One key approach to analyzing the feasibility of energy extraction and generation technologies is to understand the net energy they contribute to society. These analyses most commonly focus on a simple comparison of a source’s expected energy outputs to the required energy inputs, measured in the form of energy return on investment (EROI). What is not typically factored into net energy analysis is the influence of output variability. This omission ignores a key attribute of biological organisms and societies alike: the preference for stable returns with low dispersion versus
equivalent returns that are intermittent or variable. This biologic predilection for stability, observed and refined in academic financial literature, has a direct relationship to many new energy technologies whose outputs are much more variable than traditional energy sources. We investigate the impact of variability on net energy metrics and develop a theoretical framework to evaluate energy systems based on existing financial and biological risk models. We then illustrate the impact of variability on nominal energy return using representative technologies in electricity generation, with a more detailed analysis on wind power, where intermittence and stochastic availability of hard-to-store electricity will be factored into theoretical returns.