Real option valuation of power transmission investments by stochastic simulation
Network expansions in power markets usually lead to investment decisions subject to substantial irreversibility and uncertainty. Hence, investors need valuing the flexibility to change decisions as uncertainty unfolds progressively. Real option analysis is an advanced valuation technique that enable...
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Published in | Energy economics Vol. 47; pp. 215 - 226 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Kidlington
Elsevier B.V
01.01.2015
Elsevier Science Ltd |
Subjects | |
Online Access | Get full text |
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Summary: | Network expansions in power markets usually lead to investment decisions subject to substantial irreversibility and uncertainty. Hence, investors need valuing the flexibility to change decisions as uncertainty unfolds progressively. Real option analysis is an advanced valuation technique that enables planners to take advantage of market opportunities while preventing or mitigating losses if future conditions evolve unfavorably. In the past, many approaches for valuing real options have been developed. However, applying these methods to value transmission projects is often inappropriate as revenue cash flows are path-dependent and affected by a myriad of uncertain variables. In this work, a valuation technique based on stochastic simulation and recursive dynamic programming, called Least-Square Monte Carlo, is applied to properly value the deferral option in a transmission investment. The effect of option's maturity, the initial outlay and the capital cost upon the value of the postponement option is investigated. Finally, sensitivity analysis determines optimal decision regions to execute, postpone or reject the investment projects.
•A modern investment appraisal method is applied to value power transmission projects.•The value of the option to postpone decision to invest in transmission projects is assessed.•Simulation methods are best suited for valuing real options in transmission investments. |
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Bibliography: | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0140-9883 1873-6181 |
DOI: | 10.1016/j.eneco.2014.11.011 |