Abstract
In this paper we review and extend the stochastic LCOE portfolio theory, a mean-risk analysis of electricity generation investment portfolios, focusing on the distinction between risk and deviation risk measures in terms of risk distribution shaping. Using standard and more advanced stochastic optimization risk measures, we derive optimal portfolios in the case of fossil fuels only, and in the case which includes the nuclear asset, interpreted as a risk free asset useful to hedge and reduce LCOE dispersion around its mean, in a US market case study. Four CO2 price volatility scenarios are used to illustrate how the theory handles the impact of indirect correlation among different fuel technologies induced by CO2 costs on the determination of optimal portfolios.
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