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

@@ -15,31 +15,25 @@ 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
-            b in non_slack_buses, t in 1:instance.time
-        ]
-        overflow_values = [
-            value(overflow[sc.name, lm.name, t]) for lm in sc.lines,
-            t in 1:instance.time
-        ]
-        violations = UnitCommitment._find_violations(
-            instance = instance,
-            sc = sc,
-            net_injections = net_injection_values,
-            overflow = overflow_values,
-            isf = sc.isf,
-            lodf = sc.lodf,
-            max_per_line = max_per_line,
-            max_per_period = max_per_period,
-        )
-    end
-    @info @sprintf(
-        "Verified transmission limits in %.2f seconds",
-        time_screening
+
+    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 b in non_slack_buses,
+        t in 1:instance.time
+    ]
+    overflow_values = [
+        value(overflow[sc.name, lm.name, t]) for lm in sc.lines,
+        t in 1:instance.time
+    ]
+    violations = UnitCommitment._find_violations(
+        instance = instance,
+        sc = sc,
+        net_injections = net_injection_values,
+        overflow = overflow_values,
+        isf = sc.isf,
+        lodf = sc.lodf,
+        max_per_line = max_per_line,
+        max_per_period = max_per_period,
     )
     return violations
 end

src/solution/methods/XavQiuWanThi2019/optimize.jl

@@ -10,46 +10,73 @@ 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
+    initial_time = time()
+    large_gap = false
+    has_transmission = false
     for sc in model[:instance].scenarios
-        large_gap = false
-        has_transmission = (length(sc.isf) > 0)
+        if length(sc.isf) > 0
+            has_transmission = true
+        end
         if has_transmission && method.two_phase_gap
             set_gap(1e-2)
             large_gap = true
         end
+    end
+    while true
+        time_elapsed = time() - initial_time
+        time_remaining = method.time_limit - time_elapsed
+        if time_remaining < 0
+            @info "Time limit exceeded"
+            break
+        end
+        @info @sprintf(
+            "Setting MILP time limit to %.2f seconds",
+            time_remaining
+        )
+        JuMP.set_time_limit_sec(model, time_remaining)
+        @info "Solving MILP..."
         JuMP.optimize!(model)
-        while true
-            initial_time = time()
-            time_elapsed = time() - initial_time
-            time_remaining = method.time_limit - time_elapsed
-            if time_remaining < 0
-                @info "Time limit exceeded"
-                break
+
+        has_transmission || break
+
+        @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
-            @info @sprintf(
-                "Setting MILP time limit to %.2f seconds",
-                time_remaining
-            )
-            JuMP.set_time_limit_sec(model, time_remaining)
-            @info "Solving MILP..."
-            JuMP.optimize!(model)
-            has_transmission || break
-            violations = _find_violations(
-                model,
-                sc,
-                max_per_line = method.max_violations_per_line,
-                max_per_period = method.max_violations_per_period,
-            )
-            if isempty(violations)
-                @info "No violations found"
-                if large_gap
-                    large_gap = false
-                    set_gap(method.gap_limit)
-                else
-                    break
-                end
+        end
+        @info @sprintf(
+            "Verified transmission limits in %.2f seconds",
+            time_screening
+        )
+
+        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
+                set_gap(method.gap_limit)
             else
-                _enforce_transmission(model, violations, sc)
+                break
             end
         end
     end

test/usage.jl

@@ -4,37 +4,59 @@
 
 using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON
 
-@testset "usage" begin
-    instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
+function _set_flow_limits!(instance)
     for sc in instance.scenarios
         sc.power_balance_penalty = [100_000 for _ in 1:instance.time]
         for line in sc.lines, t in 1:4
             line.normal_flow_limit[t] = 10.0
         end
     end
-    optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
-    model = UnitCommitment.build_model(
-        instance = instance,
-        optimizer = optimizer,
-        variable_names = true,
-    )
-    @test name(model[:is_on]["g1", 1]) == "is_on[g1,1]"
-
-    # Optimize and retrieve solution
-    UnitCommitment.optimize!(model)
-    solution = UnitCommitment.solution(model)
-
-    # Write solution to a file
-    filename = tempname()
-    UnitCommitment.write(filename, solution)
-    loaded = JSON.parsefile(filename)
-    @test length(loaded["Is on"]) == 6
-
-    # Verify solution
-    @test UnitCommitment.validate(instance, solution)
-
-    # Reoptimize with fixed solution
-    UnitCommitment.fix!(model, solution)
-    UnitCommitment.optimize!(model)
-    @test UnitCommitment.validate(instance, solution)
+end
+
+@testset "usage" begin
+    @testset "deterministic" begin
+        instance = UnitCommitment.read("$FIXTURES/case14.json.gz")
+        _set_flow_limits!(instance)
+        optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
+        model = UnitCommitment.build_model(
+            instance = instance,
+            optimizer = optimizer,
+            variable_names = true,
+        )
+        @test name(model[:is_on]["g1", 1]) == "is_on[g1,1]"
+
+        # Optimize and retrieve solution
+        UnitCommitment.optimize!(model)
+        solution = UnitCommitment.solution(model)
+
+        # Write solution to a file
+        filename = tempname()
+        UnitCommitment.write(filename, solution)
+        loaded = JSON.parsefile(filename)
+        @test length(loaded["Is on"]) == 6
+
+        # Verify solution
+        @test UnitCommitment.validate(instance, solution)
+
+        # Reoptimize with fixed solution
+        UnitCommitment.fix!(model, solution)
+        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