Hybrid project power-to-x component-level system performance and financial modeling for control and design optimization. GreenHEART currently includes renewable energy, hydrogen, ammonia, and steel. Other elements such as desalination systems, pipelines, compressors, and storage systems can also be included as needed.
For more context about GreenHEART and to see analyses that have been performed using the tool, please see some of these publications. PDFs are available in the linked titles.
The levelized cost of hydrogen is calculated for varying technology costs, and tax credits to explore cost sensitivities independent of plant design, performance, and site selection. Our findings suggest that strategies for cost reduction include selecting sites with abundant wind resources, complementary wind and solar resources, and optimizing the sizing of wind and solar assets to maximize the hybrid plant capacity factor.
Grant, E., et al. "Hybrid power plant design for low-carbon hydrogen in the United States." Journal of Physics: Conference Series. Vol. 2767. No. 8. IOP Publishing, 2024.
Conducting a regional techno-economic analysis at four U.S. coastal sites, the study evaluates two energy transmission configurations and examines associated costs for the years 2025, 2030, and 2035. The results highlight that locations using fixed-bottom technology may achieve cost-competitive water electrolysis hydrogen production by 2030 through leveraging geologic hydrogen storage and federal policy incentives.
Brunik, K., et al. "Potential for large-scale deployment of offshore wind-to-hydrogen systems in the United States." Journal of Physics: Conference Series. Vol. 2767. No. 6. IOP Publishing, 2024.
Modeling results suggest that the levelized cost of storage is highly spatially heterogeneous, with minor impact on the cost of H2 in the Midwest, and potentially significant impact in areas with emerging H2 economies such as Central California and the Southeast. While TOL/MCH may be the cheapest aboveground bulk storage solution evaluated, upfront capital costs, modest energy efficiency, reliance on critical materials, and greenhouse gas emissions from heating remain concerns.
Breunig, Hanna, et al. "Hydrogen Storage Materials Could Meet Requirements for GW-Scale Seasonal Storage and Green Steel." (2024).
King, J. and Hammond, S. "Integrated Modeling, TEA, and Reference Design for Renewable Hydrogen to Green Steel and Ammonia - GreenHEART" (2024).
GreenHEART is available as a PyPi package:
pip install greenheart
Using Git, navigate to a local target directory and clone repository:
git clone https://github.com/NREL/GreenHEART.git
Navigate to GreenHEART
cd GreenHEART
Create a new virtual environment and change to it. Using Conda and naming it 'greenheart':
conda create --name greenheart python=3.9 -y
conda activate greenheart
Install GreenHEART and its dependencies:
conda install -y -c conda-forge coin-or-cbc=2.10.8 glpk
pip install electrolyzer@git+https://github.com/jaredthomas68/electrolyzer.git@smoothing
pip install ProFAST@git+https://github.com/NREL/ProFAST.git
Note if you are on Windows, you will have to manually install Cbc: https://github.com/coin-or/Cbc.
If you want to just use GreenHEART:
pip install .
If you want to work with the examples:
pip install ".[examples]"
If you also want development dependencies for running tests and building docs:
pip install -e ".[develop]"
In one step, all dependencies can be installed as:
pip install -e ".[all]"
The functions which download resource data require an NREL API key. Obtain a key from:
To set up the NREL_API_KEY
and NREL_API_EMAIL
required for resource downloads, you can create
Environment Variables called NREL_API_KEY
and NREL_API_EMAIL
. 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
NREL_API_EMAIL=your.name@email.com
Verify setup by running tests:
pytest
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
.
GreenHEART is set up to run in parallel using MPI and PETSc for finite differencing and for design of experiments runs through OpenMDAO. To use this capability you will need to follow the addtional installation instruction below:
conda install -c conda-forge mpi4py petsc4py
For more details on implementation and installation, reference the documentation for OpenMDAO.
To to check that your installation is working, do the following:
cd tests/greenheart/
mpirun -n 2 pytest test_openmdao_mpi.py
The Examples contain Jupyter notebooks and sample YAML files for common usage scenarios in GreenHEART. These are actively maintained and updated to demonstrate GreenHEART's capabilities. For full details on simulation options and other features, documentation is forthcoming.
Interested in improving GreenHEART? Please see the Contributing section for more information.