A global and local endogenous experience curve model for projecting future uptake and cost of electricity generation technologies

- Local and global experience curves have been developed for various technologies.
- The 'penalty' constraint has been developed to endogenously mimic market forces.
- The 'penalty' constraint increases the capital cost of high-demand technologies.
- The 'penalty' constraint leads to smooth uptake of technologies and their capital costs.
- The 'penalty' constraint reduces the sensitivity of the model to the learning rate.

A global and local learning model (GALLM) has been developed to project the cost and global uptake of different electricity generation technologies to the year 2050. This model features three regions, endogenous technological learning within and across those regions, various government policies to facilitate technological learning and a penalty constraint which is used to mimic the effect market forces play on the capital cost of electricity generation technologies. This constraint has been added as market forces have been a strong factor in technology pricing in recent years. Global, regional and component experience curves have been developed for some technologies. The model, with the inclusion of these features, projects a diverse range of technologies contributing to global electricity generation under a carbon price scenario. The penalty constraint leads to gradual and continual installations of technologies and because the constraint provides a disincentive to install too much of a technology, it reduces the impact of uncertainty in the learning rate. Alternative forms of the penalty constraint were tested for their suitability; it was found that, with a zero and lower-cost version of the constraint, photovoltaics are installed in a boom-and-bust cycle, which is not supported by past experience. When the constraint is set at a high level, there are fewer installations.