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MIT License

The potential for repowering US wind turbines

This repository contains code to produce the figures for an analysis first presented at the EGU 2019 in the session Spatiotemporal modelling of distributed renewable energy systems (abstract). See GIT tag egu2019 for the version of this repository used for the presentation at the EGU 2019 (including the slides). An enhanced version is presented at the INFORMS Annual Meeting 2019.

For more information about the project visit https://refuel.world/.

Map of mean wind speed and wind turbines in the US

Requirements

  • dependencies: see env.yml + standard tools like GNU Make, wget; tested only with GNU/Linux
  • approx. 200GB of disk space, more than 16GB RAM
  • API key for the CDS API
  • API key for the EIA API
  • Gurobi

How to run

To install all dependencies using conda:

conda env update -f env.yml

Store the EIA API key in a plain text file eia-api-key in the repository root directory.

Activate the conda environment:

conda activate wind_repower_usa

Install the Python Gurobi API in the conda environment:

cd /opt/gurobi810/linux64/
python setup.py install

Run individual steps using Make:

make download_turbines
make download_wind_era5
make download_energy_generation
make calc_wind_speed
make calc_simulated_energy_timeseries
make calc_simulated_energy_per_location
calc_prevail_wind_direction
calc_dist_in_direction
calc_location_clusters
make calc_min_distances
make calc_optimal_locations
make calc_repower_potential
make generate_figures
make slides

There is also a combined Make target for the computation tasks:

make compute_all

Changelog

Acknowledgements

We gratefully acknowledge support from the European Research Council ("reFUEL" ERC2017-STG 758149).