Hybrid Optimization and Performance Platform

As part of NREL's Hybrid Energy Systems Research, this software assesses optimal designs for the deployment of utility-scale hybrid energy plants, particularly considering wind, solar and storage.

Software requirements

• Python version 3.5+ 64-bit

Installing from Source

1. Using Git, navigate to a local target directory and clone repository:

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

2. Open a terminal and navigate to /HOPP

3. Create a new virtual environment and change to it. Using Conda and naming it 'hopp':

   conda create --name hopp python=3.8 -y
   conda activate hopp
   

4. Install requirements:

   conda install -c conda-forge coin-or-cbc -y
   conda install -c conda-forge shapely==1.7.1 -y
   pip install -r requirements.txt
   

   Note if you are on Windows, you will have to manually install Cbc: https://github.com/coin-or/Cbc

5. Run install script:

   python setup.py develop
   

6. The functions which download resource data require an NREL API key. Obtain a key from:

   https://developer.nrel.gov/signup/

7. To set up the NREL_API_KEY required for resource downloads, you can create an Environment Variable called NREL_API_KEY. Otherwise, you can keep the key in a new file called ".env" in the root directory of this project.

   Create a file ".env" that contains the single line:

   NREL_API_KEY=key
   

8. Verify setup by running an example:

   python examples/simulate_hybrid.py
   

Installing from Package Repositories

1. HOPP is available as a PyPi package:

   pip install HOPP
   

   or as a conda package:

   conda install hopp -c nrel -c conda-forge -c sunpower
   

   NOTE: If you install from conda you will need to install global-land-mask from PyPi:

   pip install global-land-mask
   

2. To set up NREL_API_KEY for resource downloads, first refer to section 7 and 8 above. But for the .env file method, the file should go in the working directory of your Python project, e.g. directory from where you run python.

Examples

The examples can be run by installing HOPP, then cloning the repo and calling each example file.

Basic Simulation

python examples/simulate_hybrid.py

Flicker Map

python examples/flicker.py

Single Location Analysis

python examples/analysis/single_location.py

Wind Layout Optimization

python examples/optimization/layout_opt/wind_run.py

Hybrid Layout Optimization

python examples/optimization/layout_opt/hybrid_run.py

HOPP-demos

The https://github.com/dguittet/HOPP-demos repo contains a more full featured example with detailed technical and financial inputs, a few scenarios and the optimal PV, Wind, and Battery design results.