Refactor the calculation of PRICE_EMISSION and remove PRICE_EMISSION_NEW

message_ix/model/MESSAGE/model_core.gms

@@ -135,25 +135,18 @@ Variables
 * Variable                                                                                Explanatory text
 * ======================================================================================= =======================================================================================================
 * :math:`\text{DEMAND}_{n,c,l,y,h} \in \mathbb{R}`                                        Demand level (in equilibrium with MACRO integration)
-* :math:`\text{EMISSION_CONSTRAINT_RESCALE}_{n,\widehat{e},\widehat{t},y} \in \mathbb{R}` Annual average marginal of :ref:`emission_constraint`
 * :math:`\text{PRICE_COMMODITY}_{n,c,l,y,h} \in \mathbb{R}`                               Commodity price (undiscounted marginals of :ref:`commodity_balance_gt` and :ref:`commodity_balance_lt`)
 * :math:`\text{PRICE_EMISSION}_{n,\widehat{e},\widehat{t},y} \in \mathbb{R}`              Emission price (undiscounted marginals of :ref:`emission_constraint`)
 * :math:`\text{COST_NODAL_NET}_{n,y} \in \mathbb{R}`                                      System costs at the node level net of energy trade revenues/cost
 * :math:`\text{GDP}_{n,y} \in \mathbb{R}`                                                 Gross domestic product (GDP) in market exchange rates for MACRO reporting
 * ======================================================================================= =======================================================================================================
-*
-* .. warning::
-*    Please be aware that transitioning from one period length to another for consecutive periods may result in false values of :math:`\text{PRICE_EMISSION}`. 
-*    Please see `this issue <https://github.com/iiasa/message_ix/issues/723>`_ for further information. We are currently working on a fix.
 ***
 
 Variables
 * auxiliary variables for demand, prices, costs and GDP (for reporting when MESSAGE is run with MACRO)
     DEMAND(node,commodity,level,year_all,time) demand
-    EMISSION_CONSTRAINT_RESCALE(node,type_emission,type_tec,type_year) rescaled of marginals of EMISSION_CONSTRAINT constraint
     PRICE_COMMODITY(node,commodity,level,year_all,time)  commodity price (derived from marginals of COMMODITY_BALANCE constraint)
-    PRICE_EMISSION(node,type_emission,type_tec,year_all) emission price (derived from marginals of EMISSION_BOUND constraint)
-    PRICE_EMISSION_NEW(node,type_emission,type_tec,year_all) emission price (derived from marginals of EMISSION_EQUIVALENCE constraint)
+    PRICE_EMISSION(node,type_emission,type_tec,year_all) emission price (derived from marginals of EMISSION_EQUIVALENCE constraint)
     COST_NODAL_NET(node,year_all)              system costs at the node level over time including effects of energy trade
     GDP(node,year_all)                         gross domestic product (GDP) in market exchange rates for MACRO reporting
 ;

message_ix/model/MESSAGE/model_solve.gms

@@ -39,34 +39,23 @@ if (%foresight% = 0,
         ABORT "MESSAGEix did not solve to optimality!"
     ) ;
 
-* rescale the dual of the emission constraint to account that the constraint is defined on the average year, not total
-EMISSION_CONSTRAINT_RESCALE.l(node,type_emission,type_tec,type_year)$(
-        EMISSION_CONSTRAINT.m(node,type_emission,type_tec,type_year) ) =
-    EMISSION_CONSTRAINT.m(node,type_emission,type_tec,type_year)
-        / SUM(year$( cat_year(type_year,year) ), duration_period(year) )
-;
-
-
-* assign auxiliary variables DEMAND, PRICE_COMMODITY and PRICE_EMISSION for integration with MACRO and reporting
+* assign auxiliary variables DEMAND for integration with MACRO
     DEMAND.l(node,commodity,level,year,time) = demand_fixed(node,commodity,level,year,time) ;
+
+* assign auxiliary variables PRICE_COMMODITY and PRICE_EMISSION for reporting
     PRICE_COMMODITY.l(node,commodity,level,year,time) =
         ( COMMODITY_BALANCE_GT.m(node,commodity,level,year,time) + COMMODITY_BALANCE_LT.m(node,commodity,level,year,time) )
             / df_period(year) ;
-    PRICE_EMISSION.l(node,type_emission,type_tec,year)$( SUM(type_year$( cat_year(type_year,year) ), 1 ) ) =
-        SMAX(type_year$( cat_year(type_year,year) ),
-               - EMISSION_CONSTRAINT_RESCALE.l(node,type_emission,type_tec,type_year) )
-            / df_period(year) * duration_period(year);
-    PRICE_EMISSION.l(node,type_emission,type_tec,year)$(
-        PRICE_EMISSION.l(node,type_emission,type_tec,year) = - inf ) = 0 ;
-* Calculate PRICE_EMISSION based on the marginals of EMISSION_EQUIVALENCE
-    PRICE_EMISSION_NEW.l(node,type_emission,type_tec,year)$( SUM(emission$( cat_emission(type_emission,emission) ),
+
+* calculate PRICE_EMISSION based on the marginals of EMISSION_EQUIVALENCE
+    PRICE_EMISSION.l(node,type_emission,type_tec,year)$( SUM(emission$( cat_emission(type_emission,emission) ),
          EMISSION_EQUIVALENCE.m(node,emission,type_tec,year) ) ) =
         SMAX(emission$( cat_emission(type_emission,emission) ),
                EMISSION_EQUIVALENCE.m(node,emission,type_tec,year) / emission_scaling(type_emission,emission) )
             / df_period(year);
-   PRICE_EMISSION_NEW.l(node,type_emission,type_tec,year)$(
-        ( PRICE_EMISSION_NEW.l(node,type_emission,type_tec,year) = eps ) or
-        ( PRICE_EMISSION_NEW.l(node,type_emission,type_tec,year) = -inf ) ) = 0 ;
+   PRICE_EMISSION.l(node,type_emission,type_tec,year)$(
+        ( PRICE_EMISSION.l(node,type_emission,type_tec,year) = eps ) or
+        ( PRICE_EMISSION.l(node,type_emission,type_tec,year) = -inf ) ) = 0 ;
 
 %AUX_BOUNDS% AUX_ACT_BOUND_LO(node,tec,year_all,year_all2,mode,time)$( ACT.l(node,tec,year_all,year_all2,mode,time) < 0 AND
 %AUX_BOUNDS%    ACT.l(node,tec,year_all,year_all2,mode,time) = -%AUX_BOUND_VALUE% ) = yes ;

message_ix/models.py

@@ -407,8 +407,6 @@ def initialize(cls, scenario):
 par("commodity_stock", "n c l y")
 par("construction_time", "nl t yv")
 par("demand", "n c l y h")
-par("df_year", "y")
-par("df_period", "y")
 par("duration_period", "y")
 par("duration_time", "h")
 par("dynamic_land_lo", "n s y u")
@@ -457,7 +455,6 @@ def initialize(cls, scenario):
 par("level_cost_activity_soft_up", "nl t ya h")
 par("level_cost_new_capacity_soft_lo", "nl t yv")
 par("level_cost_new_capacity_soft_up", "nl t yv")
-par("levelized_cost", "n t y h")
 par("min_utilization_factor", "nl t yv ya")
 par("operation_factor", "nl t yv ya")
 par("output", "nl t yv ya m nd c l h hd")
@@ -560,12 +557,7 @@ def initialize(cls, scenario):
 var(
     "PRICE_EMISSION",
     "n type_emission type_tec y",
-    "Emission price (derived from marginals of EMISSION_BOUND constraint)",
-)
-var(
-    "PRICE_EMISSION_NEW",
-    "n type_emission type_tec y",
-    "TEMPORARY test for Emission price fix",
+    "Emission price (derived from marginals of EMISSION_EQUIVALENCE constraint)",
 )
 var(
     "REL",

message_ix/tests/test_feature_price_emission.py

@@ -8,8 +8,10 @@
 
 solve_args = {
     "equ_list": ["EMISSION_EQUIVALENCE"],
-    "par_list": ["df_period", "df_year", "levelized_cost"],
-    "var_list": ["PRICE_EMISSION_NEW"],
+    # "par_list": ["df_period", "df_year", "levelized_cost"],
+    # At the moment, it is not possible to retrieve auxilliary parameters that
+    # are created in GAMS back to ixmp. The default "par_list" is coded in Java
+    # backened, and specifying a list here does not add/modify the default list.
 }