The interplay of the innovation cycle, build time, lifetime, and deployment rate of new energy technologies: a case study of nuclear fusion energy

Abstract

Abstract This article analyses how a forced transition to low-carbon energy impacts the innovation of new energy technologies. We apply the insights to nuclear fusion, potentially a large provider of carbon-free energy currently attracting billions in private investments. We discuss the ‘fastest-feasible-growth (FFG)’ curve for transitions: exponential growth followed by linear growth, where the rate of latter is limited by the inverse lifetime of the installation. We analyse how innovation is affected if, during rapid deployment, a technology progresses through several generations. We identify key timescales: the learning time, the generation time, the build time, and the exponential growth time of the early deployment phase and compare these for different energy technologies. We distinguish learning rate-limited and generation-time-limited innovation. Applying these findings to fusion energy, we find that a long build time may slow deployment, slow learning, and promote early technology lock-in. Slow learning can be remedied by developing multiple concepts in parallel. Probabilistic analysis of value implies that the optimal strategy is to parallelize the development of many concepts. This concurs with the present surge in private investment in multiple concepts. For this strategy to be successful, the build time of the power plant must be minimized. This requirement favours concepts that lend themselves to modularization and parallelization of production and assembly.