aachen_technical

REFLOW: Aachen technical wind potential example workflow

Overview

This example workflow demonstrates how to use the REFLOW workflow manager to generate a technical onshore wind potential for the Aachen region. It includes the following steps:

1. Data download
2. Data preprocessing
3. Land eligibility assessment
4. Wind resource assessment / simulations
5. Visualization of results and generation of output report

The final output is two .png files that visualizes the wind potential in the Aachen region, as well as a report.json file that contains the results of the wind potential assessment.

Getting started

Prerequisites

• A Unix-like operating system (e.g. Linux, MacOS) or Git Bash on Windows
• Python
• Conda package manager (mamba HIGHLY recommended)
• Git
• A working internet connection
• Sufficient disk space to store the downloaded data (approx. 5 GB)
• A Copernicus Climate Data Store API key added to the era5_settings.json file (see below). Register here.

Initial installation

1. Clone the repository:

git clone https://jugit.fz-juelich.de/iek-3/groups/data-and-model-integration/pelser/reflow-offshore-north-sea.git

2. (Optional) Copy the contents of the "aachen_technical" directory to a new directory for easier access. This is not necessary but can be helpful for organization:

cp -r reflow-offshore-north-sea/example_workflows/aachen_technical_wind_potential /path/to/new/directory

3. Change into the repository directory:

cd reflow-offshore-north-sea
cd example_workflows/aachen_technical_wind_potential

4. Create the main REFLOW python environment:

If you are using coda:

conda env create -f required_software/requirements-reflow.yml

If you have mamba installed:

mamba env create -f required_software/requirements-reflow.yml

Before running the workflow

1. Add your Corpernicus API key in the era5_settings.json file before running the workflow. This key is required to download the data from the Copernicus Climate Data Store. You can obtain a free API key by registering on the Copernicus website. In the era5_settings.json file, replace the placeholder "ERA5_API_KEY" with your API key that you receive after registering.

2. Update paths to your conda.sh file.

   2.1. Find the path to your conda.sh file. The installation directory of your conda manager can be found by typing which conda in your bash terminal. The conda.sh file is usually located in path/to/conda/installation/etc/profile.d/conda.sh

   2.2. Copy this path and add replace the conda.sh paths with your path in the following files:

   • scripts/environment_setup/env_setup.sh
   • scripts/exclusions_placements/exclusions_placements_wrapper.sh
   • scripts/simulations/simulations_wrapper.sh

Running the workflow

1. Activate the REFLOW environment:

conda activate reflow-main

2. Run the workflow

python reflow_workflow.py

Output

1. There are log files in the logs directory that contain information about the workflow execution. These contain essential information for debugging in case of errors.

2. The workflow generates a report.json file in the output directory. This file contains the results of the wind potential assessment.

3. The workflow also generates a .png file in the output/visualizations directory that visualizes the results of the wind potential assessment.

Import information

The workflow is defined in the reflow_workflow.py file. This file contains the workflow definition, which consists of a series of tasks that are executed in sequence. Each task is defined as a Python function that performs a specific action, such as downloading data, preprocessing data, or running simulations. The tasks are connected by dependencies, which specify the order in which they should be executed.

The workflow scripts are located in the scripts directory. Each task is defined in a separate Python file, which contains a function that performs the task. In some cases, such as where a seperate python environment from the main reflow environment is required, a bash script is used to run the task.

The workflow settings are defined in files found in the settings directory. These files contain the parameters that are used by the tasks to perform their actions. Take a look through them. project_settings.json and exclusions_settings.json are arguably the most important.

It is essential to update the Corpernicus API key in the era5_settings.json file before running the workflow. This key is required to download the data from the Copernicus Climate Data Store. You can obtain a free API key by registering on the Copernicus website. In the era5_settings.json file, replace the placeholder "ERA5_API_KEY" with the UID and API key that you receive after registering. This needs to be exactly as "UID:API_KEY".

The Corpernicus Climate Data Store is used to download both the ERA5 reanalysis and the satellite land cover data. NOTE that the downloading of this data may be a bottleneck in the workflow speed, due to ongoing maintenance and updates of the Copernicus Climate Data Store.

Detailed steps

The workflow runs the scripts in the following order:

1. scripts/environment_setup/env_setup_luigi_task.py:
   • Create the additional python environments needed to run the eligibility analysis and placement script (GLAES) and the simulations script (RESKit).
   • This script is run first to ensure that the necessary software is available when the tasks that require them are run.
   • The script will first check if your computer has conda or mamba installed. If mamba, it will use this by default. If not, it will use conda.
2. scripts/data_download/project_data.py:
   • Downloads the national boundary data for Germany from the GADM database.
3. scripts/data_processing/process_project_data.py:
   • Processes the national boundary data to create a shapefile for the Aachen region.
   • transforms the shapefile to the correct projection (EPSG:3035).
4. scripts/data_download/download_exclusions_data.py:
   • Downloads the satellite land cover data from the Copernicus Climate Data Store (this is only used in the simulations to estimate the land roughness when extrapolating the wind speed to hub height).
   • Downloads the Open Street Map data from using the PyROSM package.
5. scripts/data_processing/process_exclusions_data.py:
   • Converts the satellite land cover data from netCDF to a GEOTiff raster file.
   • Processes the Open Street Map data to create shapefiles that can be used in the land eligibility assessment:
     • from the main osm.pfd file, extracts the selected exclusions as outlined in the project_settings.json file.
     • for each exclusion type, clips the data to the Aachen region and converts to the correct CRS
     • saves the processed data to the data/exclusions_data/processed directory.
6. scripts/exclusions_placements/exclusions_luigi_task.py:
   • Runs the GLAES land eligibility assessment using the processed Open Street Map data.
   • The GLAES script is run in a separate python environment to the main reflow environment.
   • Generates the aachen_exclusions.tif file in the output/geodata directory.
   • Places turbines in the Aachen region based on the land eligibility assessment.
   • Generates the aachen_turbine_placements.shp and the turbine_placements_3035.csv files in the output/geodata directory.
   • Generates the initial report.json file in the output directory.
7. scripts/data_download/meteorological_data.py:
   • Downloads the ERA5 reanalysis data from the Copernicus Climate Data Store.
   • Downloads the New European Wind Atlas (NEWA) long-term mean wind speed data from the NEWA website.
8. scripts/data_processing/process_met_data.py:
   • Processes the ERA5 reanalysis data so that it is useable by the RESKIT simulations script:
     • converts the u- and v- wind components to wind speed and direction.
     • ensures that the latitude and longitude coordinates are in the correct format.
9. scripts/data_processing/convert_placements.py:
   • Converts the turbine placements from EPSG:3035 to EPSG:4326 so that they can be used in the simulations.
10. scripts/data_processing/convert_cci_to_tif.py:
    • Converts the satellite land cover data from netCDF to a GEOTiff raster file.
    • This is used in the simulations to estimate the land roughness when extrapolating the wind speed to hub height.
11. scripts/simulations/simulations_luigi_task.py:
    • Runs the RESKIT simulations to estimate the wind speed at hub height for each turbine placement.
    • The RESKIT script is run in a separate python environment to the main reflow environment.
    • Generates the wind_power_era5_2016.csv file in the output directory.
    • Updates the report.json file in the output directory with the wind speed data.
12. scripts/visualizations/visualizations_luigi_task.py:
    • Generates a visualization of the wind speed data using the report.json file.
    • Generates the exclusions_map.png file in the output/visualizations directory.

License

This project is licensed under the MIT License - see the License in the main REFLOW directory.

Acknowledgements

The authors would like to thank the German Federal Government, the German State Governments, and the Joint Science Conference (GWK) for their funding and support as part of the NFDI4Ing consortium. Funded by the German Research Foundation (DFG) – 442146713, this work was also supported by the Helmholtz Association as part of the program “Energy System Design”.