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A Real Options Approach to Evaluating New Nuclear Power Plants

Geoffrey Rothwell

Year: 2006
Volume: Volume 27
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol27-No1-3
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Abstract:
Although nuclear power plants are being built in Asia, they have not been ordered in the U.S. since the 1979 accident at Three Mile Island. For many reasons, new attention is being given to light water reactors. Currently- operating nuclear power plants in the U.S. were built under rate-of-return regulation. Now, new nuclear power plants must compete in power markets. This paper models the net present value of building an Advanced Boiling Water Reactor in Texas using a real options approach to determine the risk premium associated with net revenue uncertainty. It finds that a cost of about $1,200 per kilowatt-electric (including financing costs) for advanced light water nuclear power plants could trigger new orders. On the other hand, owner-operators might be willing to pay higher prices for nuclear megawatts if methods for mitigating price, cost, and capacity risk through contracts or real assets could be found.



Combined Heat and Power in Commercial Buildings: Investment and Risk Analysis

Karl Magnus Maribu and Stein-Erik Fleten

Year: 2008
Volume: Volume 29
Number: Number 2
DOI: 10.5547/ISSN0195-6574-EJ-Vol29-No2-7
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Abstract:
Combined heat and power (CHP) systems can generate electricity locally while they recover heat to satisfy heating loads in buildings, which means they provide efficient energy. On-site generators may reduce both the expected energy costs and cost risk exposure for developers. With volatile energy prices, a deterministic modeling framework will not yield a fair value of CHP systems because flexibility in the operational response to price changes is not taken into account. In this paper, we present a Monte Carlo simulation model that is used to find the CHP value under uncertain future wholesale electricity and natural gas prices. When considering investing in a CHP system on should consider both return and risk. Clearly, both investment return and risk depend on local energy tariffs and energy loads. We highlight an example where CHP is marginally profitable and the investment decision is not straightforward. Interestingly, CHP systems were found particularly attractive with volatile electricity prices because their ability to respond to high prices provides efficient hedges to energy cost risk. Therefore, developers should not be discouraged but rather embrace on-site generation in markets with volatile prices. From the analysis, it can also be concluded that sizing of CHP systems can be related to the energy tariff structure and cost risk preferences as well as to energy loads.



The Impact of Stochastic Extraction Cost on the Value of an Exhaustible Resource: An Application to the Alberta Oil Sands

Abdullah Almansour and Margaret Insley

Year: 2016
Volume: Volume 37
Number: Number 2
DOI: 10.5547/01956574.37.2.aalm
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Abstract:
The optimal management of a non-renewable resource extraction project is studied when input and output prices follow correlated stochastic processes. The decision problem is specified by two Bellman equations describing the project when it is currently operating or mothballed. Solutions are determined numerically using the Least Squares Monte Carlo methodology. The analysis is applied to an oil sands project which uses natural gas during extracting and upgrading. The paper takes into account the co-movement between crude oil and natural gas prices and proposes two price models: one incorporates a long-run link between the two while the other has no such link. Incorporating a long-run relationship between oil and natural gas prices has a significant effect on the value of the project and its optimal operation and reduces the sensitivity of the project to the natural gas price process.



A Compound Real Option Approach for Determining the Optimal Investment Path for RPV-Storage Systems

Benjamin Hassi, Tomas Reyes, and Enzo Sauma

Year: 2022
Volume: Volume 43
Number: Number 3
DOI: 10.5547/01956574.43.3.bhas
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Abstract:
The use of residential Photovoltaic-Storage systems may produce large benefits to owners and has expanded rapidly in recent years. Nonetheless, large uncertainties regarding the profitability of these systems make it necessary to incorporate flexibilities in their economic evaluations. This paper offers a new method to evaluate the compound flexibility of both the option of delaying investments and the option of further expanding the capacity of solar photovoltaic modules and batteries during the investment horizon. Flexibility is modeled as a compound real option, whose value is computed using a novel method that we call Compound Least Squares Monte Carlo (CLSM). The model is applied to the investment decisions associated to a residential Photovoltaic-Storage system. Results suggest that investors should use the proposed CLSM method in the economic valuation of multi-stage projects, since considering only a single flexibility could promote sub-optimal decisions. Moreover, in our case study, we show that it is optimal to break the investment down into two steps or more in 36% of future scenarios, on average.



Endogenous Bad Outputs and Technical Inefficiency in U.S. Electric Utilities

Mike Tsionas and Subal C. Kumbhakar

Year: 2024
Volume: Volume 45
Number: Number 1
DOI: 10.5547/01956574.45.1.mtsi
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Abstract:
In this paper, we consider a simultaneous modeling of good and bad outputs. We use an input distance function (IDF) with endogenous inputs as well as endogenous bad outputs, which is novel in the literature. Moreover, we model input efficiency to depend on the production of bad outputs which allows us to investigate whether emissions of pollutants (bad outputs) are related to technological performance (technical efficiency). We also model production of each bad output with a spatial structure separately, each depending on production of good outputs, inputs and other exogenous variables. These bad output production functions allow us to estimate both direct and indirect effects of good output on the production of bad outputs, which may be of special interest because they show the cost (to the society) in terms of releasing pollutants to the environment in order to increase production of good outputs. We apply the new technique to a data set on U.S. electric utilities with four bad outputs, three inputs and two good outputs. We used a Bayesian technique to estimate the model which is a system consisting of the input distance function, reduced form equations for each input, dynamics of inefficiency and bad output production technology—separately for each. Empirically, bad outputs are found to affect inefficiency positively. Percentage increases in inefficiency due to a percentage increase in each bad output are found to vary from 0.225% to 0.42%. Energy prices are found to be positively related to inefficiency. From the spatial specifications of bad outputs, we find that the spillover effects of increasing production of good outputs account for the majority of the total effect, indicating that neighborhood effects are more important than own effects. This means, the neighboring utilities played a crucial role indicating "contagion" of practices.





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