Location factor by Lingyan90 · Pull Request #1642 · IDAES/idaes-pse

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 77.57%. Comparing base (a60fbf8) to head (7813709).

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1642      +/-   ##
==========================================
+ Coverage   77.56%   77.57%   +0.01%     
==========================================
  Files         423      423              
  Lines       67529    67565      +36     
  Branches    11420    11429       +9     
==========================================
+ Hits        52379    52415      +36     
  Misses      12531    12531              
  Partials     2619     2619

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dallan-keylogic

I have some questions about the implementation here.

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

+        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

+    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


+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

        )


+def load_location_factor():


Suggested change

def load_location_factor():

def load_location_factors():

bpaul4 · 2025-07-25T17:50:42Z

        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

    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


+@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

+    ), 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

    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

 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

        # 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

…into location_factor

Lingyan90

@bpaul4, The code looks very good to me.

One issue that worth discussion is if the base cost in not in USD, it's in CAD for example, and user want use that base CAD cost to convert to Finland EUR, then the location factor application should be something like TPC_finland = TPC_Canada * LocationFactor_finland / LocationFactor_CAD.

For more general use, I would suggest modify the current location application equation to something like above, e.g. TPC_finland = TPC_baselocation * LocationFactor_finland / LocationFactor_baselocation.

And would also worth clarify that the current database are based on USD, if user use other currency, they should be consistent with their referenced currency.

Akintomiwaojo

Some comments and clarifications in-line.

Akintomiwaojo · 2026-07-29T17:41:34Z

+                # city lists within countries are not too long, list them here for the user
+                raise KeyError(
+                    f"City {city} not supported for country {country}; valid cities include "
+                    f"{self.location_factor_dictionary[country].keys()}"


dict_keys([...]) may appear in the message output. This might be an alternative:

f"{list(self.location_factor_dictionary[country].keys())}"

Akintomiwaojo · 2026-07-29T18:37:02Z

+                # too many countries to list, point users to the data file
+                raise KeyError(
+                    f"Country {country} not supported; please check the data file at "
+                    f"IDAES.idaes-pse.idaes.core.base.locations_factors.json for spelling and supported countries."


Suggested change

f"IDAES.idaes-pse.idaes.core.base.locations_factors.json for spelling and supported countries."

f"IDAES.idaes-pse.idaes.core.base.location_factors.json for spelling and supported countries."

Akintomiwaojo · 2026-07-29T18:53:35Z

+    - :math:`ISF` is the investment site factor (i.e., location factor).
+
+    Location factors for 139 countries are sourced from Compass International (2017):
+    https://www.compassinternational.net/wp-content/uploads/2017/01/Worldwide-Industrial.pdf


Could you please check this link again? It appears to be unavailable.

Could you please check this link again? It appears to be unavailable.

Is it in-house data that you requested? I checked www.compassinternational.net, and it looks like I need to request it.

@Lingyan90 could you please comment on this?

They probably have removed it or replaced it with different file. Could change the citation to something like this: Compass International, Inc. (2017). 2017 worldwide industrial [Sample edition]. https://www.compassinternational.net/wp-content/uploads/2017/01/Worldwide-Industrial.pdf (Accessed March 25, 2025).

Akintomiwaojo · 2026-07-29T19:19:12Z

+    are converted appropriately assuming the base factor of 1.0 corresponds to Washington D.C. and U.S. Northeast.
+
+    Note: For some countries, multiple city-specific location factors are provided.
+    The benchmark location is Washington, D.C., USA.


For clarification, does this imply that the benchmark for country factors, pulled from Compass International, is also Washington, D.C., USA? If not, we might be erroneously mixing factors with different benchmarks

The factors from Compass International have a benchmark of 1.0 for Washington, D.C., USA and everything else is in relation to that. The regional US factors from Seider were scaled so that Northeast (which is assumed to be the same region as DC) is 1.0.

bpaul4 · 2026-07-30T17:07:01Z

@bpaul4, The code looks very good to me.

One issue that worth discussion is if the base cost in not in USD, it's in CAD for example, and user want use that base CAD cost to convert to Finland EUR, then the location factor application should be something like TPC_finland = TPC_Canada * LocationFactor_finland / LocationFactor_CAD.

For more general use, I would suggest modify the current location application equation to something like above, e.g. TPC_finland = TPC_baselocation * LocationFactor_finland / LocationFactor_baselocation.

And would also worth clarify that the current database are based on USD, if user use other currency, they should be consistent with their referenced currency.

At the moment we only support USD for currencies. Users could define their own, however the current costing framework assumes that currencies are of the form "USD" + some descriptor about the index value or year/month so it would require an additional option. As it is we don't have any reference costs in other currencies so we can keep this in mind as a potential expansion for future work.

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

Merge branch 'main' into location_factor

72a971f

ksbeattie enabled auto-merge (squash) November 24, 2025 17:53

ksbeattie disabled auto-merge November 24, 2025 17:53

bpaul4 mentioned this pull request May 14, 2026

QGESS Costing Reorganization #1790

Merged

bpaul4 mentioned this pull request Jul 13, 2026

QGESS Costing To-Dos #1817

Open

8 tasks

bpaul4 added 4 commits July 21, 2026 16:54

Merge branch 'location_factor' of https://github.com/IDAES/idaes-pse …

6347886

…into location_factor

address reviewer comments, rename test_SSLW file to naming convention

cc824ab

add tests and related changes

e76e943

run black

6209357

bpaul4 requested review from AlexNoring, MAZamarripa, Robbybp, adowling2, aostace01, avdudchenko, dangunter, jsiirola, ksbeattie and sufikaur as code owners July 28, 2026 20:01

bpaul4 removed request for AlexNoring, MAZamarripa, Robbybp, adowling2, aostace01, avdudchenko, dangunter, jsiirola, ksbeattie, lbianchi-lbl and sufikaur July 28, 2026 20:02

bpaul4 and others added 3 commits July 28, 2026 13:03

Merge branch 'main' into location_factor

0e508f5

fix typo

e92a7dc

fix import order for pylint

b7ed334

bpaul4 requested a review from Akintomiwaojo July 28, 2026 20:56

Lingyan90 commented Jul 29, 2026

View reviewed changes

Akintomiwaojo reviewed Jul 29, 2026

View reviewed changes

bpaul4 added 2 commits July 30, 2026 10:14

address Tomi's reviewer suggestions

572e066

run black again

7813709

		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")

	f"IDAES.idaes-pse.idaes.core.base.locations_factors.json for spelling and supported countries."
	f"IDAES.idaes-pse.idaes.core.base.location_factors.json for spelling and supported countries."

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Fixes

Summary/Motivation:

Changes proposed in this PR:

Legal Acknowledgement

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