Global Energy Outlooks Comparison Methods: 2018 Update

This report describes the methodology for harmonizing multiple long-term energy outlooks and creates harmonized projection data for the IEA, OPEC, US EIA, ExxonMobil, and BP.



April 26, 2018


Richard G. Newell, Stuart Iler, and Daniel Raimi



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We update a harmonization methodology previously developed in 2015 to facilitate comparisons of long-term global energy projections issued by the International Energy Agency, US Energy Information Administration, ExxonMobil, BP, and the Organization of the Petroleum Exporting Countries. We continue to find important differences across outlooks in primary energy units used, assumed energy content of fossil fuels, assumed efficiency of nuclear and renewable electricity conversion from primary energy, categorization of biofuels, and inclusion (or exclusion) of traditional biomass. For example, the US EIA and BP’s exclusion of non-marketed traditional biomass yields estimates of global primary energy consumption that are 8 to 13 percent lower than the IEA, ExxonMobil and OPEC, which include these sources. Assumptions about energy content of fossil fuels can vary by more than 10 percent in the data examined here, requiring significant downward adjustment of primary energy consumption estimates for oil and natural gas to make BP and US EIA data comparable to IEA, OPEC, and ExxonMobil. Conventions about primary energy conversion of renewables can alter estimates for these sources, ranging from a 65 percent decrease to a 280 percent increase for particular electricity sources. We also find that there are significant differences in historical data used in these outlooks, even when measured in fuel-specific physical units such as barrels, cubic meters, or tonnes. After taking into account these differences, our harmonization methodology brings estimates within 1.5 percent or less of one another for most fuels in the benchmark year of 2015. We highlight important sources of divergence where organizations producing outlooks may find opportunities to align assumptions and improve datacomparability. Enhancing the comparability of outlooks will improve the quality of the dialogue among stakeholders to the benefit of energy decisionmaking worldwide.


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