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Systems","sub_category":"Energy Data Accessibility and Integration","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"# Annual Technology Baseline Calculators (ATB-calc)\n\nPython files and Jupyter notebooks for processing the Annual Technology Baseline (ATB) electricity data and determining LCOE and other metrics. All documentation and data for the ATB is available at the [ATB website](https://atb.nrel.gov).\n\n## Installation and Requirements\n\nThe pipeline requires [Python](https://www.python.org) 3.10 or newer. Dependancies can be installed using `pip`:\n\n```\n$ pip install -r requirements.txt\n```\n\nNote that some examples may require additional dependencies such as Jupyter. See the README files in individual\ndirectories for specifics.\n\nOnce Python and all dependancies are installed the installation can be tested by running:\n\n```\n$ pytest\n```\n\nTests take about a minute and should complete without errors. The ATB pipeline uses [xlwings](https://www.xlwings.org/) for accessing the ATB data workbook and requires a copy of Microsoft Excel. Currently the full pipeline will only run on MacOS and Windows. Linux support may be added in the future.\n\n## Running the ATB Electricity Pipeline\n\nRunning the pipeline requires downloaded the most current data in `xlsx` format from the\n[ATB website](https://atb.nrel.gov). The pipeline may be ran for one or all ATB electricity technologies.\nData may be exported in several formats. Below are several example workflows. It is assumed that all\ncommands are run from the root directory of the repository. In the examples `{PATH-TO-DATA-WORKBOOK}`\nis the path and filename to the ATB electricity data workbook `xlsx` file.\n\nProcess all techs and export to a flat file named `flat_file.csv`:\n\n```\n$ python -m lcoe_calculator.process_all --save-flat flat_file.csv {PATH-TO-DATA-WORKBOOK}\n```\n\nProcess only land-based wind and export pivoted data and meta data:\n\n```\n$ python -m lcoe_calculator.process_all --tech LandBasedWindProc \\\n\t--save-pivoted pivoted_file.csv --save-meta meta_file.csv {PATH-TO-DATA-WORKBOOK}\n```\n\nProcess only pumped storage hydropower and copy data to the clipboard so it may be pasted into a spreadsheet:\n\n```\n$ python -m lcoe_calculator.process_all --tech PumpedStorageHydroProc \\\n\t--clipboard {PATH-TO-DATA-WORKBOOK}\n```\n\nHelp for the processor and the names of available technologies can be viewed by running:\n\n```\n$ python -m lcoe_calculator.process_all --help\n```\n\n## Debt Fraction Calculator\n\nThe debt fraction calculator uses [PySAM](https://nrel-pysam.readthedocs.io/en/main/) to calculate\ndebt fractions for one or all ATB technologies. To calculate debt fractions for all technologies run\nthe following from the repository root directory:\n\n```\n$ python -m  debt_fraction_calculator.debt_fraction_calc {PATH-TO-DATA-WORKBOOK} \\\n\t{OUTPUT-CSV-FILE}\n```\n\nwhere `{PATH-TO-DATA-WORKBOOK}` is the path and filename of the ATB data workbook, and\n`{OUTPUT-CSV-FILE}` is the name of the `csv` file to create with the calculated debt fractions.\n\nDebt fractions can also be calculated for a single ATB technology if desired. The below command will\ncalculate debt fractions for land-based wind:\n\n```\n$ python -m debt_fraction_calculator.debt_fraction_calc --tech LandBasedWindProc \\\n\t{PATH-TO-DATA-WORKBOOK} {OUTPUT-CSV-FILE}\n```\n\nAll options for the debt calculator can be viewed with:\n\n```\n$ python -m debt_fraction_calculator.debt_fraction_calc --help\n```\n\n## Example Jupyter Notebooks\n\nThe `./example_notebooks` directory has several [Jupyter](https://jupyter.org/) notebooks showing\nhow to perform various tasks. The notebooks are a good way to understand how to use the code and\nexperiment with the ATB pipeline code. Jupyter must first be installed before use:\n\n```\n$ pip install jupyter\n```\n\nThe Jupyter server can then be started by running:\n\n```\n$ jupyter-notebook\n```\n\nin the root repository directory.\n\n## Notable Directories\n\n- `./lcoe_calculator` Extract technology metrics from the data workbook `xlsx` file and calculate LCOE\n  using Python.\n- `./debt_fraction_calculator` Given data and assumptions in the data workbook xlsx file, calculate\n  debt fractions using PySAM.\n- `./example_notebooks` Example Jupyter notebooks showing how to perform various operations.\n- `./tests` Tests for code in this repository.\n\n## Citing this Package\n\nMirletz, Brian, Bannister, Michael, Vimmerstedt, Laura, Stright, Dana, and Heine, Matthew.\n\"ATB-calc (Annual Technology Baseline Calculators) [SWR-23-60].\" Computer software. August 02, 2023.\nhttps://github.com/NREL/ATB-calc. https://doi.org/10.11578/dc.20230914.2.\n\n## Code Formatting\n\nThis project uses the [Black](https://black.readthedocs.io/en/stable/index.html) code formatting VS Code [plugin](https://marketplace.visualstudio.com/items?itemName=ms-python.black-formatter). Please install and run the plugin before making commits or a pull request.\n","funding_links":[],"readme_doi_urls":["https://doi.org/10.11578/dc.20230914.2"],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":[],"project_url":"https://ost.ecosyste.ms/api/v1/projects/302778","html_url":"https://ost.ecosyste.ms/projects/302778"}