Location factor #1642

Lingyan90 · 2025-07-24T20:14:06Z

Fixes

The location factor is an important metric for analyzing different market location. Here, move the location factor from PrOMMiS to IDAES for broader application. (This originally started in PrOMMiS in PR prommis/prommis#143)

Summary/Motivation:

Move the location factor to IDAES so that other repository such as PrOMMiS, WaterTAP, etc. could also access these values.

Changes proposed in this PR:

Add location factor data in costing_base.py
Added location factor data bank into location_factors.jason
Added testing code in test_costing_base.py
Added location factor in SSLW.py

Legal Acknowledgement

By contributing to this software project, I agree to the following terms and conditions for my contribution:

I agree my contributions are submitted under the license terms described in the LICENSE.txt file at the top level of this directory.
I represent I am authorized to make the contributions and grant the license. If my employer has rights to intellectual property that includes these contributions, I represent that I have received permission to make contributions and grant the required license on behalf of that employer.

codecov · 2025-07-25T11:33:11Z

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 77.01%. Comparing base (c84a7fe) to head (3957921).

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1642      +/-   ##
==========================================
- Coverage   77.01%   77.01%   -0.01%     
==========================================
  Files         395      395              
  Lines       63555    63567      +12     
  Branches    10365    10365              
==========================================
+ Hits        48944    48953       +9     
- Misses      12171    12175       +4     
+ Partials     2440     2439       -1

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dallan-keylogic

I have some questions about the implementation here.

dallan-keylogic · 2025-07-25T14:11:22Z

idaes/core/base/tests/test_costing_base.py

+        with pytest.raises(StopIteration):
+            _ = next(
+                entry
+                for entry in location_data
+                if (entry["country"], entry["city"]) == test_location
+            )


The test name indicates that this should raise a KeyError but the test itself indicates it raises a StopIteration error. It seems like you should catch the StopIteration error and raise a KeyError yourself.

Also, why are we iterating through a list entry-by-entry to check whether the country-city pair exists? Doesn't it make more sense to implement it an object (like a dict) that uses a hash lookup?

dallan-keylogic · 2025-07-25T14:12:56Z

idaes/core/base/tests/test_costing_base.py

+    else:
+        pytest.skip("Test assumptions not satisfied for invalid city test.")


Why are we skipping the test here? The only reason we should be skipping tests is if the test requires some dependency (like a solver) that not every environment has.

bpaul4

Thanks @Lingyan90 for opening this, I have a few comments.

bpaul4 · 2025-07-25T17:43:18Z

idaes/core/base/costing_base.py


+def load_location_factor():
+    """
+    Estimate the cost of constructing the same plant in different global locations using location factors.


Suggested change

Estimate the cost of constructing the same plant in different global locations using location factors.

Estimate the cost of constructing the same plant in different regions using location factors.

bpaul4 · 2025-07-25T17:49:47Z

idaes/core/base/costing_base.py

        )


+def load_location_factor():


Suggested change

def load_location_factor():

def load_location_factors():

bpaul4 · 2025-07-25T17:50:42Z

idaes/core/base/costing_base.py

        self.base_currency = None
        self.base_period = pyo.units.year

+        # Set the location factor


Suggested change

# Set the location factor

# Set the location factor, default U.S. Washington DC, location_factor = 1.00

bpaul4 · 2025-07-25T17:52:22Z

idaes/core/base/tests/test_costing_base.py

    register_idaes_currency_units,
 )

+from idaes.core.base.costing_base import load_location_factor


Suggested change

from idaes.core.base.costing_base import load_location_factor

from idaes.core.base.costing_base import load_location_factors

bpaul4 · 2025-07-25T17:52:44Z

idaes/core/base/tests/test_costing_base.py


+@pytest.mark.unit
+def test_all_valid_locations_have_factors():
+    location_data = load_location_factor()


And everywhere else in the file where this appears.

Suggested change

location_data = load_location_factor()

location_data = load_location_factors()

bpaul4 · 2025-07-25T17:58:09Z

idaes/core/base/tests/test_costing_base.py

+    ), f"Test assumption failed: {invalid_country} unexpectedly exists in data"
+
+
+@pytest.mark.unit


How would this work in practice? If a user tried to call a country which an invalid region/city, would it return a default?

bpaul4 · 2025-07-25T18:21:36Z

idaes/models/costing/SSLW.py

    register_idaes_currency_units,
 )

+from idaes.core.base.costing_base import load_location_factor


Suggested change

from idaes.core.base.costing_base import load_location_factor

from idaes.core.base.costing_base import load_location_factors

bpaul4 · 2025-07-25T18:27:27Z

idaes/models/costing/SSLW.py

 class SSLWCostingData(FlowsheetCostingBlockData):
    # Register currency and conversion rates based on CE Index
    register_idaes_currency_units()
+    load_location_factor()


This should be assigned to an object, so it can be referenced later.

I think "location" should also be a configuration argument like "CE_index_year", so the UnitModelCostingBlock will save the attribute self.location = ("United States", "Washington DC") and then apply it to the capital cost equation.

Finally, please add tests to the SSLW test file applying location factors and check built objects, object values, and cost results.

bpaul4 · 2025-07-25T18:29:48Z

idaes/models/costing/SSLW.py

        # Set a base period for all operating costs
        self.base_period = pyo.units.year
+        # Chose location and set location factor
+        self.location_factor = ("United States", "Washington DC")


Suggested change

self.location_factor = ("United States", "Washington DC")

self.location = ("United States", "Washington DC")

And then internal to the costing method, we can define self.location_factor = location_data[self.location].

ksbeattie · 2025-10-09T18:35:19Z

@Lingyan90, any news on this?

Lingyan90 · 2025-10-09T18:39:39Z

@Lingyan90, any news on this?

This PR should be addressed once the PrOMMiS costing dictionary has been moved to IDAES.

ksbeattie · 2025-10-09T21:15:58Z

@Lingyan90, any news on this?

This PR should be addressed once the PrOMMiS costing dictionary has been moved to IDAES.

Is there a PR, issue and/or person for that move (in either PrOMMiS or IDAES)?

bpaul4 · 2025-10-09T22:48:08Z

@Lingyan90, any news on this?

This PR should be addressed once the PrOMMiS costing dictionary has been moved to IDAES.

Is there a PR, issue and/or person for that move (in either PrOMMiS or IDAES)?

@ksbeattie I and others on the costing team will coordinate this move soon. Here is the issue: prommis/prommis#150

Lingyan90 added 5 commits June 10, 2025 16:26

added location factor data bank and imported into costing_base.py

bb5558c

Merge branch 'main' into location_factor

8ecd844

added location factor test

818a04a

sslw add location factor

9d733c1

Update SSLW.py

7698091

Lingyan90 requested review from agarciadiego, bpaul4, dallan-keylogic and lbianchi-lbl as code owners July 24, 2025 20:14

Update costing_base.py

3957921

dallan-keylogic reviewed Jul 25, 2025

View reviewed changes

bpaul4 reviewed Jul 25, 2025

View reviewed changes

ksbeattie added the PrOMMiS Issues related to PrOMMiS activities label Aug 4, 2025

ksbeattie mentioned this pull request Aug 4, 2025

Location factor prommis/prommis#143

Closed

4 tasks

ksbeattie added the Priority:Normal Normal Priority Issue or PR label Aug 7, 2025

ksbeattie assigned Lingyan90 Aug 7, 2025

		else:
		pytest.skip("Test assumptions not satisfied for invalid city test.")

	Estimate the cost of constructing the same plant in different global locations using location factors.
	Estimate the cost of constructing the same plant in different regions using location factors.

	# Set the location factor
	# Set the location factor, default U.S. Washington DC, location_factor = 1.00

	from idaes.core.base.costing_base import load_location_factor
	from idaes.core.base.costing_base import load_location_factors

	location_data = load_location_factor()
	location_data = load_location_factors()

		), f"Test assumption failed: {invalid_country} unexpectedly exists in data"


		@pytest.mark.unit

	self.location_factor = ("United States", "Washington DC")
	self.location = ("United States", "Washington DC")

Location factor #1642

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Lingyan90 commented Jul 24, 2025 • edited by ksbeattie Loading Uh oh! There was an error while loading. Please reload this page.

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Fixes

Summary/Motivation:

Changes proposed in this PR:

Legal Acknowledgement

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ksbeattie commented Oct 9, 2025

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Lingyan90 commented Oct 9, 2025

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bpaul4 commented Oct 9, 2025

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Lingyan90 commented Jul 24, 2025 •

edited by ksbeattie

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