Electricity generation portfolio evaluation for highly uncertain and carbon constrained future electricity industries

This paper proposes a stochastic model based on Monte-Carlo simulation to assess the expected costs and risks of different generation portfolios for electricity industries in an increasingly uncertain and carbon constrained world. The approach can incorporate uncertain carbon and fossil-fuel prices of virtually any probability distributions, as well as possible correlations between them. The tool provides expected overall costs and their associated probability distribution for any possible generation portfolio mix. The model is applied to a case study of an electricity industry with coal, CCGT and OCGT generation options that faces uncertain future carbon and fuel prices. Lognormal distributions are used to model fuel and carbon prices uncertainty. Results from the case study highlight some important issues including the potentially significant interactions between carbon and gas prices on portfolio performance. The proposed model enables the tradeoffs between expected system generation cost, associated cost uncertainty and CO₂ emissions among generation portfolios to be identified.