Update the storage constraint to use the rolling initial storage level

Update src/constraints/storage.jl to use the initial_storage_level stored
in the rolling horizon.

Add test for the rolling horizon objective values to control future changes.

Part of #1365

Author: abelsiqueira

src/constraints/storage.jl

@@ -5,10 +5,27 @@ export add_storage_constraints!
 
 Adds the storage asset constraints to the model.
 """
-function add_storage_constraints!(connection, model, variables, expressions, constraints, profiles)
+function add_storage_constraints!(
+    connection,
+    model,
+    variables,
+    expressions,
+    constraints,
+    profiles;
+    rolling_horizon = false,
+)
     var_storage_level_rep_period = variables[:storage_level_rep_period]
     var_storage_level_over_clustered_year = variables[:storage_level_over_clustered_year]
 
+    rolling_horizon_lookup = if rolling_horizon
+        Dict{Int,Int}(
+            row.var_storage_id::Int => row.id::Int for
+            row in DuckDB.query(connection, "FROM param_initial_storage_level")
+        )
+    else
+        Dict{Int,Int}()
+    end
+
     ## REP-PERIOD CONSTRAINTS (within a representative period)
     # - Balance constraint (using the lowest temporal resolution)
     let table_name = :balance_storage_rep_period, cons = constraints[table_name]
@@ -27,7 +44,12 @@ function add_storage_constraints!(connection, model, variables, expressions, con
                         sum,
                         0.0,
                     )
-                    initial_storage_level = row.initial_storage_level::Union{Float64,Missing}
+                    initial_storage_level = if rolling_horizon && row.time_block_start == 1
+                        rolling_horizon_id = rolling_horizon_lookup[row.id]
+                        variables[:param_initial_storage_level].container[rolling_horizon_id]
+                    else
+                        row.initial_storage_level::Union{Float64,Missing}
+                    end
                     storage_charging_efficiency = row.storage_charging_efficiency::Float64
                     storage_discharging_efficiency = row.storage_discharging_efficiency::Float64
 

src/create-model.jl

@@ -186,7 +186,8 @@ function create_model(
         variables,
         expressions,
         constraints,
-        profiles,
+        profiles;
+        rolling_horizon,
     )
 
     @timeit to "add_hub_constraints!" add_hub_constraints!(model, constraints)

test/io-outputs/energy-problem-rolling-horizon.txt

@@ -0,0 +1,8 @@
+EnergyProblem:
+  - Solved using rolling horizon. Internal model info:
+    - Number of variables: 337
+    - Number of constraints for variable bounds: 337
+    - Number of structural constraints: 384
+  - Model solved!
+    - Termination status: OPTIMAL
+    - Objective value: NaN

test/test-case-studies.jl

@@ -154,6 +154,21 @@ end
     TulipaEnergyModel.populate_with_defaults!(connection)
     energy_problem = TulipaEnergyModel.run_scenario(connection; show_log = false)
     @test energy_problem.objective_value ≈ 410873.9 rtol = 1e-5
+
+    # We only check the rolling horizon objectives since we cannot easily obtain
+    # the objective of the full problem
+    expected_objective_values =
+        [103424.0, 120393.6, 109303.0, 108443.0, 122910.4, 137268.2, 118006.6]
+
+    energy_problem = TulipaEnergyModel.run_rolling_horizon(connection, 24, 48; show_log = false)
+    for row in DuckDB.query(connection, "FROM rolling_horizon_window")
+        @test row.objective_value ≈ expected_objective_values[row.id] rtol = 1e-5
+    end
+
+    io = IOBuffer()
+    print(io, energy_problem)
+    @test split(String(take!(io))) ==
+          split(read("io-outputs/energy-problem-rolling-horizon.txt", String))
 end
 
 @testitem "Infeasible Case Study" setup = [CommonSetup] tags = [:case_study, :integration, :slow] begin