Logistic growth curve modeling of US energy production and consumption

Tyler M. Harris, Jay P. Devkota, Vikas Khanna, Pragnya L. Eranki and Amy E. Landis

Renewable and Sustainable Energy Reviews, 2018, vol. 96, issue C, 46-57

Abstract: This research used four-parameter multi-cycle logistic growth curve models on US Energy Information Agency annual data from 1949 to 2015 to produce fixed condition forecasts of US energy production and consumption to 2040. These models and forecasts were used to assess the ability of US energy production sources to meet demand, to anticipate production and technology challenges, and to make general policy recommendations. The logistic fixed condition forecasts indicated the ongoing increases in total US energy production dominated by crude oil and natural gas production will likely peak in 2017 (at 95.0 quadrillion “quad” BTU) then rapidly decrease through 2040 (at 36.2 quad BTU), while total US energy consumption indicated an ongoing plateau (at 98.1 quad BTU). New growth cycles not evident in the 2015 data will certainly occur, mitigating the decline in energy production before 2040. However, without adequate foresight and preemptive action, it is possible that new production growth would not be adequate to reverse the decline given historical growth trends. Therefore, in addition to continued increases in energy efficiency, reductions in use, and implementation of carbon management technologies, direct effort towards the sustainable development of substantial new growth cycles in all energy production sources (through adequate investment of resources) should be a priority of the US energy industry, policy makers, and the public alike.

Keywords: Logistic equation; Logistic growth curve modeling; Growth cycle; Energy production and consumption modeling; Fixed condition forecast (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:rensus:v:96:y:2018:i:c:p:46-57

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DOI: 10.1016/j.rser.2018.07.049

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