Reformat source code

Project.toml

@@ -15,7 +15,6 @@ Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 PackageCompiler = "9b87118b-4619-50d2-8e1e-99f35a4d4d9d"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
-Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 
 [compat]
@@ -31,8 +30,8 @@ julia = "1"
 
 [extras]
 Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
-Gurobi = "2e9cd046-0924-5485-92f1-d5272153d98b"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+Gurobi = "2e9cd046-0924-5485-92f1-d5272153d98b"
 
 [targets]
 test = ["Cbc", "Test", "Gurobi"]

src/UnitCommitment.jl

@@ -48,7 +48,7 @@ include("solution/warmstart.jl")
 include("solution/write.jl")
 include("transform/initcond.jl")
 include("transform/slice.jl")
-include("transform/randomize/XavQiuAhm2021.jl")
+include("transform/randomize.jl")
 include("utils/log.jl")
 include("validation/repair.jl")
 include("validation/validate.jl")

src/model/formulations/GenMorRam2017/startstop.jl

@@ -0,0 +1,96 @@
+# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+"""
+    _add_startup_shutdown_limit_eqs!(model::JuMP.Model, g::Unit)::Nothing
+
+Startup and shutdown limits from Gentile et al. (2017).
+Eqns. (20), (23a), and (23b) in Knueven et al. (2020).
+
+Creates constraints `eq_startstop_limit`,  `eq_startup_limit`, and `eq_shutdown_limit`
+using variables `Gar1962.StatusVars`, `prod_above` from `Gar1962.ProdVars`, and `reserve`.
+
+Constraints
+---
+* `eq_startstop_limit`
+* `eq_startup_limit`
+* `eq_shutdown_limit`
+"""
+function _add_startup_shutdown_limit_eqs!(
+    model::JuMP.Model,
+    g::Unit,
+    formulation_prod_vars::Gar1962.ProdVars,
+    formulation_status_vars::Gar1962.StatusVars,
+)::Nothing
+    # TODO: Move upper case constants to model[:instance]
+    RESERVES_WHEN_START_UP = true
+    RESERVES_WHEN_RAMP_UP = true
+    RESERVES_WHEN_RAMP_DOWN = true
+    RESERVES_WHEN_SHUT_DOWN = true
+
+    eq_startstop_limit = _init(model, :eq_startstop_limit)
+    eq_shutdown_limit = _init(model, :eq_shutdown_limit)
+    eq_startup_limit = _init(model, :eq_startup_limit)
+
+    is_on = model[:is_on]
+    prod_above = model[:prod_above]
+    reserve = model[:reserve]
+    switch_off = model[:switch_off]
+    switch_on = model[:switch_on]
+
+    T = model[:instance].time
+    gi = g.name
+
+    if g.initial_power > g.shutdown_limit
+        eqs.shutdown_limit[gi, 0] =
+            @constraint(mip, vars.switch_off[gi, 1] <= 0)
+    end
+
+    for t in 1:T
+        ## 2020-10-09 amk: added eqn (20) and check of g.min_uptime
+        # Not present in (23) in Kneueven et al.
+        if g.min_uptime > 1
+            # Equation (20) in Knueven et al. (2020)
+            eqs.startstop_limit[gi, t] = @constraint(
+                model,
+                prod_above[gi, t] + reserve[gi, t] <=
+                (g.max_power[t] - g.min_power[t]) * is_on[gi, t] -
+                max(0, g.max_power[t] - g.startup_limit) * switch_on[gi, t] - (
+                    t < T ?
+                    max(0, g.max_power[t] - g.shutdown_limit) *
+                    switch_off[gi, t+1] : 0.0
+                )
+            )
+        else
+            ## Startup limits
+            # Equation (23a) in Knueven et al. (2020)
+            eqs.startup_limit[gi, t] = @constraint(
+                model,
+                prod_above[gi, t] + reserve[gi, t] <=
+                (g.max_power[t] - g.min_power[t]) * is_on[gi, t] -
+                max(0, g.max_power[t] - g.startup_limit) * switch_on[gi, t] - (
+                    t < T ?
+                    max(0, g.startup_limit - g.shutdown_limit) *
+                    switch_off[gi, t+1] : 0.0
+                )
+            )
+
+            ## Shutdown limits
+            if t < T
+                # Equation (23b) in Knueven et al. (2020)
+                eqs.shutdown_limit[gi, t] = @constraint(
+                    model,
+                    prod_above[gi, t] + reserve[gi, t] <=
+                    (g.max_power[t] - g.min_power[t]) * xis_on[gi, t] - (
+                        t < T ?
+                        max(0, g.max_power[t] - g.shutdown_limit) *
+                        switch_off[gi, t+1] : 0.0
+                    ) -
+                    max(0, g.shutdown_limit - g.startup_limit) *
+                    switch_on[gi, t]
+                )
+            end
+        end
+    end
+end

src/model/formulations/MorLatRam2013/startstop.jl

@@ -0,0 +1,89 @@
+# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+"""
+    _add_startup_shutdown_limit_eqs!(model::JuMP.Model, g::Unit)::Nothing
+
+Startup and shutdown limits from Morales-España et al. (2013a).
+Eqns. (20), (21a), and (21b) in Knueven et al. (2020).
+
+Uses variable `prod_above` from `Gar1962.ProdVars`, the variables in `Gar1962.StatusVars`, and `reserve`
+to generate constraints below.
+
+Constraints
+---
+* :eq_startstop_limit
+* :eq_startup_limit
+* :eq_shutdown_limit
+"""
+function _add_startup_shutdown_limit_eqs!(
+    model::JuMP.Model,
+    g::Unit,
+    formulation_prod_vars::Gar1962.ProdVars,
+    formulation_status_vars::Gar1962.StatusVars,
+)::Nothing
+    # TODO: Move upper case constants to model[:instance]
+    RESERVES_WHEN_START_UP = true
+    RESERVES_WHEN_RAMP_UP = true
+    RESERVES_WHEN_RAMP_DOWN = true
+    RESERVES_WHEN_SHUT_DOWN = true
+
+    eq_startstop_limit = _init(model, :eq_startstop_limit)
+    eq_shutdown_limit = _init(model, :eq_shutdown_limit)
+    eq_startup_limit = _init(model, :eq_startup_limit)
+
+    is_on = model[:is_on]
+    prod_above = model[:prod_above]
+    reserve = model[:reserve]
+    switch_off = model[:switch_off]
+    switch_on = model[:switch_on]
+
+    T = model[:instance].time
+    gi = g.name
+    for t in 1:T
+        ## 2020-10-09 amk: added eqn (20) and check of g.min_uptime
+        if g.min_uptime > 1 && t < T
+            # Equation (20) in Knueven et al. (2020)
+            # UT > 1 required, to guarantee that vars.switch_on[gi, t] and vars.switch_off[gi, t+1] are not both = 1 at the same time
+            eq_startstop_limit[gi, t] = @constraint(
+                model,
+                prod_above[gi, t] + reserve[gi, t] <=
+                (g.max_power[t] - g.min_power[t]) * is_on[gi, t] -
+                max(0, g.max_power[t] - g.startup_limit) * switch_on[gi, t] -
+                max(0, g.max_power[t] - g.shutdown_limit) * switch_off[gi, t+1]
+            )
+        else
+            ## Startup limits
+            # Equation (21a) in Knueven et al. (2020)
+            # Proposed by Morales-España et al. (2013a)
+            eqs_startup_limit[gi, t] = @constraint(
+                model,
+                prod_above[gi, t] + reserve[gi, t] <=
+                (g.max_power[t] - g.min_power[t]) * is_on[gi, t] -
+                max(0, g.max_power[t] - g.startup_limit) * switch_on[gi, t]
+            )
+
+            ## Shutdown limits
+            if t < T
+                # Equation (21b) in Knueven et al. (2020)
+                # TODO different from what was in previous model, due to reserve variable
+                # ax: ideally should have reserve_up and reserve_down variables
+                #     i.e., the generator should be able to increase/decrease production as specified
+                #     (this is a heuristic for a "robust" solution,
+                #     in case there is an outage or a surge, and flow has to be redirected)
+                # amk: if shutdown_limit is the max prod of generator in time period before shutting down,
+                #      then it makes sense to count reserves, because otherwise, if reserves ≠ 0,
+                #      then the generator will actually produce more than the limit
+                eqs.shutdown_limit[gi, t] = @constraint(
+                    model,
+                    prod_above[gi, t] +
+                    (RESERVES_WHEN_SHUT_DOWN ? reserve[gi, t] : 0.0) <=
+                    (g.max_power[t] - g.min_power[t]) * is_on[gi, t] -
+                    max(0, g.max_power[t] - g.shutdown_limit) *
+                    switch_off[gi, t+1]
+                )
+            end
+        end
+    end
+end

src/model/formulations/base/unit.jl

@@ -35,7 +35,12 @@ function _add_unit!(model::JuMP.Model, g::Unit, formulation::Formulation)
         formulation.status_vars,
     )
     _add_startup_cost_eqs!(model, g, formulation.startup_costs)
-    _add_startup_shutdown_limit_eqs!(model, g)
+    _add_startup_shutdown_limit_eqs!(
+        model,
+        g,
+        formulation.prod_vars,
+        formulation.status_vars,
+    )
     _add_status_eqs!(model, g, formulation.status_vars)
     return
 end
@@ -76,7 +81,22 @@ function _add_startup_shutdown_vars!(model::JuMP.Model, g::Unit)::Nothing
     return
 end
 
-function _add_startup_shutdown_limit_eqs!(model::JuMP.Model, g::Unit)::Nothing
+"""
+    _add_startup_shutdown_limit_eqs!(model::JuMP.Model, g::Unit)::Nothing
+
+Creates startup/shutdown limit constraints below based on variables `Gar1962.StatusVars`, `prod_above` from `Gar1962.ProdVars`, and `reserve`.
+
+Constraints
+---
+* :eq_startup_limit
+* :eq_shutdown_limit
+"""
+function _add_startup_shutdown_limit_eqs!(
+    model::JuMP.Model,
+    g::Unit,
+    formulation_prod_vars::Gar1962.ProdVars,
+    formulation_status_vars::Gar1962.StatusVars,
+)::Nothing
     eq_shutdown_limit = _init(model, :eq_shutdown_limit)
     eq_startup_limit = _init(model, :eq_startup_limit)
     is_on = model[:is_on]

src/transform/randomize.jl

@@ -0,0 +1,53 @@
+# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
+# Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using Distributions
+
+function randomize_unit_costs!(
+    instance::UnitCommitmentInstance;
+    distribution = Uniform(0.95, 1.05),
+)::Nothing
+    for unit in instance.units
+        α = rand(distribution)
+        unit.min_power_cost *= α
+        for k in unit.cost_segments
+            k.cost *= α
+        end
+        for s in unit.startup_categories
+            s.cost *= α
+        end
+    end
+    return
+end
+
+function randomize_load_distribution!(
+    instance::UnitCommitmentInstance;
+    distribution = Uniform(0.90, 1.10),
+)::Nothing
+    α = rand(distribution, length(instance.buses))
+    for t in 1:instance.time
+        total = sum(bus.load[t] for bus in instance.buses)
+        den = sum(
+            bus.load[t] / total * α[i] for
+            (i, bus) in enumerate(instance.buses)
+        )
+        for (i, bus) in enumerate(instance.buses)
+            bus.load[t] *= α[i] / den
+        end
+    end
+    return
+end
+
+function randomize_peak_load!(
+    instance::UnitCommitmentInstance;
+    distribution = Uniform(0.925, 1.075),
+)::Nothing
+    α = rand(distribution)
+    for bus in instance.buses
+        bus.load *= α
+    end
+    return
+end
+
+export randomize_unit_costs!, randomize_load_distribution!, randomize_peak_load!

src/transform/randomize/XavQiuAhm2021.jl

@@ -1,209 +0,0 @@
-# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
-# Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-"""
-Methods described in:
-
-    Xavier, Álinson S., Feng Qiu, and Shabbir Ahmed. "Learning to solve
-    large-scale security-constrained unit commitment problems." INFORMS
-    Journal on Computing 33.2 (2021): 739-756. DOI: 10.1287/ijoc.2020.0976
-"""
-module XavQiuAhm2021
-
-using Distributions
-import ..UnitCommitmentInstance
-
-"""
-    struct Randomization
-        cost = Uniform(0.95, 1.05)
-        load_profile_mu = [...]
-        load_profile_sigma = [...]
-        load_share = Uniform(0.90, 1.10)
-        peak_load = Uniform(0.6 * 0.925, 0.6 * 1.075)
-        randomize_costs = true
-        randomize_load_profile = true
-        randomize_load_share = true
-    end
-
-Randomization method that changes: (1) production and startup costs, (2)
-share of load coming from each bus, (3) peak system load, and (4) temporal
-load profile, as follows:
-
-1. **Production and startup costs:**
-    For each unit `u`, the vectors `u.min_power_cost` and `u.cost_segments`
-    are multiplied by a constant `α[u]` sampled from the provided `cost`
-    distribution. If `randomize_costs` is false, skips this step.
-
-2. **Load share:**
-   For each bus `b` and time `t`, the value `b.load[t]` is multiplied by
-   `(β[b] * b.load[t]) / sum(β[b2] * b2.load[t] for b2 in buses)`, where
-   `β[b]` is sampled from the provided `load_share` distribution. If
-   `randomize_load_share` is false, skips this step.
-
-3. **Peak system load and temporal load profile:**
-    Sets the peak load to `ρ * C`, where `ρ` is sampled from `peak_load` and `C`
-    is the maximum system capacity, at any time. Also scales the loads of all
-    buses, so that `system_load[t+1]` becomes equal to `system_load[t] * γ[t]`,
-    where `γ[t]` is sampled from `Normal(load_profile_mu[t], load_profile_sigma[t])`.
-    
-    The system load for the first time period is set so that the peak load
-    matches `ρ * C`. If `load_profile_sigma` and `load_profile_mu` have fewer
-    elements than `instance.time`, wraps around. If `randomize_load_profile`
-    is false, skips this step.
-
-The default parameters were obtained based on an analysis of publicly available
-bid and hourly data from PJM, corresponding to the month of January, 2017. For
-more details, see Section 4.2 of the paper.
-"""
-Base.@kwdef struct Randomization
-    cost = Uniform(0.95, 1.05)
-    load_profile_mu::Vector{Float64} = [
-        1.0,
-        0.978,
-        0.98,
-        1.004,
-        1.02,
-        1.078,
-        1.132,
-        1.018,
-        0.999,
-        1.006,
-        0.999,
-        0.987,
-        0.975,
-        0.984,
-        0.995,
-        1.005,
-        1.045,
-        1.106,
-        0.981,
-        0.981,
-        0.978,
-        0.948,
-        0.928,
-        0.953,
-    ]
-    load_profile_sigma::Vector{Float64} = [
-        0.0,
-        0.011,
-        0.015,
-        0.01,
-        0.012,
-        0.029,
-        0.055,
-        0.027,
-        0.026,
-        0.023,
-        0.013,
-        0.012,
-        0.014,
-        0.011,
-        0.008,
-        0.008,
-        0.02,
-        0.02,
-        0.016,
-        0.012,
-        0.014,
-        0.015,
-        0.017,
-        0.024,
-    ]
-    load_share = Uniform(0.90, 1.10)
-    peak_load = Uniform(0.6 * 0.925, 0.6 * 1.075)
-    randomize_load_profile::Bool = true
-    randomize_costs::Bool = true
-    randomize_load_share::Bool = true
-end
-
-function _randomize_costs(
-    instance::UnitCommitmentInstance,
-    distribution,
-)::Nothing
-    for unit in instance.units
-        α = rand(distribution)
-        unit.min_power_cost *= α
-        for k in unit.cost_segments
-            k.cost *= α
-        end
-        for s in unit.startup_categories
-            s.cost *= α
-        end
-    end
-    return
-end
-
-function _randomize_load_share(
-    instance::UnitCommitmentInstance,
-    distribution,
-)::Nothing
-    α = rand(distribution, length(instance.buses))
-    for t in 1:instance.time
-        total = sum(bus.load[t] for bus in instance.buses)
-        den = sum(
-            bus.load[t] / total * α[i] for
-            (i, bus) in enumerate(instance.buses)
-        )
-        for (i, bus) in enumerate(instance.buses)
-            bus.load[t] *= α[i] / den
-        end
-    end
-    return
-end
-
-function _randomize_load_profile(
-    instance::UnitCommitmentInstance,
-    params::Randomization,
-)::Nothing
-    # Generate new system load
-    system_load = [1.0]
-    for t in 2:instance.time
-        idx = (t - 1) % length(params.load_profile_mu) + 1
-        gamma = rand(
-            Normal(params.load_profile_mu[idx], params.load_profile_sigma[idx]),
-        )
-        push!(system_load, system_load[t-1] * gamma)
-    end
-    capacity = sum(maximum(u.max_power) for u in instance.units)
-    peak_load = rand(params.peak_load) * capacity
-    system_load = system_load ./ maximum(system_load) .* peak_load
-
-    # Scale bus loads to match the new system load
-    prev_system_load = sum(b.load for b in instance.buses)
-    for b in instance.buses
-        for t in 1:instance.time
-            b.load[t] *= system_load[t] / prev_system_load[t]
-        end
-    end
-
-    return
-end
-
-end
-
-"""
-    function randomize!(
-        instance::UnitCommitment.UnitCommitmentInstance,
-        method::XavQiuAhm2021.Randomization,
-    )::Nothing
-
-Randomize costs and loads based on the method described in XavQiuAhm2021.
-"""
-function randomize!(
-    instance::UnitCommitment.UnitCommitmentInstance,
-    method::XavQiuAhm2021.Randomization,
-)::Nothing
-    if method.randomize_costs
-        XavQiuAhm2021._randomize_costs(instance, method.cost)
-    end
-    if method.randomize_load_share
-        XavQiuAhm2021._randomize_load_share(instance, method.load_share)
-    end
-    if method.randomize_load_profile
-        XavQiuAhm2021._randomize_load_profile(instance, method)
-    end
-    return
-end
-
-export randomize!

test/runtests.jl

@@ -28,9 +28,7 @@ const ENABLE_LARGE_TESTS = ("UCJL_LARGE_TESTS" in keys(ENV))
     @testset "transform" begin
         include("transform/initcond_test.jl")
         include("transform/slice_test.jl")
-        @testset "randomize" begin
-            include("transform/randomize/XavQiuAhm2021_test.jl")
-        end
+        include("transform/randomize_test.jl")
     end
     @testset "validation" begin
         include("validation/repair_test.jl")

test/transform/randomize/XavQiuAhm2021_test.jl

@@ -1,63 +0,0 @@
-# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-import Random
-import UnitCommitment: XavQiuAhm2021
-
-using Distributions
-using UnitCommitment, Cbc, JuMP
-
-get_instance() = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
-system_load(instance) = sum(b.load for b in instance.buses)
-test_approx(x, y) = @test isapprox(x, y, atol = 1e-3)
-
-@testset "XavQiuAhm2021" begin
-    @testset "cost and load share" begin
-        instance = get_instance()
-
-        # Check original costs
-        unit = instance.units[10]
-        test_approx(unit.min_power_cost[1], 825.023)
-        test_approx(unit.cost_segments[1].cost[1], 36.659)
-        test_approx(unit.startup_categories[1].cost[1], 7570.42)
-
-        # Check original load share
-        bus = instance.buses[1]
-        prev_system_load = system_load(instance)
-        test_approx(bus.load[1] / prev_system_load[1], 0.012)
-
-        Random.seed!(42)
-        randomize!(
-            instance,
-            XavQiuAhm2021.Randomization(randomize_load_profile = false),
-        )
-
-        # Check randomized costs
-        test_approx(unit.min_power_cost[1], 831.977)
-        test_approx(unit.cost_segments[1].cost[1], 36.968)
-        test_approx(unit.startup_categories[1].cost[1], 7634.226)
-
-        # Check randomized load share
-        curr_system_load = system_load(instance)
-        test_approx(bus.load[1] / curr_system_load[1], 0.013)
-
-        # System load should not change
-        @test prev_system_load ≈ curr_system_load
-    end
-
-    @testset "load profile" begin
-        instance = get_instance()
-
-        # Check original load profile
-        @test round.(system_load(instance), digits = 1)[1:8] ≈
-              [3059.5, 2983.2, 2937.5, 2953.9, 3073.1, 3356.4, 4068.5, 4018.8]
-
-        Random.seed!(42)
-        randomize!(instance, XavQiuAhm2021.Randomization())
-
-        # Check randomized load profile
-        @test round.(system_load(instance), digits = 1)[1:8] ≈
-              [4854.7, 4849.2, 4732.7, 4848.2, 4948.4, 5231.1, 5874.8, 5934.8]
-    end
-end

test/transform/randomize_test.jl

@@ -0,0 +1,43 @@
+# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using UnitCommitment, Cbc, JuMP
+
+_get_instance() = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
+_total_load(instance) = sum(b.load[1] for b in instance.buses)
+
+@testset "randomize_unit_costs!" begin
+    instance = _get_instance()
+    unit = instance.units[10]
+    prev_min_power_cost = unit.min_power_cost
+    prev_prod_cost = unit.cost_segments[1].cost
+    prev_startup_cost = unit.startup_categories[1].cost
+    randomize_unit_costs!(instance)
+    @test prev_min_power_cost != unit.min_power_cost
+    @test prev_prod_cost != unit.cost_segments[1].cost
+    @test prev_startup_cost != unit.startup_categories[1].cost
+end
+
+@testset "randomize_load_distribution!" begin
+    instance = _get_instance()
+    bus = instance.buses[1]
+    prev_load = instance.buses[1].load[1]
+    prev_total_load = _total_load(instance)
+    randomize_load_distribution!(instance)
+    curr_total_load = _total_load(instance)
+    @test prev_load != instance.buses[1].load[1]
+    @test abs(prev_total_load - curr_total_load) < 1e-3
+end
+
+@testset "randomize_peak_load!" begin
+    instance = _get_instance()
+    bus = instance.buses[1]
+    prev_total_load = _total_load(instance)
+    prev_share = bus.load[1] / prev_total_load
+    randomize_peak_load!(instance)
+    curr_total_load = _total_load(instance)
+    curr_share = bus.load[1] / prev_total_load
+    @test curr_total_load != prev_total_load
+    @test abs(curr_share - prev_share) < 1e-3
+end