A Monte Carlo based decision-support tool for assessing generation portfolios in future carbon constrained electricity industries

This paper presents a novel decision-support tool for assessing future generation portfolios in an increasingly uncertain electricity industry. The tool combines optimal generation mix concepts with Monte Carlo simulation and portfolio analysis techniques to determine expected overall industry costs...

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Veröffentlicht in:Energy policy 2012-02, Vol.41 (1), p.374-392
Hauptverfasser: Vithayasrichareon, Peerapat, MacGill, Iain F.
Format: Artikel
Sprache:eng
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Zusammenfassung:This paper presents a novel decision-support tool for assessing future generation portfolios in an increasingly uncertain electricity industry. The tool combines optimal generation mix concepts with Monte Carlo simulation and portfolio analysis techniques to determine expected overall industry costs, associated cost uncertainty, and expected CO2 emissions for different generation portfolio mixes. The tool can incorporate complex and correlated probability distributions for estimated future fossil-fuel costs, carbon prices, plant investment costs, and demand, including price elasticity impacts. The intent of this tool is to facilitate risk-weighted generation investment and associated policy decision-making given uncertainties facing the electricity industry. Applications of this tool are demonstrated through a case study of an electricity industry with coal, CCGT, and OCGT facing future uncertainties. Results highlight some significant generation investment challenges, including the impacts of uncertain and correlated carbon and fossil-fuel prices, the role of future demand changes in response to electricity prices, and the impact of construction cost uncertainties on capital intensive generation. The tool can incorporate virtually any type of input probability distribution, and support sophisticated risk assessments of different portfolios, including downside economic risks. It can also assess portfolios against multi-criterion objectives such as greenhouse emissions as well as overall industry costs. ► Present a decision support tool to assist generation investment and policy making under uncertainty. ► Generation portfolios are assessed based on their expected costs, risks, and CO2 emissions. ► There is tradeoff among expected cost, risks, and CO2 emissions of generation portfolios. ► Investment challenges include economic impact of uncertainties and the effect of price elasticity. ► CO2 emissions reduction depends on the mix of generation technologies within the portfolio.
ISSN:0301-4215
1873-6777
DOI:10.1016/j.enpol.2011.10.060