[Clearly Energy Returned on Invested (EROI) research needs to have common standards because results vary by orders of magnitude. Taking the “average” is not going to produce the best guess because outliers skew the average up substantially. The EROI of onshore wind ranges from 5 to 92, Solar PV from 1 to almost 50, and hydropower from 6 to nearly 300. The energy payback times in Figure A, which come from the IPCC (in orange) are far too short. In general the IPCC greatly exaggerates how much coal, oil, and natural gas remain because the IPCC does not invite systems ecologists and the petroleum geologists who correctly predicted peak oil production based on Hubbert and other mathematical algorithms, decades of field work, and the world’s best database of oil production around the globe.
Alice Friedemann www.energyskeptic.com]
DOE. 2014. Wind vision a new era for wind power in the United States. Department of Energy.
Energy ratio is the ratio of energy produced by a technology over its lifetime to the input energy required to build the power generating technology. Energy payback time is the amount of time required to pay back the technology’s input energy requirements given the amount of yearly energy produced. Source: Non-wind estimates from [Edenhofer]; wind estimates based on literature review detailed in Appendix J.
Similar in concept to the assessment of life-cycle GHG emissions is the aim of a large body of literature to estimate on a life-cycle basis the amount of energy required to manufacture and operate energy conversion technologies or fuels (i.e., “input” energy). This concept helps inform decision makers on the degree to which various energy technologies provide a “net” increase in energy supply, and is often expressed in the form of either:
- Energy ratio: a ratio of the amount of energy produced by a technology over its lifetime to its input energy; or
- Energy payback time: the amount of time required to pay back the input energy given the amount of yearly energy produced.
Figure A summarizes published estimates of these two metrics for wind technologies, in comparison to estimates for other electric generation technologies as presented in a recent report from the Intergovernmental Panel on Climate Change [Edenhofer]. With regard to wind energy, 55 references reporting more than 130 net energy estimates were reviewed, using the same literature screening approach as for the review of life-cycle GHG emissions (see Appendix J).
Figure A presents a summary of the review. To be clear, these results are reported from studies that exhibit considerable methodological variability. Although previous work has identified several key issues that can influence results (e.g., [Kubiszewski, Brandt 2011, Brandt 2013]), the literature remains diverse and unconsolidated. Variability in the results for wind, for example, may in part be due to difference in the treatment of end-of-life modeling (e.g., recycling); assumed system lifetime and capacity factor; technology evaluated (turbine size, height); and whether turbine replacement is considered.
Notwithstanding these caveats, the results suggest that both land-based and offshore wind power have similar, if not somewhat lower, energy payback times as other technologies, with higher (especially at the high end) energy ratios. That is, wind energy performs relatively well in comparison to other electric generation technologies on these metrics, requiring roughly the same or even lower amounts of input energy relative to energy produced.
Brandt, A.R.; Dale, M. 2011. A General Mathematical Framework for Calculating Systems-Scale Efficiency of Energy Extraction and Conversion: Energy Return on Investment (EROI) and Other Energy Return Ratios. Energies (4:8):1211–1245. http://www.mdpi.com/1996-1073/4/8/1211.
Brandt, A.R.; et al. 2013. Calculating Systems-Scale Energy Efficiency and Net Energy Returns: A Bottom-Up Matrix-Based Approach. Energy (62):235–247. http://www.sciencedirect.com/science/article/pii/S0360544213008207.
Edenhofer, O.; et al., eds. 2011. IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation. Cambridge, UK, and New York: Cambridge University Press. http://srren.ipcc-wg3.de/
Kubiszewski, I.; et al. 2010. Meta-Analysis of Net Energy Return for Wind Power Systems. Renewable Energy (35:1), 2010; pp. 218–225. doi:10.1016/j.renene.2009.01.012. http://www.researchgate.net/publication/ 222703134_Meta-analysis_of_net_energy_return_for_wind_power_systems