LandBOSSE
The Land-based Balance-of-System Systems Engineering model is a systems engineering tool that estimates the balance-of-system costs associated with installing utility scale wind plants (10, 1.5 MW turbines or larger).
https://github.com/WISDEM/LandBOSSE
Category: Renewable Energy
Sub Category: Wind Energy
Keywords from Contributors
openmdao systems-engineering wind wisdem
Last synced: about 19 hours ago
JSON representation
Repository metadata
New LandBOSSE Model (Developed in 2018-2019)
- Host: GitHub
- URL: https://github.com/WISDEM/LandBOSSE
- Owner: WISDEM
- License: other
- Created: 2014-10-06T20:54:57.000Z (over 10 years ago)
- Default Branch: main
- Last Pushed: 2025-02-28T18:15:43.000Z (about 2 months ago)
- Last Synced: 2025-04-10T06:04:31.678Z (18 days ago)
- Language: Python
- Homepage:
- Size: 18.8 MB
- Stars: 16
- Watchers: 17
- Forks: 26
- Open Issues: 23
- Releases: 13
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE.txt
README.md
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.
User Guides
First, read the technical report to understand the big picture of LandBOSSE. In the technical report, you will find process diagrams, equations and the modules that implement them. Then, come back to this documentation and read the user guide.
In brief, LandBOSSE takes .xlsx
spreadsheets, reads input data from tabs on the spreadsheets, and writes the results to an output .xlsx
file. There are three sections in the user guide to demonstrate how to perform these steps.
The user guide comes in three parts:
-
Software installation,
-
Input data configuration, and
-
Output data analysis.
Software Installation
There are two options depending on whether you are a developer or an end user and what operating system you are running.
-
Windows end-user: If you run the Microsoft Windows operating system and aren't setting up as a developer who is going to be modifying the core library, these instructions are for you. Find out how to configure Windows for end users.
-
macOS end user and macOS developer: If you run the macOS operating system, either as an end-user or as a developer, these instructions are for you. Both developers and end-users will need most of the steps. Find out how to configure macOS for end users and developers.
Operation after the installation
Review the installation instructions on how to activate a virtual environment, if you haven't already.
Then, read the Operation and Folder Structure for details on running the command that executes LandBOSSE from the command line.
Owner metadata
- Name: WISDEM
- Login: WISDEM
- Email: [email protected]
- Kind: organization
- Description: The Wind-Plant Integrated System Design and Engineering Model (WISDEM (TM)) set
- Website: https://www.nrel.gov/wind/systems-engineering.html
- Location: NREL National Wind Technology Center, Boulder, CO
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/5444272?v=4
- Repositories: 40
- Last ynced at: 2023-08-07T02:31:27.458Z
- Profile URL: https://github.com/WISDEM
GitHub Events
Total
- Release event: 1
- Delete event: 1
- Issue comment event: 3
- Push event: 6
- Pull request review event: 3
- Pull request review comment event: 3
- Pull request event: 9
- Fork event: 1
- Create event: 3
Last Year
- Release event: 1
- Delete event: 1
- Issue comment event: 3
- Push event: 6
- Pull request review event: 3
- Pull request review comment event: 3
- Pull request event: 9
- Fork event: 1
- Create event: 3
Committers metadata
Last synced: 7 days ago
Total Commits: 523
Total Committers: 9
Avg Commits per committer: 58.111
Development Distribution Score (DDS): 0.442
Commits in past year: 28
Committers in past year: 3
Avg Commits per committer in past year: 9.333
Development Distribution Score (DDS) in past year: 0.071
Name | Commits | |
---|---|---|
Alicia Key | a****y@n****v | 292 |
Annika Eberle | a****e@n****v | 104 |
parangat94 | p****4@g****m | 53 |
Garrett Barter | g****r@n****v | 35 |
Paul Crook | p****k@n****v | 26 |
Aaron Barker | b****9@g****m | 7 |
Katherine Dykes | k****s@n****v | 4 |
ptrbortolotti | p****i@g****m | 1 |
WIN\jumu | j****u@d****k | 1 |
Committer domains:
Issue and Pull Request metadata
Last synced: 2 days ago
Total issues: 98
Total pull requests: 102
Average time to close issues: 2 months
Average time to close pull requests: 10 days
Total issue authors: 10
Total pull request authors: 10
Average comments per issue: 0.46
Average comments per pull request: 0.49
Merged pull request: 92
Bot issues: 0
Bot pull requests: 0
Past year issues: 1
Past year pull requests: 7
Past year average time to close issues: N/A
Past year average time to close pull requests: 7 days
Past year issue authors: 1
Past year pull request authors: 3
Past year average comments per issue: 0.0
Past year average comments per pull request: 0.57
Past year merged pull request: 7
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- akey7 (73)
- parangat94 (10)
- eberlea (5)
- badeshiben (3)
- dykesk (2)
- ChristopherCampos (1)
- jrleee (1)
- FlorianMandel (1)
- ptrbortolotti (1)
- tejedor24 (1)
Top Pull Request Authors
- akey7 (63)
- gbarter (15)
- parangat94 (11)
- crookp (5)
- eberlea (2)
- badeshiben (2)
- ChristopherCampos (1)
- ptrbortolotti (1)
- barker59 (1)
- jp5000 (1)
Top Issue Labels
- enhancement (14)
- input enhancement (14)
- approved (11)
- output enhancement (11)
- analysis script (9)
- bug (9)
- parametrics (8)
- epic enhancement (1)
Top Pull Request Labels
- approved (5)
- ready (3)
- being reviewed (2)
- enhancement (1)
- not started (1)
- changes requested (1)
Package metadata
- Total packages: 3
-
Total downloads:
- pypi: 742 last-month
- Total dependent packages: 0 (may contain duplicates)
- Total dependent repositories: 1 (may contain duplicates)
- Total versions: 37
- Total maintainers: 1
proxy.golang.org: github.com/wisdem/landbosse
- Homepage:
- Documentation: https://pkg.go.dev/github.com/wisdem/landbosse#section-documentation
- Licenses: other
- Latest release: v2.6.0+incompatible (published 2 months ago)
- Last Synced: 2025-04-26T14:02:15.325Z (2 days ago)
- Versions: 9
- Dependent Packages: 0
- Dependent Repositories: 0
-
Rankings:
- Dependent packages count: 6.999%
- Average: 8.173%
- Dependent repos count: 9.346%
proxy.golang.org: github.com/WISDEM/LandBOSSE
- Homepage:
- Documentation: https://pkg.go.dev/github.com/WISDEM/LandBOSSE#section-documentation
- Licenses:
- Latest release: v2.6.0+incompatible (published 2 months ago)
- Last Synced: 2025-04-26T14:02:15.792Z (2 days ago)
- Versions: 9
- Dependent Packages: 0
- Dependent Repositories: 0
-
Rankings:
- Dependent packages count: 6.999%
- Average: 8.173%
- Dependent repos count: 9.346%
pypi.org: landbosse
LandBOSSE
- Homepage: https://github.com/WISDEM/LandBOSSE
- Documentation: https://landbosse.readthedocs.io/
- Licenses: other
- Latest release: 2.3.0 (published over 4 years ago)
- Last Synced: 2025-04-26T14:02:15.671Z (2 days ago)
- Versions: 19
- Dependent Packages: 0
- Dependent Repositories: 1
- Downloads: 742 Last month
-
Rankings:
- Dependent packages count: 7.31%
- Forks count: 8.272%
- Stargazers count: 14.537%
- Average: 16.31%
- Dependent repos count: 22.088%
- Downloads: 29.345%
- Maintainers (1)
Dependencies
- actions/checkout v4 composite
- actions/setup-python v4 composite
- conda-incubator/setup-miniconda v2 composite
- numpy *
- openpyxl *
- pandas *
- scipy *
- xlsxwriter *
- et-xmlfile
- numpy
- openmdao
- openpyxl
- pandas
- pip
- pytest
- python
- scipy
- setuptools
- xlsxwriter
Score: 12.472827258298958