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Annual Technology Baseline Calculators

To inform electric and transportation sector analysis in the United States, each year NREL provides a robust set of modeling input assumptions for energy technologies and a diverse set of potential electricity generation futures or modeling scenarios.
https://github.com/nrel/atb-calc

Category: Energy Systems
Sub Category: Energy Data Accessibility and Integration

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Python files and Jupyter notebooks for processing the Annual Technology Baseline (ATB) electricity data and determining LCOE and other metrics.

README.md

Annual Technology Baseline Calculators (ATB-calc)

Python 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.

Installation and Requirements

The pipeline requires Python 3.10 or newer. Dependancies can be installed using pip:

$ pip install -r requirements.txt

Note that some examples may require additional dependencies such as Jupyter. See the README files in individual
directories for specifics.

Once Python and all dependancies are installed the installation can be tested by running:

$ pytest

Tests take about a minute and should complete without errors. The ATB pipeline uses xlwings 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.

Running the ATB Electricity Pipeline

Running the pipeline requires downloaded the most current data in xlsx format from the
ATB website. The pipeline may be ran for one or all ATB electricity technologies.
Data may be exported in several formats. Below are several example workflows. It is assumed that all
commands are run from the root directory of the repository. In the examples {PATH-TO-DATA-WORKBOOK}
is the path and filename to the ATB electricity data workbook xlsx file.

Process all techs and export to a flat file named flat_file.csv:

$ python -m lcoe_calculator.process_all --save-flat flat_file.csv {PATH-TO-DATA-WORKBOOK}

Process only land-based wind and export pivoted data and meta data:

$ python -m lcoe_calculator.process_all --tech LandBasedWindProc \
	--save-pivoted pivoted_file.csv --save-meta meta_file.csv {PATH-TO-DATA-WORKBOOK}

Process only pumped storage hydropower and copy data to the clipboard so it may be pasted into a spreadsheet:

$ python -m lcoe_calculator.process_all --tech PumpedStorageHydroProc \
	--clipboard {PATH-TO-DATA-WORKBOOK}

Help for the processor and the names of available technologies can be viewed by running:

$ python -m lcoe_calculator.process_all --help

Debt Fraction Calculator

The debt fraction calculator uses PySAM to calculate
debt fractions for one or all ATB technologies. To calculate debt fractions for all technologies run
the following from the repository root directory:

$ python -m  debt_fraction_calculator.debt_fraction_calc {PATH-TO-DATA-WORKBOOK} \
	{OUTPUT-CSV-FILE}

where {PATH-TO-DATA-WORKBOOK} is the path and filename of the ATB data workbook, and
{OUTPUT-CSV-FILE} is the name of the csv file to create with the calculated debt fractions.

Debt fractions can also be calculated for a single ATB technology if desired. The below command will
calculate debt fractions for land-based wind:

$ python -m debt_fraction_calculator.debt_fraction_calc --tech LandBasedWindProc \
	{PATH-TO-DATA-WORKBOOK} {OUTPUT-CSV-FILE}

All options for the debt calculator can be viewed with:

$ python -m debt_fraction_calculator.debt_fraction_calc --help

Example Jupyter Notebooks

The ./example_notebooks directory has several Jupyter notebooks showing
how to perform various tasks. The notebooks are a good way to understand how to use the code and
experiment with the ATB pipeline code. Jupyter must first be installed before use:

$ pip install jupyter

The Jupyter server can then be started by running:

$ jupyter-notebook

in the root repository directory.

Notable Directories

  • ./lcoe_calculator Extract technology metrics from the data workbook xlsx file and calculate LCOE
    using Python.
  • ./debt_fraction_calculator Given data and assumptions in the data workbook xlsx file, calculate
    debt fractions using PySAM.
  • ./example_notebooks Example Jupyter notebooks showing how to perform various operations.
  • ./tests Tests for code in this repository.

Citing this Package

Mirletz, Brian, Bannister, Michael, Vimmerstedt, Laura, Stright, Dana, and Heine, Matthew.
"ATB-calc (Annual Technology Baseline Calculators) [SWR-23-60]." Computer software. August 02, 2023.
https://github.com/NREL/ATB-calc. https://doi.org/10.11578/dc.20230914.2.

Code Formatting

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