Add multiplier to limit use of out-of-region values in endogenous learning calculations

Currently, endogenous learning calculations for relevant technologies (solar, wind, CCS, batteries, hydrogen electrolyzers) are made based on a global baseline and global deployment data. This means that in-region policies have relatively little affect on the speed of learning and cost declines, as any one region (even a large region, such as the U.S.) has a small effect on the global total. But, to take one example, it's not clear that the learning rate for state-of-the-art batteries in the U.S. should be strongly dependent on how many inexpensive EVs there are in India or China. Perhaps only a share of the out-of-region installed base, and out-of-region deployment, should be added to in-region values for endogenous learning purposes.

Consider introducing a new variable that contains multipliers that limit the share of the out-of-region values that are included when considering endogenous learning baseline and deployment for each technology. Perhaps a single (non-subscripted) multiplier is suitable for all technologies that use endogenous learning.

EnergyInnovation / eps-us

Add multiplier to limit use of out-of-region values in endogenous learning calculations #55