Effects of technology assumptions on US power sector capacity, generation and emissions projections: Results from the EMF 32 Model Intercomparison Project.

Journal Article (Journal Article)

This paper is one of two syntheses in this special issue of the results of the EMF 32 power sector study. This paper focuses on the effects of technology and market assumptions with projections out to 2050. A total of 15 models contributed projections based on a set of standardized scenarios. The scenarios include a range of assumptions about the price of natural gas, costs of end-use energy efficiency, retirements of nuclear power, the cost of renewable electricity, and overall electricity demand. The range of models and scenarios represent similarities and differences across a broad spectrum of analytical methods. One similarity across almost all results from all models and scenarios is that the share of electricity generation and capacity fueled by coal shrinks over time, although the rate at which coal capacity is retired depends on the price of natural gas and the amount of electricity that is demanded. Another similarity is that the models project average increases in natural gas power generating capacity in every scenario over the 2020-2050 period, but at lower average annual rates than those that prevailed during the 2000-2015 period. The projections also include higher gas capacity utilization rates in the 2035-2050 period compared to the 2020-2050 period in every scenario, except the high gas price sensitivity. Renewables capacity is also projected to increase in every scenario, although the annual new capacity varies from modest rates below the observed 2000-2015 wind and solar average to rates more than 3 times that high. Model estimates of CO2 emissions largely follow from the trends in generation. Low renewables cost and low gas prices both result in lower overall CO2 emission rates relative to the 2020-2035 and 2035-2050 reference. Both limited nuclear lifetimes and higher demand result in increased CO2 emissions.

Full Text

Duke Authors

Cited Authors

  • Creason, JR; Bistline, JE; Hodson, EL; Murray, BC; Rossmann, CG

Published Date

  • January 2018

Published In

Volume / Issue

  • 73 /

Start / End Page

  • 290 - 306

PubMed ID

  • 31073253

Pubmed Central ID

  • PMC6503686

Electronic International Standard Serial Number (EISSN)

  • 1873-6181

International Standard Serial Number (ISSN)

  • 0140-9883

Digital Object Identifier (DOI)

  • 10.1016/j.eneco.2018.04.013


  • eng