. "A data envelopment analysis model integrated with portfolio theory for energy mix adjustment: Evidence in the power industry," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    24. Badami, M. & Camillieri, F. & Portoraro, A. & Vigliani, E., 2014. "Energetic and economic assessment of cogeneration plants: A comparative design and experimental condition study," Energy, Elsevier, vol. 71(C), pages 255-262.
    25. Barbara Glensk & Reinhard Madlener, 2013. "Multi-period portfolio optimization of power generation assets," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 23(4), pages 20-38.

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    More about this item

    Keywords

    Combined heat and power; CHP promotion scheme; Portfolio optimization;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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