sector_coupling.transport_batteries_to_power module#
ftt_p_2nd_hand_batteries.py#
Second-hand batteries repurposing module
@author: Femke Nijsse
- sector_coupling.transport_batteries_to_power.get_sector_coupling_dict(data, titles)#
- sector_coupling.transport_batteries_to_power.second_hand_batteries(data, time_lag, year, titles)#
This function estimates the size of the second-hand battery market based on scrappage of electric vehicles from FTT:Tr. We use batteries from cars scrapped in the previous time step
Numbers are taken from the Xu et al (2022) paper: https://www.nature.com/articles/s41467-022-35393-0
Differences with Xu can be partially explained by the smaller size of batteries in FTT:Tr compared to their model.
- Returns:
data dictionary with updated battery capacity in GWh # Todo: check if units still correct
- Mutates:
Updates data in-place: keys ‘Second-hand batteries by age’ and ‘Second-hand battery stock’ are modified.
Estimate the battery needs in power from GW to GWh, and compute ratio with transport. The original Ueckerdt paper does not contain this information. We therefore estimate this from key numbers in the https://energy.mit.edu/research/future-of-energy-storage/
In table 6.13, in 5 gCO2 scenario, there is a factor 3.8 between the two. In table C12, in the 5 gCO2 scenario, there is a factor 4.8. Average is 4.3.
- Return type:
Share repurposed batteries compared to short-term storage needs
- sector_coupling.transport_batteries_to_power.update_costs_from_transport_batteries(data, storage_ratio, year, titles)#
Compute the new costs for storage. Repurposing batteries have costs of roughly 20-80% of new batteries, or 30% to 70%, according to:
We take a mid-point value of 50%.
- Return type:
Battery costs and new marginal costs
- sector_coupling.transport_batteries_to_power.vehicle_to_grid(data, time_lag, year, titles)#