Add re targets (#137)

tests/test_solve/test_solve.py

@@ -177,3 +177,57 @@ def test_simple_trade():
 
     assert model.solution["NetTrade"].values[0][2][0] == 15
     assert np.round(model._m.objective.value) == 28200.0
+
+
+def test_simple_re_target():
+    """
+    This model has 2 generators, solar and coal, with identical parameters except for solar having
+    double the capex and is tagged as renewable using the param include_in_joint_renewable_target.
+
+    A 20% renewable target is set.
+    """
+    model = Model(
+        id="test-feasibility",
+        renewable_production_target=0.2,
+        time_definition=dict(id="years-only", years=range(2020, 2031)),
+        regions=[dict(id="single-region")],
+        commodities=[
+            dict(id="electricity", demand_annual=25, include_in_joint_renewable_target=True)
+        ],
+        impacts=[],
+        technologies=[
+            dict(
+                id="coal-gen",
+                operating_life=2,
+                capex=400,
+                operating_modes=[
+                    dict(
+                        id="generation",
+                        opex_variable=5,
+                        output_activity_ratio={"electricity": 1},
+                    )
+                ],
+            ),
+            dict(
+                id="solar-gen",
+                operating_life=2,
+                capex=800,
+                include_in_joint_renewable_target=True,
+                operating_modes=[
+                    dict(
+                        id="generation",
+                        opex_variable=5,
+                        output_activity_ratio={"electricity": 1},
+                    )
+                ],
+            ),
+        ],
+    )
+
+    model._build()
+
+    model._m.solve()
+
+    assert model._m.termination_condition == "optimal"
+    assert np.round(model._m.objective.value) == 54671.0
+    assert model._m.solution["NewCapacity"][0][1][0] == 5  # i.e. solar new capacity

tz/osemosys/model/constraints/__init__.py

@@ -43,7 +43,8 @@ def add_constraints(ds: xr.Dataset, m: Model, lex: Dict[str, LinearExpression])
     m = add_emissions_constraints(ds, m, lex)
     m = add_annual_activity_constraints(ds, m, lex)
     m = add_new_capacity_constraints(ds, m, lex)
-    m = add_re_targets_constraints(ds, m, lex)
+    if ds["REMinProductionTarget"].notnull().any():
+        m = add_re_targets_constraints(ds, m, lex)
     m = add_reserve_margin_constraints(ds, m, lex)
     m = add_storage_constraints(ds, m, lex)
     m = add_total_activity_constraints(ds, m, lex)

tz/osemosys/model/constraints/re_targets.py

@@ -54,6 +54,12 @@ def add_re_targets_constraints(ds: xr.Dataset, m: Model, lex: Dict[str, LinearEx
     ```
     """
 
-    # TODO
+    con = (
+        lex["ProductionAnnualRE"]
+        >= lex["ProductionAnnual"].assign_coords({"FUEL": ds["RETagFuel"] == 1})
+        * ds["REMinProductionTarget"]
+    )
+    mask = ds["RETagFuel"] == 1
+    m.add_constraints(con, name="RE1_RenewableProduction_MinConstraint", mask=mask)
 
     return m

tz/osemosys/model/linear_expressions/__init__.py

@@ -9,6 +9,7 @@
 from tz.osemosys.model.linear_expressions.emissions import add_lex_emissions
 from tz.osemosys.model.linear_expressions.financials import add_lex_financials
 from tz.osemosys.model.linear_expressions.production import add_lex_quantities
+from tz.osemosys.model.linear_expressions.re_production import add_lex_re_production
 from tz.osemosys.model.linear_expressions.reserve_margin import add_lex_reserve_margin
 from tz.osemosys.model.linear_expressions.storage import add_lex_storage
 from tz.osemosys.model.linear_expressions.trade import add_lex_trade
@@ -29,5 +30,7 @@ def add_linear_expressions(ds: xr.Dataset, m: Model) -> Dict[str, LinearExpressi
     add_lex_financials(ds, m, lex)
     add_lex_quantities(ds, m, lex)
     add_lex_reserve_margin(ds, m, lex)
+    if ds["REMinProductionTarget"].notnull().any():
+        add_lex_re_production(ds, m, lex)
 
     return lex

tz/osemosys/model/linear_expressions/re_production.py

@@ -0,0 +1,29 @@
+from typing import Dict
+
+import xarray as xr
+from linopy import LinearExpression, Model
+
+
+def add_lex_re_production(ds: xr.Dataset, m: Model, lex: Dict[str, LinearExpression]):
+
+    RateOfProductionByTechnologyByModeRE = m["RateOfActivity"] * ds["OutputActivityRatio"].where(
+        ds["OutputActivityRatio"].notnull() & (ds["RETagTechnology"] == 1)
+    )
+    RateOfProductionByTechnologyRE = RateOfProductionByTechnologyByModeRE.where(
+        ds["OutputActivityRatio"].sum("MODE_OF_OPERATION") != 0
+    ).sum(dims="MODE_OF_OPERATION")
+    RateOfProductionRE = RateOfProductionByTechnologyRE.sum(dims="TECHNOLOGY")
+    ProductionByTechnologyRE = RateOfProductionByTechnologyRE * ds["YearSplit"]
+    ProductionRE = RateOfProductionRE * ds["YearSplit"]
+    ProductionAnnualRE = ProductionRE.sum(dims="TIMESLICE")
+
+    lex.update(
+        {
+            "RateOfProductionByTechnologyByModeRE": RateOfProductionByTechnologyByModeRE,
+            "RateOfProductionByTechnologyRE": RateOfProductionByTechnologyRE,
+            "RateOfProductionRE": RateOfProductionRE,
+            "ProductionRE": ProductionRE,
+            "ProductionByTechnologyRE": ProductionByTechnologyRE,
+            "ProductionAnnualRE": ProductionAnnualRE,
+        }
+    )