Clean up capacity index sets

temoa/components/capacity.py

@@ -18,6 +18,8 @@
 from deprecated import deprecated
 from pyomo.environ import value
 
+from .utils import get_capacity_factor
+
 if TYPE_CHECKING:
     from temoa.core.model import TemoaModel
     from temoa.types import (
@@ -142,23 +144,14 @@ def get_default_capacity_factor(
     return value(model.capacity_factor_tech[r, s, d, t])
 
 
-def get_capacity_factor(
-    model: TemoaModel, r: Region, s: Season, d: TimeOfDay, t: Technology, v: Vintage
-) -> float:
-    if model.is_capacity_factor_process[r, t, v]:
-        return value(model.capacity_factor_process[r, s, d, t, v])
-    else:
-        return value(model.capacity_factor_tech[r, s, d, t])
-
-
 # ============================================================================
 # PYOMO INDEX SETS
 # ============================================================================
 
 
-def capacity_variable_indices(
+def new_capacity_variable_indices(
     model: TemoaModel,
-) -> set[tuple[Region, Technology, Vintage]] | None:
+) -> set[tuple[Region, Technology, Vintage]]:
     return model.new_capacity_rtv
 
 
@@ -184,86 +177,72 @@ def annual_retirement_variable_indices(
     }
 
 
+def capacity_variable_indices(
+    model: TemoaModel,
+) -> set[tuple[Region, Period, Technology, Vintage]]:
+    return model.active_capacity_rptv
+
+
 def capacity_available_variable_indices(
     model: TemoaModel,
-) -> set[tuple[Region, Period, Technology]] | None:
+) -> set[tuple[Region, Period, Technology]]:
     return model.active_capacity_available_rpt
 
 
 def regional_exchange_capacity_constraint_indices(
     model: TemoaModel,
 ) -> set[tuple[Region, Region, Period, Technology, Vintage]]:
-    indices: set[tuple[Region, Region, Period, Technology, Vintage]] = set()
-    for r_e, p, i in model.export_regions:
-        for r_i, t, v, _o in model.export_regions[r_e, p, i]:
-            indices.add((r_e, r_i, p, t, v))
-
-    return indices
+    return {
+        (r_to, r_from, p, t, v)
+        for r_from, p, i in model.export_regions
+        for r_to, t, v, _o in model.export_regions[r_from, p, i]
+    }
 
 
 def capacity_annual_constraint_indices(
     model: TemoaModel,
 ) -> set[tuple[Region, Period, Technology, Vintage]]:
-    capacity_indices: set[tuple[Region, Period, Technology, Vintage]] = set()
-    if model.active_activity_rptv:
-        for r, p, t, v in model.active_activity_rptv:
-            if t in model.tech_annual and t not in model.tech_demand:
-                if t not in model.tech_uncap:
-                    capacity_indices.add((r, p, t, v))
-    else:
-        return set()
-
-    return capacity_indices
+    return {
+        (r, p, t, v)
+        for r, p, t, v in model.active_capacity_rptv
+        if t in model.tech_annual and t not in model.tech_demand
+    }
 
 
 def capacity_constraint_indices(
     model: TemoaModel,
 ) -> set[tuple[Region, Period, Season, TimeOfDay, Technology, Vintage]]:
-    capacity_indices: set[tuple[Region, Period, Season, TimeOfDay, Technology, Vintage]] = set()
-    if model.active_activity_rptv:
-        for r, p, t, v in model.active_activity_rptv:
-            if t not in model.tech_annual or t in model.tech_demand:
-                if t not in model.tech_uncap:
-                    if t not in model.tech_storage:
-                        for s in model.time_season:
-                            for d in model.time_of_day:
-                                capacity_indices.add((r, p, s, d, t, v))
-    else:
-        return set()
-
-    return capacity_indices
-
-
-@deprecated('switched over to validator... this set is typically VERY empty')
-def capacity_factor_process_indices(
-    model: TemoaModel,
-) -> set[tuple[Region, Season, TimeOfDay, Technology, Vintage]]:
-    indices: set[tuple[Region, Season, TimeOfDay, Technology, Vintage]] = set()
-    for r, _i, t, v, _o in model.efficiency.sparse_keys():
-        for s in model.time_season:
-            for d in model.time_of_day:
-                indices.add((r, s, d, t, v))
-    return indices
+    return {
+        (r, p, s, d, t, v)
+        for r, p, t, v in model.active_capacity_rptv
+        for s in model.time_season
+        for d in model.time_of_day
+        if t not in model.tech_annual or t in model.tech_demand
+        if t not in model.tech_storage
+    }
 
 
 def capacity_factor_tech_indices(
     model: TemoaModel,
 ) -> set[tuple[Region, Season, TimeOfDay, Technology]]:
-    all_cfs: set[tuple[Region, Season, TimeOfDay, Technology]] = set()
-    if model.active_capacity_available_rpt:  # in case every tech in the model is unlim_cap
-        for r, _p, t in model.active_capacity_available_rpt:
-            for s in model.time_season:
-                for d in model.time_of_day:
-                    all_cfs.add((r, s, d, t))
-    else:
-        return set()
-    return all_cfs
+    return {
+        (r, s, d, t)
+        for r, _p, t in model.active_capacity_available_rpt
+        for s in model.time_season
+        for d in model.time_of_day
+    }
 
 
-def capacity_available_variable_indices_vintage(
+@deprecated('switched over to validator... this set is typically VERY empty')
+def capacity_factor_process_indices(
     model: TemoaModel,
-) -> set[tuple[Region, Period, Technology, Vintage]] | None:
-    return model.active_capacity_available_rptv
+) -> set[tuple[Region, Season, TimeOfDay, Technology, Vintage]]:
+    return {
+        (r, s, d, t, v)
+        for r, _i, t, v, _o in model.efficiency.sparse_keys()
+        for s in model.time_season
+        for d in model.time_of_day
+    }
 
 
 # ============================================================================
@@ -660,18 +639,14 @@ def create_capacity_and_retirement_sets(model: TemoaModel) -> None:
     # Create active capacity index sets from the now-populated process_vintages
     model.new_capacity_rtv = {
         (r, t, v)
-        for r, p, t in model.process_vintages
-        for v in model.process_vintages[r, p, t]
+        for r, t, v in model.process_periods
         if t not in model.tech_uncap and v in model.time_optimize
     }
     model.active_capacity_available_rpt = {
-        (r, p, t)
-        for r, p, t in model.process_vintages
-        if model.process_vintages[r, p, t] and t not in model.tech_uncap
+        (r, p, t) for r, p, t in model.process_vintages if t not in model.tech_uncap
     }
-    model.active_capacity_available_rptv = {
+    model.active_capacity_rptv = {
         (r, p, t, v)
-        for r, p, t in model.process_vintages
+        for r, p, t in model.active_capacity_available_rpt
         for v in model.process_vintages[r, p, t]
-        if t not in model.tech_uncap
     }

temoa/components/commodities.py

@@ -136,7 +136,7 @@ def demand_activity_constraint_indices(
     demand commodity (and no annual techs co-serve it), the flow variables are fixed
     directly and DAC indices are omitted.
     """
-    indices = {
+    return {
         (r, p, s, d, t, v, dem)
         for r, p, dem in model.demand_constraint_rpc
         if (r, p, dem) not in model.singleton_demands
@@ -145,15 +145,14 @@ def demand_activity_constraint_indices(
         for s in model.time_season
         for d in model.time_of_day
     }
-    return indices
 
 
 def commodity_balance_constraint_indices(
     model: TemoaModel,
 ) -> set[tuple[Region, Period, Season, TimeOfDay, Commodity]]:
     # Generate indices only for those commodities that are produced by
     # technologies with varying output at the time slice level.
-    indices = {
+    return {
         (r, p, s, d, c)
         for r, p, c in model.commodity_balance_rpc
         # r in this line includes interregional transfer combinations (not needed).
@@ -163,24 +162,20 @@ def commodity_balance_constraint_indices(
         for d in model.time_of_day
     }
 
-    return indices
-
 
 def annual_commodity_balance_constraint_indices(
     model: TemoaModel,
 ) -> set[tuple[Region, Period, Commodity]]:
     # Generate indices only for those commodities that are produced by
     # technologies with constant annual output.
-    indices = {
+    return {
         (r, p, c)
         for r, p, c in model.commodity_balance_rpc
         # r in this line includes interregional transfer combinations (not needed).
         if r in model.regions  # this line ensures only the regions are included.
         and c in model.commodity_annual
     }
 
-    return indices
-
 
 # ============================================================================
 # PYOMO CONSTRAINT RULES

temoa/components/costs.py

@@ -97,18 +97,11 @@ def get_loan_life(model: TemoaModel, r: Region, t: Technology, v: Vintage) -> in
 
 
 def cost_fixed_indices(model: TemoaModel) -> set[tuple[Region, Period, Technology, Vintage]]:
-    # we pull the unlimited capacity techs from this index.  They cannot have fixed costs
-    if model.active_activity_rptv:
-        return {
-            (r, p, t, v) for r, p, t, v in model.active_activity_rptv if t not in model.tech_uncap
-        }
-    return set()
+    return model.active_capacity_rptv
 
 
 def cost_variable_indices(model: TemoaModel) -> set[tuple[Region, Period, Technology, Vintage]]:
-    if model.active_activity_rptv:
-        return model.active_activity_rptv
-    return set()
+    return model.active_activity_rptv
 
 
 def lifetime_loan_process_indices(model: TemoaModel) -> set[tuple[Region, Technology, Vintage]]:
@@ -120,9 +113,7 @@ def lifetime_loan_process_indices(model: TemoaModel) -> set[tuple[Region, Techno
     because in myopic mode, previously optimized vintages remain active in later
     windows and their data must be accepted by the param's index set.
     """
-    indices = {(r, t, v) for r, i, t, v, o in model.efficiency.sparse_keys()}
-
-    return indices
+    return {(r, t, v) for r, i, t, v, o in model.efficiency.sparse_keys()}
 
 
 # ============================================================================

temoa/components/emissions.py

@@ -38,20 +38,18 @@
 def emission_activity_indices(
     model: TemoaModel,
 ) -> set[tuple[Region, Commodity, Commodity, Technology, Vintage, Commodity]]:
-    indices = {
+    return {
         (r, e, i, t, v, o)
         for r, i, t, v, o in model.efficiency.sparse_keys()
         for e in model.commodity_emissions
         if r in model.regions  # omit any exchange/groups
     }
 
-    return indices
-
 
 def linked_tech_constraint_indices(
     model: TemoaModel,
 ) -> set[tuple[Region, Period, Season, TimeOfDay, Technology, Vintage, Commodity]]:
-    linkedtech_indices = {
+    return {
         (r, p, s, d, t, v, e)
         for r, t, e in model.linked_techs.sparse_keys()
         for p in model.time_optimize
@@ -62,8 +60,6 @@ def linked_tech_constraint_indices(
         for d in model.time_of_day
     }
 
-    return linkedtech_indices
-
 
 # ============================================================================
 # PYOMO CONSTRAINT RULES

temoa/components/flows.py

@@ -41,9 +41,7 @@
 
 def flow_variable_indices(
     model: TemoaModel,
-) -> (
-    set[tuple[Region, Period, Season, TimeOfDay, Commodity, Technology, Vintage, Commodity]] | None
-):
+) -> set[tuple[Region, Period, Season, TimeOfDay, Commodity, Technology, Vintage, Commodity]]:
     return model.active_flow_rpsditvo
 
 
@@ -55,9 +53,7 @@ def flow_variable_annual_indices(
 
 def flex_variable_indices(
     model: TemoaModel,
-) -> (
-    set[tuple[Region, Period, Season, TimeOfDay, Commodity, Technology, Vintage, Commodity]] | None
-):
+) -> set[tuple[Region, Period, Season, TimeOfDay, Commodity, Technology, Vintage, Commodity]]:
     return model.active_flex_rpsditvo
 
 
@@ -69,17 +65,13 @@ def flex_variable_annual_indices(
 
 def flow_in_storage_variable_indices(
     model: TemoaModel,
-) -> (
-    set[tuple[Region, Period, Season, TimeOfDay, Commodity, Technology, Vintage, Commodity]] | None
-):
+) -> set[tuple[Region, Period, Season, TimeOfDay, Commodity, Technology, Vintage, Commodity]]:
     return model.active_flow_in_storage_rpsditvo
 
 
 def curtailment_variable_indices(
     model: TemoaModel,
-) -> (
-    set[tuple[Region, Period, Season, TimeOfDay, Commodity, Technology, Vintage, Commodity]] | None
-):
+) -> set[tuple[Region, Period, Season, TimeOfDay, Commodity, Technology, Vintage, Commodity]]:
     return model.active_curtailment_rpsditvo