Abstract:
We study the optimal transition from fossil fuels to renewable energy in a neoclassical growth economy with endogenous technological progress in energy production. Innovations keep fossil energy costs under control even as increased exploitation raises mining costs. Nevertheless, the economy transitions to renewable energy after about 80% of available fossil fuels are exploited. The energy shadow price remains more than double current values for over 75 years around the switch time. Consumption and output growth decline sharply during the transition period, which we thus identify as an "energy crisis." The model highlights the important role energy can play in influencing economic growth.

Abstract:
It is often claimed that a difficulty of raising investment funds prevents promising new energy technologies from attaining commercial viability. We examine this issue using a dynamic intertemporal model of the displacement of fossil fuel energy technologies by non-fossil alternatives. Our model highlights the fact that since capital used to produce energy services from fossil fuels is a sunk cost, it will continue to be used so long as the price of energy covers merely short-run operating costs. Until fossil fuels are abandoned, the price of energy is insufficient to cover even the operating costs of renewable energy production, let alone provide a competitive return on the capital employed. The full long-run costs of renewable energy production are not covered until some time after fossil fuels are abandoned.

Abstract:
A pressing question facing policy makers today in developing a long-term strategy to manage carbon emissions from the electric power sector is how to appropriately balance investment in R&D for driving innovation in emerging low-and zero-carbon technologies with investment in commercially available technologies for meeting existing energy needs. Likewise, policy makers need to determine how to allocate limited funding across multiple technologies. Unfortunately, existing modeling tools to study these questions lack a realistic representation of electric power system operations, the innovation process, or both. In this paper, we present a new modeling framework for long-term R&D and electricity generation capacity planning that combines an economic representation of endogenous non-linear technical change with a detailed representation of the power system. The model captures the complementary nature of technologies in the power sector; physical integration constraints of the system; and the opportunity to build new knowledge capital as a non-linear function of R&D and accumulated knowledge, reflective of the diminishing marginal returns to research inherent in the energy innovation process. Through a series of numerical experiments and sensitivity analyses - with and without carbon policy - we show how using frameworks that do not incorporate these features can over-or under-estimate the value of different emerging technologies, and potentially misrepresent the cost-effectiveness of R&D opportunities.