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Natural gas, uncertainty, and climate policy in the US electric power sector

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  • Bistline, John E.

Abstract

This paper investigates how uncertainties related to natural gas prices and potential climate policies may influence capacity investments, utilization, and emissions in US electricity markets. Using a two-stage stochastic programming approach, model results suggest that climate policies are stronger drivers of greenhouse gas emission trajectories than new natural gas supplies. The dynamics of learning and irreversibility may give rise to an investment climate where strategic delay is optimal. Hedging strategies are shown to be sensitive to the specification of probability distributions for climate policy and natural gas prices, highlighting the important role of uncertainty quantification in future research. The paper also illustrates how this stochastic modeling framework could be used to quantify the value of limiting methane emissions from natural gas production.

Suggested Citation

  • Bistline, John E., 2014. "Natural gas, uncertainty, and climate policy in the US electric power sector," Energy Policy, Elsevier, vol. 74(C), pages 433-442.
    • Handle: RePEc:eee:enepol:v:74:y:2014:i:c:p:433-442
    DOI: 10.1016/j.enpol.2014.08.017
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    Cited by:

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    3. LaPlue, Lawrence D., 2022. "Environmental consequences of natural gas wellhead pricing deregulation," Journal of Environmental Economics and Management, Elsevier, vol. 116(C).
    4. Xia, Tongshui & Ji, Qiang & Geng, Jiang-Bo, 2020. "Nonlinear dependence and information spillover between electricity and fuel source markets: New evidence from a multi-scale analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    5. Bistline, John E., 2016. "Energy technology R&D portfolio management: Modeling uncertain returns and market diffusion," Applied Energy, Elsevier, vol. 183(C), pages 1181-1196.
    6. Chen, Lei & Huang, Ding-Bin & Wang, Shan-You & Nie, Yi-Nan & He, Ya-Ling & Tao, Wen-Quan, 2019. "A study on dynamic desorption process of methane in slits," Energy, Elsevier, vol. 175(C), pages 1174-1180.
    7. Wiggins, Seth & Etienne, Xiaoli, 2015. "US Natural Gas Price Determination: Fundamentals and the Development of Shale," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205788, Agricultural and Applied Economics Association.
    8. Bistline, John E., 2015. "Electric sector capacity planning under uncertainty: Climate policy and natural gas in the US," Energy Economics, Elsevier, vol. 51(C), pages 236-251.
    9. Tan, Siah Hong & Barton, Paul I., 2016. "Optimal dynamic allocation of mobile plants to monetize associated or stranded natural gas, part II: Dealing with uncertainty," Energy, Elsevier, vol. 96(C), pages 461-467.
    10. Drachal, Krzysztof, 2018. "Comparison between Bayesian and information-theoretic model averaging: Fossil fuels prices example," Energy Economics, Elsevier, vol. 74(C), pages 208-251.
    11. Carroll, Deborah A. & Stevens, Kelly A., 2021. "The short-term impact on emissions and federal tax revenue of a carbon tax in the U.S. electricity sector," Energy Policy, Elsevier, vol. 158(C).
    12. Gençer, Emre & Agrawal, Rakesh, 2016. "A commentary on the US policies for efficient large scale renewable energy storage systems: Focus on carbon storage cycles," Energy Policy, Elsevier, vol. 88(C), pages 477-484.

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