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Investment in electricity generation under emissions price uncertainty : the plant-type decision

Abstract:
This paper investigates the effects of uncertain emissions prices on the plant-type investment decision of an electricity generating firm. It is assumed that the firm faces an investment deadline and is deciding between "clean" and "dirty" generating alternatives, with the dirty option being more profitable in the absence of emissions regulation. Two models are presented in which the policy variable, the carbon dioxide (CO2) price, is assumed to evolve according to two different stochastic processes, each representing a different degree of possible future government intervention. In the first, the emissions cap is assumed fixed and certain, and CO2 permit prices evolve according to a geometric Brownian motion, and in the second it is assumed that the government may alter the cap at some point in the future, and CO2 prices are modelled as following a combined Poisson-geometric Brownian motion. The models employ real options analysis and the firm's decision is couched as an optimal stopping problem in which the continuation region is characterized by the default decision of replacing the dying coal plant with a new dirty unit. The models are solved for the critical permit price, τ*, at which the construction of a clean plant rather than a dirty one becomes optimal, and the dependence of the models’ solutions on the parameter values chosen is demonstrated. The results indicate that uncertainty leads to a delay in investment generally, and a reduction in clean-unit construction. It is shown that this delay is more pronounced in the jump-diffusion scenario, when emissions caps can be altered in the future, than in the geometric Brownian motion setting, when the emissions cap is assumed fixed.
Publication status:
Published
Peer review status:
Reviewed (other)

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Institution:
University of Oxford
Research group:
Oxford Institute for Energy Studies
Role:
Author


Publisher:
Oxford Institute for Energy Studies
Series:
OIES paper
Publication date:
2008-01-01
Edition:
Publisher's version
Paper number:
EV39
ISBN:
9781901795772


Language:
English
Keywords:
UUID:
uuid:113f38ca-122e-4aca-9f21-0803790a9d36
Local pid:
ora:10578
Deposit date:
2015-03-13
ARK identifier:

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