UK Low Carbon Technology Database (UKLCTD)

UK Low Carbon Technology Database (UKLCTD)

Version used for revised paper submitted to Nature Energy: Sheridan Few, Predrag Djapic, Gpran Strbac, Jenny Nelson, Chiara Candelise, "A geographically disaggregated approach to integrate low-carbon technologies across local electricity networks"

Overview

This repository contains:

(1) The United Kingdom Low Carbon Technology Database (UKLCTD), a collection of real geographically disaggregated data on current deployment of small scale photovoltaics (PV), heat pumps (HPs), electric vehicles (EVs), network inrastructure, domestic and nondomestic meter density, electricity demand, and rurality at an LSOA / Scottish Data Zone level. (UKLCTD.csv)

(2) Scenarios for future deployment of PV, HPs, EVs, and battery storage upto 2050 at an LSOA level based upon current data, National Grid's Future Energy Scenarios (FES) and UKPN, NPG, and WPD's Distribution Future Energy Scenarios (DFES). (UKLCTD_Scenarios_DFES_base_[date].csv, 2050 file has PV deployment capped at two per meter)

(3) Raw data from which each of the above are generated, and R scripts used to generate the above databases from raw data. Links to sources of raw data are included in scripts to facilitate upadates to this framework as new data becomes available. (UKLCTD.zip)

Usage

R scripts in the zip file have a short comment at the start describing their function. Before running, 'root_path' variable will need to be updated in each script to reflect the path these files are kept in on your local repository.

The data may be explored using the following script:

- Import_UKLCTD.R

To generate the UKLCTD and scenarios from scratch, scripts are intended to be run in this order (names mostly self explanatory)

- Generate_UKLCTD.R
- Add_substations_to_UKLCTD.R
- Add_Scottish_rurality_to_UKLCTD.R
- Generate_NG_scenarios.R
- Add_DFES_scenarios_w_plot.R
- Cap_Deployment.R

Each of these scripts generates data used by subsequent scripts. These are broken down into stages and commented as far as possible.

Data Structure

Data: All raw data is in "Input_Data". This data can be updated as new information becomes available (input data files, sheets, and cells referred to in the above scripts will likely need to be updated accordingly). Data produced by these scripts in "Intermediate Data" and "Output Data" folders depending on whether it is used by subsequent scripts. Plots are generated in the "Plots" folder

Attribution

If this framework has been useful, please cite the following papers outlining our methodology:

Few, S., Djapic, P., Strbac, G., Nelson J., Candelise C. A geographically disaggregated approach to integrate low-carbon technologies across local electricity networks. Nat Energy (2024). https://doi.org/10.1038/s41560-024-01542-6

Few, S., Djapic, P., Strbac, G., Nelson J., Candelise C. Assessing Local Costs and Impacts of Distributed Solar PV Using High Resolution Data from across Great Britain. Renewable Energy 162 (2020) 1140–50. https://doi.org/10.1016/j.renene.2020.08.025