Power of Screening Models for Developing Flexible Design Strategies in Hydropower Projects: Case Study of Ethiopia
Publication: Journal of Water Resources Planning and Management
Volume 140, Issue 12
Abstract
Long-term price changes in water resources benefits may greatly affect a project’s value, however the traditional approach to river basin planning has not been able to take full account of these uncertainties. Additionally, the relatively recent approach of adaptive management does not provide much systematic guidance for planners. This paper proposes an approach that allows planners of river basins to incorporate flexibility into the design to enable them to increase the expected value of these projects by avoiding untimely elements, taking advantage of favorable opportunities. This paper considers the application of a midfidelity screening model to identify flexible design opportunities and strategies. Such a model is adopted to explore the impacts of future electricity price uncertainty on a proposed system of hydroelectric dams in Ethiopia. Using possible price paths developed from a binomial lattice model calibrated on price variability, the screening model is used to (1) identify the most flexible construction sequence for building the dams and (2) value various options exercised on the most flexible construction sequence. Scenarios are evaluated using the criteria of expected net present value and capital expenditure and assessed using cumulative distribution functions. Results indicate that the best option increases the expected net present value of the most flexible construction sequence by nearly 2%. Furthermore, the cumulative distribution function curve analysis demonstrates how a failure to consider uncertainties such as price may result in a significant underevaluation or overevaluation of the project. Thus, this study highlights the value of a systematic approach using a midfidelity screening model to assess the uncertainties present in water resource infrastructure investments.
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Acknowledgments
We gratefully thank and acknowledge the MIT Joint Program on the Science and Policy of Global Change for sharing their Emissions Prediction and Policy Analysis (EPPA) model, supported by a consortium of government, industry, and foundation sponsors including the Department of Energy (DOE) Integrated Assessment Grant (DE-FG02-94ER61937) (for a complete list of sponsors, see http://globalchange.mit.edu). We also acknowledge Dr. Michel-Alexandre Cardin for the development in Excel of the 7-period binomial model adapted in this analysis, and first created for ESD.71, a subject offered in the Fall of 2010 at the Massachusetts Institute of Technology.
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Published In
Journal of Water Resources Planning and Management
Volume 140 • Issue 12 • December 2014
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Nov 27, 2012
Accepted: Oct 10, 2013
Published online: Oct 12, 2013
Discussion open until: Oct 30, 2014
Published in print: Dec 1, 2014
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