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Leveraging Non-Renewable Fuels for Renewable Electricity Generation

CSS Publication Number

Electricity is a key energy carrier for residential, commercial and industrial
activities, particularly in developed countries. In the United States, electricity
generation accounts for 39% of total primary energy consumption with renewable
sources providing only 9% of the total [1]. This reliance on fossil and nuclear
fuels is not sustainable on a long term basis and is a major contributor to
environmental challenges such as global climate change, acidification, smog
formation, and radioactive waste disposal. Transition to renewable technologies
provides an opportunity for enhancing the sustainability of electricity generation.
The objectives of this paper are to compare the life cycle energy performance of
competing renewable technologies through the use of net energy ratio (NER) and
to examine alternative life cycle assessment (LCA) methods for evaluating the
NER. The net energy ratio as defined here is the total life cycle electrical energy
output of a system relative to the total life cycle primary energy input from nonrenewable
sources and is used to discuss the non-renewable energy leveraging
capacity of electricity generation. NER values can be calculated using either a
process-based LCA approach or an input-output based LCA approach.
Examination of NER values for alternative technologies is extremely complex.
Materials of construction, processing systems, operating parameters, durability,
and other factors all affect technology performance. In the case of many
renewable energy technologies, location factors such as solar radiation levels,
wind speeds, and crop yields directly impact NER values. Examples that
demonstrate these factors for select renewable technologies are shown in Table 1.
Not surprisingly, the identification and examination of key technology
parameters is an important component of understanding energy performance.
This paper highlights critical factors included in energy analyses, and provides
NER values for the major electricity generation technologies available in the US.


Process-based LCA studies require detailed information regarding a well-defined
system and the associated processes. EIOLCA requires information regarding
economic transactions and environmental impacts associated with broad
industrial sectors within a specified economy (e.g. the US national economy).
The resulting analyses provide a detailed understanding of individual system
components in the case of process-based LCA or a comprehensive view based on
a more extensive system boundary in the case of EIOLCA.
Figure 1 compares the NER of a wind farm using the two LCA methods studied.
The electrical output of the facility at any point on the figure is identical for both
methods, however, differences in the amount of life cycle energy input captured
by the two methods results in different NER values. EIOLCA tends to be more
comprehensive and inclusive than process based approaches, which yields a
larger denominator for the computation of the NER. Consequently, EIOLCA
based NER values are smaller than process based LCA results. Two key system
parameters, the lifetime of the facility and the capacity factor, affect the NER
regardless of the LCA method used.
Overall results from EIOLCA and process-based LCA methods indicate that the
greatest leveraging of non-renewable energy occurs with wind turbines and
hydroelectric plants followed by biomass and photovoltaics.


[1] U.S. Department of Energy, Annual Energy Review 2003, DOE/EIA-0384,
Energy Information Administration (2004).
[2] D. V. Spitzley, G. A. Keoleian, Life Cycle Environmental and Economic
Assessment of Willow Biomass Electricity: A Comparison with Other Renewable
and Non-Renewable Sources, CSS04-05, Center for Sustainable Systems,
University of Michigan, (2004).

Research Areas
Energy Systems
Publication Type
Conference Proceeding
Full Citation
Pacca, S., D.V. Spitzley and G.A. Keoleian. 2005. Leveraging Non-Renewable Fuels for Renewable Electricity Generation. 3rd International Conference of the International Society for Industrial Ecology (ISIE) Proceedings. Stockholm, Sweden: 371-373.