reView is a data portal for reviewing outputs from the National Renewable Energy Laboratory's (NREL) Renewable Energy Potential Model (reV). It is currently limited to tables generated by the reV Supply Curve module, which provide technical potential data for a given technology under a set of land-use, technology performance, and cost assumptions. Once a user has generated tables withreV, reView allows that user to view the data as an interactive map linked to an interactive graph, allowing for quick exploration of reV outputs. Other functionality allows the user to filter the dataset based on variable thresholds, calculate differences between two tables, compare multiple tables in one chart, group results by region, and calculate least-cost scenarios at each point. More functionality is coming soon.

1. Clone the reView repository.

   Using ssh:

   git clone [email protected]:NREL/reView.git
   

   Using https:

   git clone https://github.com/NREL/reView.git
   

2. cd into the repository: cd reView.

3. Install Package and Dependencies

   1. RECOMMENDED OPTION
      Using conda/mamba ():

      1. Create a conda environment:

         conda env create -f environment.yml
         

      2. Activate the environment:

         conda activate review
         

      3. Install reView:
         For users:

         pip install -e .
         

         For developers:

         pip install -e '.[dev]'
         

   2. CHOOSE YOUR OWN ADVENTURE
      Using pip:

      1. Create and activate an environment with your tool of choice
      2. Install GEOS dependency (https://libgeos.org/usage/install/).
      3. Install reView:
         For users:

         pip install -e .
         

         For developers:

         pip install -e '.[dev]'
         

   Note:
   The pip approach has not been tested by the reView package maintainers.

4. Create a project config pointing to directory containing reV supply curve tables. Save as json dictionary in configs/ (e.g. configs/sample.json). If the user doesn't have reV data, they can get started with supply-curves for NREL's standard scenarios based on the Electricity Annual Technology Baseline through NREL's Geospatial Data Science group. Supply curves for wind power are available here and those for solar photovoltaic power are available here.

   {
       "project_name": <"Your Project Name>",
       "directory": <"Local path to folder containing reV supply curve tables">
   }

1. Run the reView command:

   reView
   

2. Open your browser and enter the URL output from command above. The default port is 8050.

   http://localhost:8050
   

1. To run reView using gunicorn (a Python WSGI HTTP Server for UNIX) for better performance, make sure to follow the installation steps as outlined above, but when you get to the last step of #2, include the gunicorn dependency:

   pip install -e '.[gunicorn]'
   

   or, for more development tools:

   pip install -e '.[dev,gunicorn]'
   

2. Run reView using gunicorn:

   cd reView
   gunicorn index:server
   

3. Open your browser and enter the URL output from command above. The default port is 9875.

   http://localhost:9875
   

Additional command-line tools are available as part of this package. A list of these tools can be accessed using the command reView-tools. More information on the usage of these tools can be found in the Usage documentation.

This repository uses pylint to lint the code, please follow this guideline if you wish to contribute to this repository. In addition, your code must pass all existing tests. You will need to download the Chrome Driver in order to run the integration tests included with this repository.

Before pushing code, the following commands should be run to ensure GitHub actions will succeed:

pylint reView
pylint tests

flake8 reView
flake8 tests

pytest