Correct optimize!, add stochastic test case

src/solution/methods/XavQiuWanThi2019/enforce.jl

@@ -34,19 +34,21 @@ function _enforce_transmission(;
     if violation.outage_line === nothing
         limit = violation.monitored_line.normal_flow_limit[violation.time]
         @info @sprintf(
-            "    %8.3f MW overflow in %-5s time %3d (pre-contingency)",
+            "    %8.3f MW overflow in %-5s time %3d (pre-contingency, scenario %s)",
             violation.amount,
             violation.monitored_line.name,
             violation.time,
+            sc.name,
         )
     else
         limit = violation.monitored_line.emergency_flow_limit[violation.time]
         @info @sprintf(
-            "    %8.3f MW overflow in %-5s time %3d (outage: line %s)",
+            "    %8.3f MW overflow in %-5s time %3d (outage: line %s, scenario %s)",
             violation.amount,
             violation.monitored_line.name,
             violation.time,
             violation.outage_line.name,
+            sc.name,
         )
     end
 

src/solution/methods/XavQiuWanThi2019/find.jl

@@ -15,12 +15,11 @@ function _find_violations(
     overflow = model[:overflow]
     length(sc.buses) > 1 || return []
     violations = []
-    @info "Verifying transmission limits..."
+
-    time_screening = @elapsed begin
     non_slack_buses = [b for b in sc.buses if b.offset > 0]
     net_injection_values = [
-            value(net_injection[sc.name, b.name, t]) for
+        value(net_injection[sc.name, b.name, t]) for b in non_slack_buses,
-            b in non_slack_buses, t in 1:instance.time
+        t in 1:instance.time
     ]
     overflow_values = [
         value(overflow[sc.name, lm.name, t]) for lm in sc.lines,
@@ -36,11 +35,6 @@ function _find_violations(
         max_per_line = max_per_line,
         max_per_period = max_per_period,
     )
-    end
-    @info @sprintf(
-        "Verified transmission limits in %.2f seconds",
-        time_screening
-    )
     return violations
 end
 

src/solution/methods/XavQiuWanThi2019/optimize.jl

@@ -10,16 +10,19 @@ function optimize!(model::JuMP.Model, method::XavQiuWanThi2019.Method)::Nothing
         JuMP.set_optimizer_attribute(model, "MIPGap", gap)
         @info @sprintf("MIP gap tolerance set to %f", gap)
     end
-    for sc in model[:instance].scenarios
+    initial_time = time()
     large_gap = false
-        has_transmission = (length(sc.isf) > 0)
+    has_transmission = false
+    for sc in model[:instance].scenarios
+        if length(sc.isf) > 0
+            has_transmission = true
+        end
         if has_transmission && method.two_phase_gap
             set_gap(1e-2)
             large_gap = true
         end
-        JuMP.optimize!(model)
+    end
     while true
-            initial_time = time()
         time_elapsed = time() - initial_time
         time_remaining = method.time_limit - time_elapsed
         if time_remaining < 0
@@ -33,14 +36,41 @@ function optimize!(model::JuMP.Model, method::XavQiuWanThi2019.Method)::Nothing
         JuMP.set_time_limit_sec(model, time_remaining)
         @info "Solving MILP..."
         JuMP.optimize!(model)
+
         has_transmission || break
-            violations = _find_violations(
+
+        @info "Verifying transmission limits..."
+        time_screening = @elapsed begin
+            violations = []
+            for sc in model[:instance].scenarios
+                push!(
+                    violations,
+                    _find_violations(
                         model,
                         sc,
                         max_per_line = method.max_violations_per_line,
                         max_per_period = method.max_violations_per_period,
+                    ),
+                )
+            end
+        end
+        @info @sprintf(
+            "Verified transmission limits in %.2f seconds",
+            time_screening
         )
-            if isempty(violations)
+
+        violations_found = false
+        for v in violations
+            if !isempty(v)
+                violations_found = true
+            end
+        end
+
+        if violations_found
+            for (i, v) in enumerate(violations)
+                _enforce_transmission(model, v, model[:instance].scenarios[i])
+            end
+        else
             @info "No violations found"
             if large_gap
                 large_gap = false
@@ -48,9 +78,6 @@ function optimize!(model::JuMP.Model, method::XavQiuWanThi2019.Method)::Nothing
             else
                 break
             end
-            else
-                _enforce_transmission(model, violations, sc)
-            end
         end
     end
     return

test/usage.jl

@@ -4,14 +4,19 @@
 
 using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON
 
-@testset "usage" begin
+function _set_flow_limits!(instance)
-    instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
     for sc in instance.scenarios
         sc.power_balance_penalty = [100_000 for _ in 1:instance.time]
         for line in sc.lines, t in 1:4
             line.normal_flow_limit[t] = 10.0
         end
     end
+end
+
+@testset "usage" begin
+    @testset "deterministic" begin
+        instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
+        _set_flow_limits!(instance)
         optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
         model = UnitCommitment.build_model(
             instance = instance,
@@ -38,3 +43,20 @@ using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON
         UnitCommitment.optimize!(model)
         @test UnitCommitment.validate(instance, solution)
     end
+
+    @testset "stochastic" begin
+        instance = UnitCommitment.read([
+            "$FIXTURES/case14.json.gz",
+            "$FIXTURES/case14.json.gz",
+        ])
+        _set_flow_limits!(instance)
+        @test length(instance.scenarios) == 2
+        optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
+        model = UnitCommitment.build_model(
+            instance = instance,
+            optimizer = optimizer,
+        )
+        UnitCommitment.optimize!(model)
+        solution = UnitCommitment.solution(model)
+    end
+end