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Investment risks in power generation: A comparison of fossil fuel and renewable energy dominated markets

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  • Tietjen, Oliver
  • Pahle, Michael
  • Fuss, Sabine

Abstract

Due to their high capital intensity, weather dependent renewable energies (RES) such as solar and wind face considerable investment risks in power markets. In addition, their uncertain production volumes also affect the investment risks of other plant types through the impact on power prices and residual demand. Increasing RES shares thus potentially increase overall investment risks in power markets, which many analysts consider to be a potential problem. Against this background, this paper compares investment risks of different technologies in markets with increasing shares of variable RES. It further analyses how generation mixes are affected by these investment risks if the risks are evaluated on a stand-alone basis or in a plant portfolio context of a private firm. For this purpose, a stylized investment and dispatch model is used to conduct Monte Carlo simulations from which risk measures are derived. The results show that capital intensive RES face the highest stand-alone risks, since their profits are most affected by the power price risk. However, the results further indicate that the stand-alone risks of variable RES decrease with their share in the market because of a negative correlation of output and price risk. In addition, RES have a risk benefit in firm plant portfolios in terms of constituting a hedge against losses of fossil fuel plants. This positive portfolio effect, however, rapidly decreases and becomes negative with increasing RES shares in the market.

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  • Tietjen, Oliver & Pahle, Michael & Fuss, Sabine, 2016. "Investment risks in power generation: A comparison of fossil fuel and renewable energy dominated markets," Energy Economics, Elsevier, vol. 58(C), pages 174-185.
    • Handle: RePEc:eee:eneeco:v:58:y:2016:i:c:p:174-185
    DOI: 10.1016/j.eneco.2016.07.005
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    More about this item

    Keywords

    Power markets; Investment risks; Monte Carlo simulation; Portfolio optimization; Renewable energy;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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