Model coupling issues

[Femkemilene]

Couple the FTT models with the following four aspects

• Electriciy demand; heat, transport and steel should feed back to electricity
• Electricity price: add the elasticity from the X-databank (elasticity is econometrically estimated). Feed electricity price into the other models.
• Cross-learning: specifically in terms of electricity storage
• RLDC: add some uncertainty from literature on additional strain on grid

[pv-camecon]

This sounds like we need to iterate between the electricity users and suppliers within each year until prices and demand have converged. Not impossible and I wouldn't think it would take many interations to find convergence.

If we are to implement this in the master version, then it would be great to have a switch available that allows us to undo the coupling. The reason being that during update cycles, we'd want to compare E3ME output to the standalone output (using inputs from E3ME) to check the FTT results align.

On learning: Perhaps we need to run all FTTs in a single timeloop. It would be pose a couple of design issues, but it does allow us to combine the cross-sectoral learning effects wherever they may apply.