A-LEAF plugin

CHANGELOG.md

@@ -16,6 +16,8 @@ and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.
   ([#107](https://github.com/watts-dev/watts/pull/107))
 * GCMAT plugin via the `PluginGCMAT` class
   ([#114](https://github.com/watts-dev/watts/pull/114))
+* A-LEAF plugin via the `PluginALEAF` class
+  ([#119](https://github.com/watts-dev/watts/pull/119))
 
 ### Changes
 

doc/source/reference/index.rst

@@ -14,6 +14,7 @@ API Reference
    watts.PluginGeneric
    watts.PluginABCE
    watts.PluginACCERT
+   watts.PluginALEAF
    watts.PluginGCMat
    watts.PluginMCNP
    watts.PluginMOOSE

doc/source/user/plugins.rst

@@ -335,6 +335,45 @@ As with other plugins, :class:`~watts.PluginABCE` is easily used by::
 .. note::
     `ABCE` is still under active development.
 
+A-LEAF Plugin
++++++++++++++
+The :class:`~watts.PluginALEAF` class enables simulations with the Argonne 
+Low-carbon Electricity Analysis Framework (A-LEAF) code using a text based 
+input file for fuel price modification. The A-LEAF code using an excel based
+input file, and the A-LEAF plugin will only modify the fuel price under the
+``Fuel`` section of the input file. Since A-LEAF code is still under
+active development, the plugin will be updated as the code is updated.
+
+The A-LEAF fuel price input file can be templated as follows:
+
+.. code-block:: jinja
+
+    Scenario	FUEL	Type	Unit	2022	2023	2024	2025	2026	...
+
+    Reference	Coal	Real	2022 $/MMBtu	1.64	1.61	1.65	1.57	1.52	...
+    ...
+    Base	Nuclear	Real	2020 $/MMBTU	{% for year, price in fuel_price.items() %}
+    {{ price }}{% if not loop.last %}	{% endif %}{% endfor %}
+    Base	Biomass	Real	2020 $/MMBTU	5.00	5.11	5.22	5.34	5.45	...
+    ...
+    Low	OGS	Real	2020 $/MMBTU	3.30	3.00	2.73	2.58	2.56	...
+
+Before running the A-LEAF plugin, you need to specify the directory that the
+executable and the license key are in (they must be in the same directory). This
+can be done by adding the ``A-LEAF_DIR`` variable to the environment or by
+explicitly specifying the path in the Python script as::
+
+    aleaf_plugin = watts.PluginALEAF(
+        'aleaf_template',
+        executable="/path/to/A-LEAF",
+        extra_inputs=[]
+    )
+
+As with other plugins, :class:`~watts.PluginALEAF` can be used by calling the
+:meth:`~watts.PluginALEAF` instance directly the same way as other plugins.
+    aleaf_plugin = watts.PluginALEAF('aleaf_template')
+    aleaf_result = aleaf_plugin(params)
+
 
 Dakota Plugin
 +++++++++++++

examples/1App_ALAEF_LCGTEP/Fuel.txt

@@ -0,0 +1,19 @@
+Scenario	FUEL	Type	Unit	2022	2023	2024	2025	2026	2027	2028	2029	2030	2031	2032	2033	2034	2035	2036	2037	2038	2039	2040	2041	2042	2043	2044	2045	2046	2047	2048	2049	2050	2051	2052	2053	2054	2055	2056	2057	2058	2059	2060
+Reference	Coal	Real	2021 $/MMBtu	1.64	1.61	1.65	1.57	1.52	1.50	1.49	1.50	1.50	1.50	1.50	1.50	1.51	1.52	1.53	1.54	1.56	1.56	1.58	1.59	1.60	1.60	1.62	1.63	1.64	1.65	1.65	1.66	1.66	1.75	1.85	1.96	2.07	2.19	2.31	2.44	2.58	2.73	2.89
+Reference	NG	Real	2021 $/MMBtu	3.84	3.49	3.17	3.00	2.98	3.08	3.25	3.36	3.46	3.54	3.58	3.65	3.64	3.64	3.65	3.67	3.68	3.69	3.72	3.73	3.70	3.71	3.65	3.61	3.60	3.60	3.62	3.60	3.59	3.80	4.01	4.24	4.48	4.74	5.01	5.29	5.59	5.91	6.25
+Reference	Petroleum	Real	2021 $/MMBtu	12.18	10.50	11.39	11.61	11.89	12.20	12.46	12.58	12.82	13.08	13.27	13.42	13.54	13.67	13.86	14.03	14.20	14.26	14.55	14.70	14.75	15.00	15.28	15.36	15.58	15.65	15.62	15.65	15.59	16.48	17.42	18.41	19.46	20.57	21.74	22.98	24.29	25.68	27.14
+Reference	Nuclear	Real	2021 $/MMBtu	0.72	0.72	0.72	0.72	0.72	0.73	0.73	0.73	0.73	0.73	0.73	0.74	0.74	0.74	0.74	0.74	0.74	0.75	0.75	0.75	0.75	0.76	0.76	0.76	0.76	0.76	0.77	0.77	0.77	0.81	0.86	0.91	0.96	1.02	1.07	1.14	1.20	1.27	1.34
+Reference	Biomass	Real	2020 $/MMBTU	5.00	5.11	5.22	5.34	5.45	5.57	5.70	5.82	5.95	6.08	6.22	6.35	6.49	6.63	6.78	6.93	7.08	7.24	7.40	7.56	7.73	7.90	8.07	8.25	8.43	8.61	8.80	9.00	9.20	9.72	10.27	10.86	11.48	12.13	12.82	13.56	14.33	15.15	16.01
+Reference	OGS	Real	2020 $/MMBTU	3.84	3.49	3.17	3.00	2.98	3.08	3.25	3.36	3.46	3.54	3.58	3.65	3.64	3.64	3.65	3.67	3.68	3.69	3.72	3.73	3.70	3.71	3.65	3.61	3.60	3.60	3.62	3.60	3.59	3.80	4.01	4.24	4.48	4.74	5.01	5.29	5.59	5.91	6.25
+Base	Coal	Real	2020 $/MMBTU	1.57	1.54	1.57	1.50	1.45	1.43	1.43	1.43	1.43	1.44	1.43	1.43	1.44	1.45	1.46	1.47	1.49	1.49	1.51	1.52	1.52	1.53	1.54	1.56	1.56	1.57	1.57	1.58	1.58	1.67	1.77	1.87	1.98	2.09	2.21	2.33	2.47	2.61	2.76
+Base	NG	Real	2020 $/MMBTU	3.67	3.34	3.03	2.87	2.84	2.94	3.10	3.21	3.30	3.38	3.42	3.48	3.48	3.47	3.48	3.50	3.52	3.52	3.55	3.56	3.54	3.54	3.48	3.45	3.44	3.43	3.46	3.44	3.43	3.62	3.83	4.05	4.28	4.52	4.78	5.05	5.34	5.65	5.97
+Base	Petroleum	Real	2020 $/MMBTU	11.63	10.03	10.88	11.09	11.35	11.65	11.90	12.01	12.24	12.49	12.68	12.82	12.93	13.05	13.24	13.40	13.56	13.61	13.90	14.04	14.09	14.32	14.60	14.67	14.88	14.95	14.92	14.94	14.89	15.74	16.63	17.58	18.58	19.64	20.76	21.95	23.20	24.52	25.92
+Base	Nuclear	Real	2020 $/MMBTU	{% for year, price in fuel_price.items() %}{{ price }}{% if not loop.last %}	{% endif %}{% endfor %}
+Base	Biomass	Real	2020 $/MMBTU	5.00	5.11	5.22	5.34	5.45	5.57	5.70	5.82	5.95	6.08	6.22	6.35	6.49	6.63	6.78	6.93	7.08	7.24	7.40	7.56	7.73	7.90	8.07	8.25	8.43	8.61	8.80	9.00	9.20	9.72	10.27	10.86	11.48	12.13	12.82	13.56	14.33	15.15	16.01
+Base	OGS	Real	2020 $/MMBTU	3.67	3.34	3.03	2.87	2.84	2.94	3.10	3.21	3.30	3.38	3.42	3.48	3.48	3.47	3.48	3.50	3.52	3.52	3.55	3.56	3.54	3.54	3.48	3.45	3.44	3.43	3.46	3.44	3.43	3.62	3.83	4.05	4.28	4.52	4.78	5.05	5.34	5.65	5.97
+Low	Coal	Real	2020 $/MMBTU	1.41	1.38	1.42	1.35	1.31	1.29	1.28	1.29	1.29	1.29	1.29	1.29	1.30	1.30	1.32	1.33	1.34	1.34	1.36	1.37	1.37	1.38	1.39	1.40	1.41	1.42	1.41	1.42	1.43	1.51	1.59	1.68	1.78	1.88	1.99	2.10	2.22	2.35	2.48
+Low	NG	Real	2020 $/MMBTU	3.30	3.00	2.73	2.58	2.56	2.64	2.79	2.89	2.97	3.05	3.07	3.13	3.13	3.13	3.14	3.15	3.17	3.17	3.20	3.20	3.18	3.19	3.13	3.11	3.10	3.09	3.11	3.09	3.09	3.26	3.45	3.64	3.85	4.07	4.30	4.55	4.81	5.08	5.37
+Low	Petroleum	Real	2020 $/MMBTU	10.46	9.03	9.79	9.98	10.22	10.48	10.71	10.81	11.02	11.24	11.41	11.53	11.64	11.75	11.91	12.06	12.21	12.25	12.51	12.63	12.68	12.89	13.14	13.21	13.39	13.45	13.43	13.45	13.40	14.16	14.97	15.82	16.73	17.68	18.69	19.75	20.88	22.07	23.33
+Low	Nuclear	Real	2020 $/MMBTU	0.62	0.62	0.62	0.62	0.62	0.62	0.62	0.63	0.63	0.63	0.63	0.63	0.63	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	0.41	1.03	1.09	1.15
+Low	Biomass	Real	2020 $/MMBTU	4.50	4.60	4.70	4.80	4.91	5.02	5.13	5.24	5.36	5.47	5.59	5.72	5.84	5.97	6.10	6.24	6.37	6.51	6.66	6.80	6.95	7.11	7.26	7.42	7.59	7.75	7.92	8.10	8.28	8.75	9.25	9.77	10.33	10.92	11.54	12.20	12.90	13.63	14.41
+Low	OGS	Real	2020 $/MMBTU	3.30	3.00	2.73	2.58	2.56	2.64	2.79	2.89	2.97	3.05	3.07	3.13	3.13	3.13	3.14	3.15	3.17	3.17	3.20	3.20	3.18	3.19	3.13	3.11	3.10	3.09	3.11	3.09	3.09	3.26	3.45	3.64	3.85	4.07	4.30	4.55	4.81	5.08	5.37

examples/1App_ALAEF_LCGTEP/README.md

@@ -0,0 +1,22 @@
+# 1App_ALEAF_LCGTEP
+
+## Purpose
+
+This example provides a demonstration for using WATTS to run and analyze simulations with A-LEAF (Argonne Low-carbon Electricity Analysis Framework) under various supply chain disruption scenarios. The example explores different fuel price settings to understand the impact on US nuclear capacity expansion result.
+
+
+## Code(s)
+
+- A-LEAF
+- Julia (A-LEAF dependency)
+
+## Keywords
+
+- Energy Market
+- Capacity Expansion
+- Economic Modeling 
+
+## File descriptions
+
+- [__watts_exec.py__](watts_exec.py): WATTS workflow for this example. This is the file to execute to run the problem described above.
+- [__A-LEAF_fuel_template__](Fuel.txt): Fuel price for this example

examples/1App_ALAEF_LCGTEP/watts_exec.py

@@ -0,0 +1,67 @@
+# SPDX-FileCopyrightText: 2022-2025 UChicago Argonne, LLC
+# SPDX-License-Identifier: MIT
+
+"""
+This example demonstrates how to use WATTS to run an A-LEAF calculation.
+"""
+
+import watts
+from pathlib import Path
+import pandas as pd
+
+params = watts.Parameters()
+
+
+fuel_price = {
+    2022: 0.62, 2023: 0.62, 2024: 0.62, 2025: 0.62, 2026: 0.62, 2027: 0.62,
+    2028: 0.63, 2029: 0.63, 2030: 0.63, 2031: 0.76, 2032: 0.76, 2033: 0.76,
+    2034: 0.76, 2035: 0.76, 2036: 0.77, 2037: 0.77, 2038: 0.77, 2039: 0.77,
+    2040: 0.77, 2041: 0.78, 2042: 0.78, 2043: 0.78, 2044: 0.78, 2045: 0.78,
+    2046: 0.79, 2047: 0.79, 2048: 0.79, 2049: 0.79, 2050: 0.79, 2051: 0.80,
+    2052: 0.80, 2053: 0.80, 2054: 0.80, 2055: 0.80, 2056: 0.81, 2057: 0.81,
+    2058: 0.81, 2059: 0.81, 2060: 0.81
+}
+
+
+# Set nuclear prices from reference and calculated growth
+starting_year = 2031
+starting_price = 0.76
+
+# Compute prices dynamically for years after the starting year
+growth_rates = {year: 1.0028 if year <= 2050 else 1.057 for year in range(starting_year + 1, 2061)}
+computed_prices = {starting_year: starting_price}
+for year in range(starting_year + 1, 2061):
+    prev_price = computed_prices[year - 1]
+    computed_prices[year] = round(prev_price * growth_rates[year], 3)
+
+fuel_price.update(computed_prices)
+
+# Initialize parameters and pass the fuel price dictionary
+params = watts.Parameters()
+params['fuel_price'] = fuel_price
+# Display parameter summary
+params.show_summary(show_metadata=True, sort_by='key')
+
+# Set default path for results
+results_path = Path.cwd() / 'results'
+results_path.mkdir(exist_ok=True, parents=True)
+watts.Database.set_default_path(results_path)
+
+# Create ALEAF plugin
+# aleaf_plugin = watts.PluginALEAF('Fuel.txt', extra_templates={'Simulation Configuration': 'Simulation Configuration.txt'})
+aleaf_plugin = watts.PluginALEAF('Fuel.txt')
+# Run ALEAF
+aleaf_result = aleaf_plugin(params)
+print('ALEAF simulation completed.')
+
+# Get the technology summary
+techsummary = aleaf_result.csv_data
+# keep only the capacity columns 
+techsummary = techsummary[['Year', 'UnitGroup', 'Unit_Type', 'Fuel', 'ICAP', 'ICap_New', 'ICap_Ret']]
+
+# group the technology summary by year and fuel
+grouped_df = techsummary.groupby(['Year','Fuel']).sum()
+# print out the grouped dataframe
+print(grouped_df)
+
+

src/watts/__init__.py

@@ -2,6 +2,7 @@
 # SPDX-License-Identifier: MIT
 
 from .plugin import *
+from .plugin_aleaf import *
 from .plugin_accert import *
 from .plugin_openmc import *
 from .plugin_moose import *

src/watts/plugin_aleaf.py

@@ -0,0 +1,158 @@
+from pathlib import Path
+import shutil
+import pandas as pd
+from typing import List, Optional, Dict
+import os
+
+from .plugin import Plugin
+from .results import Results, ExecInfo
+from .fileutils import PathLike
+from .parameters import Parameters
+from .template import TemplateRenderer
+import subprocess
+
+
+
+class ResultsALEAF(Results):
+    """ALEAF simulation results.
+
+    Parameters
+    ----------
+    params : Parameters
+        Parameters used for the simulation.
+    exec_info : ExecInfo
+        Execution information.
+    inputs : List[PathLike]
+        List of input files used for the simulation.
+    outputs : List[PathLike]
+        List of output files generated by the simulation.
+
+    Attributes
+    ----------
+    csv_data : pd.DataFrame
+        DataFrame containing the results from the ALEAF simulation.
+    """
+
+
+    def __init__(self, params: Parameters, exec_info: ExecInfo,
+                 inputs: List[PathLike], outputs: List[PathLike]):
+        super().__init__(params, exec_info, inputs, outputs)
+        self.csv_data = self._get_aleaf_csv_data()
+
+    def _get_aleaf_csv_data(self) -> pd.DataFrame:
+        """Read ALEAF output CSV file and return results as a DataFrame."""
+        output_file = next((p for p in self.outputs if p.name.endswith('_system_tech_summary_EXP.csv')), None)
+        if output_file and output_file.exists():
+            return pd.read_csv(output_file)
+        else:
+            return pd.DataFrame()  # Return an empty DataFrame if no CSV file is found
+
+
+class PluginALEAF(Plugin):
+    """Plugin for running ALEAF.
+
+    Parameters
+    ----------
+    template_file : PathLike
+        Path to the template file for ALEAF.
+    extra_templates : Optional[Dict[str, PathLike]]
+        Additional templates to be used in the simulation.
+    show_stdout : bool
+        Whether to show standard output during execution.
+    show_stderr : bool
+        Whether to show standard error during execution.
+    """
+
+    def __init__(self, template_file: PathLike, extra_templates: Optional[Dict[str, PathLike]] = None,
+                 show_stdout: bool = False, show_stderr: bool = False):
+        super().__init__(extra_inputs=[], show_stdout=show_stdout, show_stderr=show_stderr)
+        self.template_file = template_file
+        self.extra_templates = extra_templates or {}
+        self.plugin_name = 'ALEAF'
+        self.renderer = TemplateRenderer(template_file)
+        self.aleaf_dir = os.getenv('ALEAF_DIR')
+        if not self.aleaf_dir:
+            raise EnvironmentError("ALEAF_DIR environment variable is not set.")
+        self.output_folder = None
+
+    def prerun(self, params: Parameters) -> None:
+        """Generate ALEAF input files and check for pre-existing output.
+
+        Parameters
+        ----------
+        params : Parameters
+            Parameters to be used for the simulation.
+        """
+
+        # Copy the original ALEAF input file to the working directory
+        original_input_path = Path(self.aleaf_dir) / "setting/ALEAF_Master_LC_GTEP.xlsx"
+        modified_input_path = Path("ALEAF_Master_LC_GTEP.xlsx")
+        shutil.copy(original_input_path, modified_input_path)
+
+        # Load the Excel file and modify the 'Fuel' sheet
+        self.renderer(params = params, filename = self.template_file)
+        fuel_data = pd.read_csv("Fuel.txt", sep="\t")
+
+        with pd.ExcelWriter(modified_input_path, engine='openpyxl', mode='a', if_sheet_exists='replace') as writer:
+            fuel_sheet = pd.read_excel(writer, sheet_name='Fuel')
+            fuel_sheet.update(fuel_data)
+            fuel_sheet.to_excel(writer, sheet_name='Fuel', index=False)
+
+        # Render and apply additional templates if provided
+        for sheet_name, template_path in self.extra_templates.items():
+            template_renderer = TemplateRenderer(template_path)
+            sheet_data = template_renderer(params)
+            with pd.ExcelWriter(modified_input_path, engine='openpyxl', mode='a', if_sheet_exists='replace') as writer:
+                sheet_data.to_excel(writer, sheet_name=sheet_name, index=False)
+
+        # Copy the modified input file back to the original directory in ALEAF_DIR
+        shutil.copy(modified_input_path, original_input_path)
+
+        # Check the 'Simulation Configuration' sheet to find the correct case and CaseID remove the first row
+        config_sheet = pd.read_excel(modified_input_path, sheet_name='Simulation Configuration', header=1)
+        # Find the row with Run_Flag set to TRUE
+        case_row = config_sheet[config_sheet['Run_Flag'] == True].iloc[0]
+        case_id = case_row['Case_ID']
+        # Build the expected output directory and file path based on CaseID
+        output_folder = Path(self.aleaf_dir) / f"output/LC_GTEP/USA/case_id_{case_row.name+1}_{case_id}"
+        output_file = output_folder / f"{case_id}__system_tech_summary_EXP.csv"
+
+        # If the output file exists, back it up or delete it before running a new simulation
+        if output_file.exists():
+            backup_folder = output_folder / "backup"
+            backup_folder.mkdir(parents=True, exist_ok=True)
+            shutil.move(str(output_file), backup_folder / output_file.name)
+
+        # Save the output folder path for later use in postrun
+        self.output_folder = output_folder
+
+
+    def run(self):
+        """Run ALEAF.
+
+        Parameters
+        ----------
+        None
+        """
+        # Ensure the ALEAF directory exists
+        command = ['julia', 'execute_ALEAF.jl']
+        subprocess.run(command, cwd=self.aleaf_dir)
+
+    def postrun(self, params: Parameters, exec_info: ExecInfo) -> ResultsALEAF:
+        """Collect information from ALEAF simulation and create results object.
+        Parameters
+        ----------
+        params : Parameters
+            Parameters used for the simulation.
+            exec_info : ExecInfo
+            exec_info : ExecInfo
+                Execution information.
+
+        Returns
+        -------
+        ResultsALEAF
+            Results object containing the simulation results.
+        """
+        output_folder = Path(self.aleaf_dir) / f"output/LC_GTEP/USA/case_id_1_Test EXP"
+        outputs = [output_folder / "Test EXP__system_tech_summary_EXP.csv"]
+        return ResultsALEAF(params, exec_info, self.extra_inputs, outputs)