A More Realistic Way to Simulate Large-Scale Adoption of New Energy Technologies
To assess long-range risks to food, water, energy and other critical, interdependent natural resources, scientists and decision-makers must rely on models that simulate the interplay between Earth and human systems. A key aspect of modeling human systems is to project the evolution of the energy mix over time. To produce a meaningful energy-mix projection, a human-system model must account for how quickly new energy technologies are likely to be adopted at large scale. Now researchers at the MIT Joint Program on the Science and Policy of Global Change have devised a new strategy to represent the penetration of such technologies within a global energy-economic model. Their representation incorporates what has been learned from historic analogues of new energy technology adoption, estimates of factors that slow adoption over the first 10-15 years, and an understanding of the impact of economic incentives on the pace of adoption.
The new MIT modeling strategy provides more realistic representation of how quickly alternative energy technologies can be adopted at large scale within a global energy-economic computable general equilibrium model. This capability could enable scientists and decision-makers to produce more accurate assessments of the likely contribution of such technologies to the future energy mix and simulations of any large-scale transition toward lower-carbon energy sources—thus improving assessments of long-term risks to multiple, interdependent sectors such as food, water, and energy.
Accounting for the likely contribution of advanced technologies to the future energy mix is critical in energy-economic modeling, as these technologies, while often not yet commercially viable, could substitute for fossil energy when favorable policies are in place. Simulating the transition from fossil energy to low-carbon substitutes turns out to be challenging, as many of these alternative energy sources have not been widely adopted. Evidence for how quickly they can be adopted at large scale must therefore be obtained mostly from small samples or analogous technologies. This study aims to improve the representation of technology diffusion in multisector dynamics models and ground that representation in empirical foundations and economic theory. Toward that end, the researchers develop an approach to model the penetration of a low-carbon substitute within a global energy-economic computable general equilibrium (CGE) model. Drawing upon data from historic analogues of new energy technology adoption and economic theory, their approach enables the simulation of multiple dynamics related to new technology diffusion. These include sunk investments in existing technology; intellectual property and scarcity rents associated with the new technology (i.e., gains to the producer when the price of output, driven either by monopoly pricing or by demand, is above the full cost of production); adjustment costs related to expanding the new technology (e.g. trying to speed up production leads to waste and requires hiring workers with less training); short- and long-run pricing of output of the new technology; and the rate of diffusion of the new technology and how it is influenced by economic factors.