LandBOSSE

Welcome to LandBOSSE!

The Land-based Balance-of-System Systems Engineering (LandBOSSE) model is a systems engineering tool that estimates the balance-of-system (BOS) costs associated with installing utility scale wind plants (10, 1.5 MW turbines or larger). It can execute on macOS and Windows. At this time, for both platforms, it is a command line tool that needs to be accessed from the command line.

The methods used to develop this model (specifically, LandBOSSE Version 2.1.0) are described in greater detail the following report:

Eberle, Annika, Owen Roberts, Alicia Key, Parangat Bhaskar, and Katherine Dykes. 2019. NREL’s Balance-of-System Cost Model for Land-Based Wind. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-72201. https://www.nrel.gov/docs/fy19osti/72201.pdf.

Installation

For any installation, users should use a virtual environment. We recommend Miniconda or Anaconda, but any supporting PyPI or source installations are possible. Here, we'll work with conda for compatibility with other NREL tools.

In the below, you can replace the name "landbosse" with any name you choose, and the Python version can be any that you prefer as long as it's supported by LandBOSSE.

conda create -n landbosse python=3.13 -y

PyPI

pip install NREL-landbosse

Source

1. Navigate to your preferred installation location

2. Clone the repo (or fork and clone your fork, if preferred).

   git clone https://github.com/NLRWindSystems/LandBOSSE.git

3. Enter the directory and install the local version

   cd LandBOSSE
   pip install .

   Optional: pip install -e . for editable installations if you plan to modify the code itself.

User Guides

First time running teh model

At its most basic, the following setup is required, though the provided input data in project_inpute_template can be used to test out the model and view results before diving into configuring custom scenarios.

1. Create an "input" and "output" folder for LandBOSSE to access. If you are using a source installation, then ensure the folders are not located inside the local copy of the repository.
2. Create a project_list.xlsx like LandBOSSE/project_list.xlsx and a subfolder called project_data inside of inputs.
3. Each project in project_list.xlsx should have a corresponding Excel file in project_data similar to the examples in LandBOSSE/project_input_template/project_data.

Running the model

Once the initial steps (above) are followed, we can run the model:

1. Activate your virtual environment: `conda activate landbosse
2. Navigate to the top-level LandBOSSE folder
3. Run the model: python main.py -i input-folder-path -o output-folder-path (be sure to replace "input-folder-path" and "output-folder-path" with your respective input and output folders).

All together

conda activate landbosse
cd /path/to/LandBOSSE
python main.py -i /path/to/inputs -o /path/to/outputs
conda deactivate

4. View your results in the output folder.

Integrating LandBOSSE into your code

While LandBOSSE was originally designed as a CLI tool powered by Excel workbooks, an API also exists to run the model within another application.

Further documentation coming soon