CO2 volatility impact on energy portfolio choice: A fully stochastic LCOE theory analysis. (15th March 2017)

• Record Type: Journal Article
• Authors: Lucheroni, Carlo; Mari, Carlo
• Is Part Of: Applied energy. Volume 190(2017)
• Page Start: 278
• Page End: 290
• Publication Date: 2017-03-15
• Subjects: Q40 -- G31 -- G32 -- L94 -- M21; Levelized cost of electricity -- Nuclear power -- Risk and deviation measures; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2016.12.125
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: Stochastic LCOE theory is an extension of the levelized cost of electricity analysis. The fully stochastic analysis include stochastic processes for fossil fuels prices and CO2 prices. The nuclear asset is risky through uncertainty about construction times and it is used as a hedge. Volatility of CO2 prices has a strong influence on CO2 emissions reduction. Abstract: Market based pricing of CO2 was designed to control CO2 emissions by means of the price level, since high CO2 price levels discourage emissions. In this paper, it will be shown that the level of uncertainty on CO2 market prices, i.e. the volatility of CO2 prices itself, has a strong influence not only on generation portfolio risk management but also on CO2 emissions abatement. A reduction of emissions can be obtained when rational power generation capacity investors decide that the capacity expansion cost risk induced jointly by CO2 volatility and fossil fuels prices volatility can be efficiently hedged adding to otherwise fossil fuel portfolios some nuclear power as a carbon free asset. This intriguing effect will be discussed using a recently introduced economic analysis tool, called stochastic LCOE theory. The stochastic LCOE theory used here was designed to investigate diversification effects on energy portfolios. In previous papers this theory was used to study diversification effects on portfolios composed of carbon risky fossil technologies and a carbon risk-free nuclear technology in a risk-reward trade-off frame. In this paper the stochastic LCOE theory will be extended to include uncertainty about nuclear power plant construction times, i.e. considering nuclear risky as well, this being the main uncertainty source of financial risk in nuclear technology. Two measures of risk will be used, standard deviation and CVaR deviation, to derive efficient frontiers for generation portfolios. Frontier portfolios will be analyzed in their implications on emissions control.