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A Stochastic Model for the Measurement of Electricity Outage Costs

Abraham Grosfeld-Nir and Asher Tishler

Year: 1993
Volume: Volume 14
Number: Number 2
DOI: 10.5547/ISSN0195-6574-EJ-Vol14-No2-8
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Abstract:
The measurement of customer outage costs has recently become an important subject of research for the electric utilities. This paper uses a stochastic dynamic model as the starting point in developing a market-based method for the evaluation of outage costs. Specifically, the model postulates that once an electricity outage occurs, all production activity stops. Full production is resumed once the electricity outage is over. This process repeats itself indefinitely. The business customer maximizes his expected discounted profits (the expected value of the firm), taking into account his limited ability to respond to repeated random electricity outages. The model is applied to 11 industrial branches in Israel. The estimates exhibit a large variation across branches.



Incorporating Investment Uncertainty into Greenhouse Policy Models

John R. Birge and Charles H. Rosa

Year: 1996
Volume: Volume17
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol17-No1-5
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Abstract:
Greenhouse gas policy decisions require comprehensive understanding of atmospheric, economic, and social impacts. Many studies have considered the effects of atmospheric uncertainty in global warming, but economic uncertainties, have received Less analysis. We consider a key component of economic uncertainty: the return on investments in new technologies. Using a mathematical! programming model, we show that ignoring uncertainty in technology investment policy may lead to decreases as great as 2 percent in overall expected economic activity in the U.S. with even higher losses in possible future scenarios. These results indicate that both federal and private technology investment policies should be based on models explicitly incorporating uncertainty.



Nuclear Power: A Hedge against Uncertain Gas and Carbon Prices?

Fabien A. Roques , William J. Nuttall, David M. Newbery, Richard de Neufville, Stephen Connors

Year: 2006
Volume: Volume 27
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol27-No4-1
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Abstract:
High fossil fuel prices have rekindled interest in nuclear power. This paper identifies specific characteristics making nuclear power unattractive to merchant generators in liberalized electricity markets, and argues that non-fossil fuel technologies have an overlooked option value given fuel and carbon price uncertainty. Stochastic optimization estimates the company option value of keeping open the choice between nuclear and gas technologies. The merchant option value decreases sharply as the correlation between electricity, gas, and carbon prices rises, casting doubt on whether merchant investors have adequate incentives to choose socially efficient diversification in liberalized electricity markets.



Carbon Capture Retrofits and the Cost of Regulatory Uncertainty

Peter S. Reinelt and David W. Keith

Year: 2007
Volume: Volume 28
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol28-No4-5
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Abstract:
Power generation firms confront impending replacement of an aging coal-fired fleet in a business environment characterized by volatile natural gas prices and uncertain carbon regulation. We develop a stochastic dynamic programming model of firm investment decisions that minimizes the expected present value of future power generation costs under uncertain natural gas and carbon prices. We explore the implications of regulatory uncertainty on generation technology choice and the optimal timing of investment, and assess the implications of these choices for regulators. We find that interaction of regulatory uncertainty with irreversible investment always raises the social cost of carbon abatement. Further, the social cost of regulatory uncertainty is strongly dependent on the relative competitiveness of IGCC plants, for which the cost of later carbon capture retrofits is comparatively small, and on the firm�s ability to use investments in natural gas generation as a transitional strategy to manage carbon regulation uncertainty. Without highly competitive IGCC or low gas prices, regulatory uncertainty can increase the expected social cost of reducing emissions by 40 to 60%.



Stochastic Trends and Technical Change: The Case of Energy Consumption in the British Industrial and Domestic Sectors

Paolo Agnolucci

Year: 2010
Volume: Volume 31
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol31-No4-5
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Abstract:
This paper estimates energy demand in the British domestic and indus�trial sectors and analyzes the extent to which energy-saving technological change is exogenous, or induced by the energy price. The paper implements models with a linear trend, models making use of the price decomposition of Dargay and Gately (1995a) and the Structural Time Series Models (STSMs) of Harvey (1989). Stochastic trends have been found to be rather important while in neither of the sectors assessed in this study could the hypothesis of symmetric price effects be rejected. Following Hunt and Judge (2005), stochastic trend and asymmetric price effects are found to be substitutes in the industrial sector. In particular we con�clude that asymmetric price effects can substitute for the slope in the stochastic trend. Finally, energy consumption in the industrial sector is strongly in.uenced by price while the effect of price in the domestic sector is markedly smaller.



Investment Propensities under Carbon Policy Uncertainty

Janne Kettunen, Derek W. Bunn and William Blyth

Year: 2011
Volume: Volume 32
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol32-No1-4
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Abstract:
Whether companies invest in new power facilities at a particular point in time, or delay, depends upon the perceived evolution of uncertainties and the investors' attitudes to risk and return. With additional risks emerging through climate change mitigation mechanisms, the propensity to invest may increasingly depend upon how each technology and company is exposed to carbon price uncertainty. We approach this by estimating the cumulative probabilities of investment over time in various technologies as a function of behavioral, policy, financial and market assumptions. Using a multistage stochastic optimization model with exogenous uncertainty in carbon price, we demonstrate that detailed financial analysis with real options and risk constraints can make substantial difference to the investment propensities compared to conventional economic analysis. Further, we show that the effects of different carbon policies and market instruments on these decision propensities depend on the characteristics of the companies and may induce market structure evolution.



Optimal Abandonment of EU Coal-fired Stations

Luis M. Abadie, José; M. Chamorro and Mikel González-Eguino

Year: 2011
Volume: Volume 32
Number: Number 3
DOI: 10.5547/ISSN0195-6574-EJ-Vol32-No3-7
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Abstract:
Coal-fired power plants face potential difficulties in a carbon constrained world. The traditional advantage of coal as a cheaper fuel may erode in the future if CO2 allowance prices increase. When would it be optimal to abandon a coal station and obtain its salvage value? We assess this question following the Real Options approach. We consider the case of a coal plant that operates in a deregulated electricity market where natural gas-fired plants are the marginal units. We assume specific stochastic processes for the fundamental uncertainties in our model: coal price, natural gas price, and emission allowance price. The underlying parameters are derived from actual futures markets. They are further used in a three-dimensional binomial lattice to assess the decision to abandon. We draw the optimal exercise boundary. Sensitivity analyses (regarding fuel prices, allowance price, volatilities, useful life, residual value, thermal efficiency, safety valves in carbon prices, time step) are also undertaken.



Managing a Portfolio of Real options: Sequential Exploration of Dependent Prospects

James L. Smith and Rex Thompson

Year: 2008
Volume: Volume 29
Number: Special Issue
DOI: 10.5547/ISSN0195-6574-EJ-Vol29-NoSI-4
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Abstract:
We consider the impact of sequential investment and active management on the value of a portfolio of real options. The options are assumed to be interdependent, in that exercise of any one is assumed to produce, in addition to some intrinsic value based on an underlying asset, further information regarding the values of other options based on related assets. We couch the problem in terms of oil exploration, where a discrete number of related geological prospects are available for drilling, and management's objective is to maximize the expected value of the combined exploration campaign. Management's task is complex because the expected value of the investment sequence depends on the order in which options are exercised. A basic conclusion is that, although dependence increases the variance of potential outcomes, it also increases the expected value of the embedded portfolio of options and magnifies the value of optimal management. Stochastic dynamic programming techniques may be used to establish the optimal sequence of investment. Given plausible restrictions on the information structure, however, we demonstrate that the optimal dynamic program can be identified and implemented by policies that are relatively simple to execute. In other words, we provide sufficient conditions for the optimality of intuitive decision rules, like biggest first, most likely first, or greatest intrinsic value first. We also develop exact analytic expressions for the implied value of the portfolio, which permits the value of active management to be assessed directly.



Changes in the Operational Efficiency of National Oil Companies

Peter R. Hartley and Kenneth B. Medlock III

Year: 2013
Volume: Volume 34
Number: Number 2
DOI: 10.5547/01956574.34.2.2
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Abstract:
Using data on 61 oil companies from 2001-09, we examine the evolution of revenue efficiency of National Oil Companies (NOCs) and shareholder-owned oil companies (SOCs). We find that NOCs generally are less efficient than SOCs, but their efficiency increased faster over the last decade. We also find evidence that partial privatizations increase operational efficiency, and (weaker) evidence that mergers and acquisitions during the decade tended to increase the efficiency of the merging firms. Finally, we find evidence that much of the inefficiency of NOCs is consistent with the hypothesis that government ownership leads to different firm objectives.



The Costs of Electricity Systems with a High Share of Fluctuating Renewables: A Stochastic Investment and Dispatch Optimization Model for Europe

Stephan Nagl, Michaela Fursch, and Dietmar Lindenberger

Year: 2013
Volume: Volume 34
Number: Number 4
DOI: 10.5547/01956574.34.4.8
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Abstract:
Renewable energies are meant to cover a large share of the future electricity demand. However, the availability of wind and solar power depends on local weather conditions. In this article, we analyze the impact of the stochastic availability of wind and solar energy on the cost-minimal power plant mix and the related total system costs. To determine optimal conventional, renewable and storage capacities for different shares of renewables, we apply a stochastic investment and dispatch optimization model to the European electricity market. The model considers stochastic feed-in structures and full load hours of wind and solar technologies and different correlations between regions and technologies. Key findings include a lower value of fluctuating renewables and higher system costs compared to deterministic investment and dispatch models. Furthermore, the value of solar technologies is--relative to wind turbines--underestimated when neglecting negative correlations between wind speeds and solar radiation.




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