Use of Real Options as a Policy-Analysis Tool

Blyth, William

doi:10.1016/b978-0-08-056887-4.00004-4

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…The standard deviation of the coal price is smaller than that of the gas price indicating that the fluctuation of coal price is less than the gas price. The standard deviations of fuel prices are approximately in line with values used in a number of other studies and they are generally between 25-30% of the mean value [18][19][20].…”

Section: ) Fuel Pricesupporting

confidence: 85%

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

Vithayasrichareon

MacGill

Wen

2010

IEEE PES General Meeting

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This paper proposes a stochastic model based onMonte-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 CO 2 emissions among generation portfolios to be identified. Index Terms-Monte Carlo simulation, electricity generation portfolio, generation investment under uncertainty.IX. BIOGRAPHIES . His current research interests are in power industry restructuring, power system fault diagnosis and restoration strategies, and artificial intelligence applications in power systems.

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Section: ) Fuel Pricesupporting

confidence: 85%

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

Vithayasrichareon

MacGill

Wen

2010

IEEE PES General Meeting

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“…Mean fuel prices are obtained from (ACIL Tasman, 2009) while their SD of gas and coal price used in this study is based on their historical trend which is estimated to be 30% and 10% of their respective mean value (Blyth, 2008;IEA, 2009b;Roques et al, 2008). These values are shown in Table 3.…”

Section: Stochastic Model Of Uncertain Parametersmentioning

confidence: 99%

Assessing the value of wind generation in future carbon constrained electricity industries

Vithayasrichareon

MacGill

2013

Energy Policy

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Methodologies for characterising and valuing energy security — A short critical review

Månsson

Johansson

Nilsson

2012

2012 9th International Conference on the European Energy Market

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Use of Real Options as a Policy-Analysis Tool

Cited by 3 publications

References 19 publications

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

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

Assessing the value of wind generation in future carbon constrained electricity industries

Methodologies for characterising and valuing energy security — A short critical review

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Use of Real Options as a Policy-Analysis Tool

Cited by 3 publications

References 19 publications

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

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

Assessing the value of wind generation in future carbon constrained electricity industries

Methodologies for characterising and valuing energy security &#x2014; A short critical review

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Methodologies for characterising and valuing energy security — A short critical review