Initial commit to the forked repository

README.md

@@ -1,3 +1,31 @@
+# TEMOA
+## Model features
+
+This is an extended version of the [TEMOA](https://temoacloud.com/) (Tools for Energy Modeling Optimization and Analysis) energy system modeling framework.
+
+The development team currently includes [Matteo Nicoli](http://www.mahtep.polito.it/people/phd_students/nicoli_matteo), [Gianvito Colucci](http://www.mahtep.polito.it/people/phd_students/colucci_gianvito), [Daniele Lerede](http://www.mahtep.polito.it/people/phd_students/lerede_daniele) and Prof. [Laura Savoldi](http://www.mahtep.polito.it/people/head/savoldi_laura) from [MAHTEP Group](http://www.mahtep.polito.it/) at [Department of Energy](https://www.denerg.polito.it/en/) of [Politecnico di Torino](https://www.polito.it/). For any communication related to our TEMOA version, please write to [[email protected]](mailto:[email protected]).
+
+Figure 1 schematically shows the main differences between the [original TEMOA](https://github.com/TemoaProject/temoa) version and the MAHTEP version.
+
+![](docs/TEMOA.svg)
+*Figure 1. Original (a) and extended (b) TEMOA structure.*
+
+The main changes between the two versions concern:
+* Integration of new parameters and constraints in the TEMOA algorithm, as explained in [1].
+* Development of a database pre-processing module, whom functions are explained in [1].
+* Development of a database post-processing module, to derive aggregated results by technologies, commodities, and groups of them.
+
+The public model instances based on this TEMOA version are:
+* [TEMOA-Italy](https://github.com/MAHTEP/TEMOA-Italy)
+* [TEMOA-Europe](https://github.com/MAHTEP/TEMOA-Europe)
+
+Below, the list of publications in which this version was used:
+1. M. Nicoli, F. Gracceva, D. Lerede, and L. Savoldi, “Can We Rely on Open-Source Energy System Optimization Models? The TEMOA-Italy Case Study,” Energies (Basel), vol. 15, no. 18, p. 6505, Sep. 2022, doi: 10.3390/en15186505.
+2. M. Nicoli, A TIMES-like open-source model for the Italian energy system. Turin, 2021. Accessed: Jul. 05, 2022. [Online]. Available: https://webthesis.biblio.polito.it/18850/
+3. G. Colucci, D. Lerede, M. Nicoli, and L. Savoldi, “Dynamic Accounting for End-Use CO2 Emissions From Low-Carbon Fuels in Energy System Optimization Models,” Energy Proceedings, 2022, doi: 10.46855/energy-proceedings-10294.
+4. A. Balbo, “Will hydrogen be a game-changer in the Italian decarbonization pathways? Exploiting an Energy System Optimization Model for scenario analysis,” Politecnico di Torino, 2022. Accessed: Feb. 11, 2023. [Online]. Available: https://webthesis.biblio.polito.it/24983/
+5. M. E. Alfano, “Modeling the Energy and the Water Systems in an open-access Energy System Optimization Model: the Pantelleria case study,” Politecnico di Torino, 2022. Accessed: Jan. 19, 2023. [Online]. Available: https://webthesis.biblio.polito.it/24982/
+
 # Overview
 
 The 'energysystem' branch is the current master branch of

temoa_model/config_sample

@@ -31,7 +31,7 @@
 
 # Report Duals (Optional) 
 # Store Duals results in the output .sqlite file
-#--saveDUALS
+--saveDUALS
 
 # Spreadsheet Output (Optional) 
 # Direct model output to a spreadsheet
@@ -44,8 +44,8 @@
 
 # Solver-related arguments (Optional)
 #--neos                            # Optional, specify if you want to use NEOS server to solve
-#--solver=cplex                    # Optional, indicate the solver
-#--keep_pyomo_lp_file             # Optional, generate Pyomo-compatible LP file
+--solver=gurobi                    # Optional, indicate the solver
+#--keep_pyomo_lp_file              # Optional, generate Pyomo-compatible LP file
 
 # Modeling-to-Generate Alternatives (Optional)
 # Run name will be automatically generated by appending '_mga_' and iteration number to scenario name

temoa_model/temoa_config.py

@@ -128,8 +128,14 @@ def query_table (t_properties, f):
 		['set',  'tech_annual',               '',                    '',             0],
 		['set',  'tech_variable',             '',                    '',             0],
 		['set',  'groups',                    '',                    '',             0],
-		['param','MinGenGroupTarget',         '',                    '',             2],
-		['param','MinGenGroupWeight',         '',                    '',             3],
+		['param','TechGroupWeight',           '',                    '',             3],
+		['param','MinActivityGroup',          '',                    '',             2],
+		['param','MaxActivityGroup',          '',                    '',             2],
+		['param','MinCapacityGroup',          '',                    '',             2],
+		['param','MaxCapacityGroup',          '',                    '',             2],
+		['param','MinInputGroup',             '',                    '',             4],
+		['param','MaxInputGroup',             '',                    '',             4],
+		['param','MaxOutputGroup',            '',                    '',             4],
 		['param','LinkedTechs',               '',                    '',             3],
 		['param','SegFrac',                   '',                    '',             2],
 		['param','DemandSpecificDistribution','',                    '',             4],
@@ -154,6 +160,7 @@ def query_table (t_properties, f):
 		['param','LifetimeTech',              '',                    '',             2],
 		['param','LifetimeProcess',           '',                    '',             3],
 		['param','LifetimeLoanTech',          '',                    '',             2],
+		['param','CapacityFactor',            '',                    '',             3],
 		['param','CapacityFactorTech',        '',                    '',             4],
 		['param','CapacityFactorProcess',     '',                    '',             5],
 		['param','Efficiency',                '',                    '',             5],

temoa_model/temoa_initialize.py

@@ -796,6 +796,17 @@ def CreateSparseDicts ( M ):
 # associated with specific parameters.
 # ---------------------------------------------------------------
 
+def CapacityFactorIndices(M):
+	indices = set(
+		(r, t, v)
+
+		for r in M.regions
+		for t in M.tech_all
+		for v in M.vintage_all
+	)
+
+	return indices
+
 def CapacityFactorProcessIndices ( M ):
 	indices = set(
 	  (r, s, d, t, v)

temoa_model/temoa_model.py

@@ -139,6 +139,9 @@ def temoa_create_model(name="Temoa"):
     )
     M.validate_UsedEfficiencyIndices = BuildAction(rule=CheckEfficiencyIndices)
 
+    M.CapacityFactor_rtv = Set(dimen=3, initialize= CapacityFactorIndices)
+    M.CapacityFactor = Param(M.CapacityFactor_rtv, default=1)
+
     M.CapacityFactor_rsdtv = Set(dimen=5, initialize=CapacityFactorProcessIndices)
     M.CapacityFactorProcess = Param(M.CapacityFactor_rsdtv, mutable=True)
 
@@ -210,17 +213,21 @@ def temoa_create_model(name="Temoa"):
     M.MinCapacity = Param(M.RegionalIndices, M.time_optimize, M.tech_all)
     M.MaxCapacity = Param(M.RegionalIndices, M.time_optimize, M.tech_all)
     M.MaxResource = Param(M.RegionalIndices, M.tech_all)
-    M.MinCapacitySum = Param(M.time_optimize)  # for techs in tech_capacity
-    M.MaxCapacitySum = Param(M.time_optimize)  # for techs in tech_capacity
     M.MaxActivity = Param(M.RegionalGlobalIndices, M.time_optimize, M.tech_all)
     M.MinActivity = Param(M.RegionalGlobalIndices, M.time_optimize, M.tech_all)
     M.GrowthRateMax = Param(M.RegionalIndices, M.tech_all)
     M.GrowthRateSeed = Param(M.RegionalIndices, M.tech_all)
     M.EmissionLimit = Param(M.RegionalGlobalIndices, M.time_optimize, M.commodity_emissions)
     M.EmissionActivity_reitvo = Set(dimen=6, initialize=EmissionActivityIndices)
-    M.EmissionActivity = Param(M.EmissionActivity_reitvo)
-    M.MinGenGroupWeight = Param(M.RegionalIndices, M.tech_groups, M.groups, default = 0)
-    M.MinGenGroupTarget = Param(M.time_optimize, M.groups)
+    M.EmissionActivity = Param(M.EmissionActivity_reitvo, default = 0)
+    M.TechGroupWeight = Param(M.RegionalIndices, M.tech_groups, M.groups, default = 0)
+    M.MinActivityGroup = Param(M.time_optimize, M.groups)
+    M.MaxActivityGroup = Param(M.time_optimize, M.groups)
+    M.MinCapacityGroup = Param(M.time_optimize, M.groups)
+    M.MaxCapacityGroup = Param(M.time_optimize, M.groups)
+    M.MinInputGroup = Param(M.regions, M.time_optimize, M.commodity_physical, M.groups)
+    M.MaxInputGroup = Param(M.regions, M.time_optimize, M.commodity_physical, M.groups)
+    M.MaxOutputGroup = Param(M.regions, M.time_optimize, M.commodity_physical, M.groups)
     M.LinkedTechs = Param(M.RegionalIndices, M.tech_all, M.commodity_emissions)
 
     # Define parameters associated with electric sector operation
@@ -448,12 +455,54 @@ def temoa_create_model(name="Temoa"):
     )
 
     M.MinActivityGroup_pg = Set(
-        dimen=2, initialize=lambda M: M.MinGenGroupTarget.sparse_iterkeys()
+        dimen=2, initialize=lambda M: M.MinActivityGroup.sparse_iterkeys()
     )
-    M.MinActivityGroup = Constraint(
+    M.MinActivityGroupConstraint = Constraint(
         M.MinActivityGroup_pg, rule=MinActivityGroup_Constraint
     )
 
+    M.MaxActivityGroup_pg = Set(
+        dimen=2, initialize=lambda M: M.MaxActivityGroup.sparse_iterkeys()
+    )
+    M.MaxActivityGroupConstraint = Constraint(
+        M.MaxActivityGroup_pg, rule=MaxActivityGroup_Constraint
+    )
+
+    M.MinCapacityGroupConstraint_pg = Set(
+        dimen=2, initialize=lambda M: M.MinCapacityGroup.sparse_iterkeys()
+    )
+    M.MinCapacityGroupConstraint = Constraint(
+        M.MinCapacityGroupConstraint_pg, rule=MinCapacityGroup_Constraint
+    )
+
+    M.MaxCapacityGroupConstraint_pg = Set(
+        dimen=2, initialize=lambda M: M.MaxCapacityGroup.sparse_iterkeys()
+    )
+    M.MaxCapacityGroupConstraint = Constraint(
+        M.MaxCapacityGroupConstraint_pg, rule=MaxCapacityGroup_Constraint
+    )
+
+    M.MinInputGroup_Constraint_rpig = Set(
+        dimen=4, initialize=lambda M: M.MinInputGroup.sparse_iterkeys()
+    )
+    M.MinInputGroupConstraint = Constraint(
+        M.MinInputGroup_Constraint_rpig, rule=MinInputGroup_Constraint
+    )
+
+    M.MaxInputGroup_Constraint_rpig = Set(
+        dimen=4, initialize=lambda M: M.MaxInputGroup.sparse_iterkeys()
+    )
+    M.MaxInputGroupConstraint = Constraint(
+        M.MaxInputGroup_Constraint_rpig, rule=MaxInputGroup_Constraint
+    )
+
+    M.MaxOutputGroup_Constraint_rpig = Set(
+        dimen=4, initialize=lambda M: M.MaxOutputGroup.sparse_iterkeys()
+    )
+    M.MaxOutputGroupConstraint = Constraint(
+        M.MaxOutputGroup_Constraint_rpig, rule=MaxOutputGroup_Constraint
+    )
+
     M.MaxCapacityConstraint_rpt = Set(
         dimen=3, initialize=lambda M: M.MaxCapacity.sparse_iterkeys()
     )
@@ -468,27 +517,13 @@ def temoa_create_model(name="Temoa"):
         M.MaxResourceConstraint_rt, rule=MaxResource_Constraint
     )
 
-    M.MaxCapacitySetConstraint_rp = Set(
-        dimen=2, initialize=lambda M: M.MaxCapacitySum.sparse_iterkeys()
-    )
-    M.MaxCapacitySetConstraint = Constraint(
-        M.MaxCapacitySetConstraint_rp, rule=MaxCapacitySet_Constraint
-    )
-
     M.MinCapacityConstraint_rpt = Set(
         dimen=3, initialize=lambda M: M.MinCapacity.sparse_iterkeys()
     )
     M.MinCapacityConstraint = Constraint(
         M.MinCapacityConstraint_rpt, rule=MinCapacity_Constraint
     )
 
-    M.MinCapacitySetConstraint_rp = Set(
-        dimen=2, initialize=lambda M: M.MinCapacitySum.sparse_iterkeys()
-    )
-    M.MinCapacitySetConstraint = Constraint(
-        M.MinCapacitySetConstraint_rp, rule=MinCapacitySet_Constraint
-    )
-
     M.TechInputSplitConstraint_rpsditv = Set(
         dimen=7, initialize=TechInputSplitConstraintIndices
     )