Break down model.jl

src/solution/fix.jl

@@ -16,14 +16,14 @@ function fix!(model::JuMP.Model, solution::AbstractDict)::Nothing
     for g in instance.units
         for t in 1:T
             is_on_value = round(solution["Is on"][g.name][t])
-            production_value =
+            prod_value =
                 round(solution["Production (MW)"][g.name][t], digits = 5)
             reserve_value =
                 round(solution["Reserve (MW)"][g.name][t], digits = 5)
             JuMP.fix(is_on[g.name, t], is_on_value, force = true)
             JuMP.fix(
                 prod_above[g.name, t],
-                production_value - is_on_value * g.min_power[t],
+                prod_value - is_on_value * g.min_power[t],
                 force = true,
             )
             JuMP.fix(reserve[g.name, t], reserve_value, force = true)

src/solution/methods/XaQiWaTh19/structs.jl

@@ -9,6 +9,8 @@ import DataStructures: PriorityQueue
         time_limit::Float64
         gap_limit::Float64
         two_phase_gap::Bool
+        max_violations_per_line::Int
+        max_violations_per_period::Int
     end
 
 Lazy constraint solution method described in:
@@ -17,8 +19,8 @@ Lazy constraint solution method described in:
     constraint filtering in large-scale security-constrained unit commitment. 
     IEEE Transactions on Power Systems, 34(3), 2457-2460.
 
-Fields
-=========
+## Fields
+
 - `time_limit`:
     the time limit over the entire optimization procedure.
 - `gap_limit`: 
@@ -26,6 +28,13 @@ Fields
 - `two_phase_gap`: 
     if true, solve the problem with large gap tolerance first, then reduce
     the gap tolerance when no further violated constraints are found.
+- `max_violations_per_line`:
+    maximum number of violated transmission constraints to add to the
+    formulation per transmission line.
+- `max_violations_per_period`:
+    maximum number of violated transmission constraints to add to the
+    formulation per time period.
+
 """
 struct _XaQiWaTh19
     time_limit::Float64
@@ -35,11 +44,11 @@ struct _XaQiWaTh19
     max_violations_per_period::Int
 
     function _XaQiWaTh19(;
-        time_limit::Float64,
-        gap_limit::Float64,
-        two_phase_gap::Bool,
-        max_violations_per_line::Int,
-        max_violations_per_period::Int,
+        time_limit::Float64 = 86400.0,
+        gap_limit::Float64 = 1e-3,
+        two_phase_gap::Bool = true,
+        max_violations_per_line::Int = 1,
+        max_violations_per_period::Int = 5,
     )
         return new(
             time_limit,

src/solution/optimize.jl

@@ -10,14 +10,5 @@ advanced methods to accelerate the solution process and to enforce transmission
 and N-1 security constraints.
 """
 function optimize!(model::JuMP.Model)::Nothing
-    return UnitCommitment.optimize!(
-        model,
-        _XaQiWaTh19(
-            time_limit = 3600.0,
-            gap_limit = 1e-4,
-            two_phase_gap = true,
-            max_violations_per_line = 1,
-            max_violations_per_period = 5,
-        ),
-    )
+    return UnitCommitment.optimize!(model, _XaQiWaTh19())
 end

src/solution/warmstart.jl

@@ -5,8 +5,6 @@
 function set_warm_start!(model::JuMP.Model, solution::AbstractDict)::Nothing
     instance, T = model[:instance], model[:instance].time
     is_on = model[:is_on]
-    prod_above = model[:prod_above]
-    reserve = model[:reserve]
     for g in instance.units
         for t in 1:T
             JuMP.set_start_value(is_on[g.name, t], solution["Is on"][g.name][t])