Improve sysimage.jl

.gitignore

@@ -18,3 +18,4 @@ TODO.md
 docs/_build
 .vscode
 Manifest.toml
+*/Manifest.toml

Makefile

@@ -5,23 +5,20 @@
 JULIA := julia --color=yes --project=@.
 VERSION := 0.2
 
-build/sysimage.so: src/utils/sysimage.jl Project.toml Manifest.toml
+build/sysimage.so: src/utils/sysimage.jl Project.toml
-	mkdir -p build
+	julia --project=. -e "using Pkg; Pkg.instantiate()"
-	mkdir -p benchmark/results/test
+	julia --project=test -e "using Pkg; Pkg.instantiate()"
-	cd benchmark; $(JULIA) --trace-compile=../build/precompile.jl benchmark.jl test/case14
+	$(JULIA) src/utils/sysimage.jl test/runtests.jl
-	$(JULIA) src/utils/sysimage.jl
 
 clean:
-	rm -rf build/*
+	rm -rfv build
 
 docs:
 	cd docs; make clean; make dirhtml
 	rsync -avP --delete-after docs/_build/dirhtml/ ../docs/$(VERSION)/
 	
 test: build/sysimage.so
-	@echo Running tests...
+	$(JULIA) --sysimage build/sysimage.so test/runtests.jl
-	$(JULIA) --sysimage build/sysimage.so -e 'using Pkg; Pkg.test("UnitCommitment")' | tee build/test.log
-
 
 format:
 	julia -e 'using JuliaFormatter; format(["src", "test", "benchmark"], verbose=true);'

Project.toml

@@ -15,10 +15,10 @@ 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]
-Cbc = "0.7"
 DataStructures = "0.18"
 Distributions = "0.25"
 GZip = "0.5"
@@ -27,11 +27,3 @@ JuMP = "0.21"
 MathOptInterface = "0.9"
 PackageCompiler = "1"
 julia = "1"
-
-[extras]
-Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
-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.jl")
+include("transform/randomize/XavQiuAhm2021.jl")
 include("utils/log.jl")
 include("validation/repair.jl")
 include("validation/validate.jl")

src/instance/read.jl

@@ -266,15 +266,20 @@ function _from_json(json; repair = true)
     end
 
     instance = UnitCommitmentInstance(
-        T,
+        buses_by_name = Dict(b.name => b for b in buses),
-        power_balance_penalty,
+        buses = buses,
-        shortfall_penalty,
+        contingencies_by_name = Dict(c.name => c for c in contingencies),
-        units,
+        contingencies = contingencies,
-        buses,
+        lines_by_name = Dict(l.name => l for l in lines),
-        lines,
+        lines = lines,
-        reserves,
+        power_balance_penalty = power_balance_penalty,
-        contingencies,
+        price_sensitive_loads_by_name = Dict(ps.name => ps for ps in loads),
-        loads,
+        price_sensitive_loads = loads,
+        reserves = reserves,
+        shortfall_penalty = shortfall_penalty,
+        time = T,
+        units_by_name = Dict(g.name => g for g in units),
+        units = units,
     )
     if repair
         UnitCommitment.repair!(instance)

src/instance/structs.jl

@@ -69,17 +69,21 @@ mutable struct PriceSensitiveLoad
     revenue::Vector{Float64}
 end
 
-mutable struct UnitCommitmentInstance
+Base.@kwdef mutable struct UnitCommitmentInstance
-    time::Int
+    buses_by_name::Dict{AbstractString,Bus}
-    power_balance_penalty::Vector{Float64}
-    "Penalty for failing to meet reserve requirement."
-    shortfall_penalty::Vector{Float64}
-    units::Vector{Unit}
     buses::Vector{Bus}
-    lines::Vector{TransmissionLine}
+    contingencies_by_name::Dict{AbstractString,Contingency}
-    reserves::Reserves
     contingencies::Vector{Contingency}
+    lines_by_name::Dict{AbstractString,TransmissionLine}
+    lines::Vector{TransmissionLine}
+    power_balance_penalty::Vector{Float64}
+    price_sensitive_loads_by_name::Dict{AbstractString,PriceSensitiveLoad}
     price_sensitive_loads::Vector{PriceSensitiveLoad}
+    reserves::Reserves
+    shortfall_penalty::Vector{Float64}
+    time::Int
+    units_by_name::Dict{AbstractString,Unit}
+    units::Vector{Unit}
 end
 
 function Base.show(io::IO, instance::UnitCommitmentInstance)

src/model/build.jl

@@ -21,8 +21,6 @@ Arguments
 - `optimizer`:
     the optimizer factory that should be attached to this model (e.g. Cbc.Optimizer).
     If not provided, no optimizer will be attached.
-- `formulation`:
-    the details of which constraints, variables, etc. to use
 - `variable_names`: 
     If true, set variable and constraint names. Important if the model is going
     to be exported to an MPS file. For large models, this can take significant

src/model/formulations/ArrCon2000/ramp.jl

@@ -2,15 +2,6 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-"""
-    _add_ramp_eqs!(model, unit, formulation_prod_vars, formulation_ramping, formulation_status_vars)::Nothing
-
-Ensure constraints on ramping are met.
-Based on Arroyo and Conejo (2000).
-Eqns. (24), (25) in Knueven et al. (2020).
-
-Adds constraints identified by `ArrCon200.Ramping` to `model` using variables `Gar1962.ProdVars` and `is_on` from `Gar1962.StatusVars`.
-"""
 function _add_ramp_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -31,6 +22,7 @@ function _add_ramp_eqs!(
     reserve = model[:reserve]
     eq_ramp_down = _init(model, :eq_ramp_down)
     eq_ramp_up = _init(model, :eq_ramp_up)
+    is_initially_on = (g.initial_status > 0)
 
     # Gar1962.ProdVars
     prod_above = model[:prod_above]
@@ -40,8 +32,6 @@ function _add_ramp_eqs!(
     switch_off = model[:switch_off]
     switch_on = model[:switch_on]
 
-    is_initially_on = _is_initially_on(g) > 0
-
     for t in 1:model[:instance].time
         # Ramp up limit
         if t == 1
@@ -66,7 +56,7 @@ function _add_ramp_eqs!(
             min_prod_last_period =
                 g.min_power[t-1] * is_on[gn, t-1] + prod_above[gn, t-1]
 
-            # Equation (24) in Knueven et al. (2020)
+            # Equation (24) in Kneuven et al. (2020)
             eq_ramp_up[gn, t] = @constraint(
                 model,
                 max_prod_this_period - min_prod_last_period <=
@@ -97,7 +87,7 @@ function _add_ramp_eqs!(
             min_prod_this_period =
                 g.min_power[t] * is_on[gn, t] + prod_above[gn, t]
 
-            # Equation (25) in Knueven et al. (2020)
+            # Equation (25) in Kneuven et al. (2020)
             eq_ramp_down[gn, t] = @constraint(
                 model,
                 max_prod_last_period - min_prod_this_period <=

src/model/formulations/ArrCon2000/structs.jl

@@ -13,12 +13,6 @@ module ArrCon2000
 
 import ..RampingFormulation
 
-"""
-Constraints
----
-* `eq_ramp_up`: Equation (24) in Knueven et al. (2020)
-* `eq_ramp_down`: Equation (25) in Knueven et al. (2020)
-"""
 struct Ramping <: RampingFormulation end
 
 end

src/model/formulations/CarArr2006/pwlcosts.jl

@@ -2,12 +2,6 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-"""
-    _add_production_piecewise_linear_eqs!
-
-Ensure respect of production limits along each segment.
-Creates constraints `CarArr2006.PwlCosts` using variables `Gar1962.StatusVars`
-"""
 function _add_production_piecewise_linear_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -27,7 +21,7 @@ function _add_production_piecewise_linear_eqs!(
     for t in 1:model[:instance].time
         gn = g.name
         for k in 1:K
-            # Equation (45) in Knueven et al. (2020)
+            # Equation (45) in Kneuven et al. (2020)
             # NB: when reading instance, UnitCommitment.jl already calculates
             #     difference between max power for segments k and k-1 so the
             #     value of cost_segments[k].mw[t] is the max production *for
@@ -42,14 +36,14 @@ function _add_production_piecewise_linear_eqs!(
             set_upper_bound(segprod[gn, t, k], g.cost_segments[k].mw[t])
 
             # Definition of production
-            # Equation (43) in Knueven et al. (2020)
+            # Equation (43) in Kneuven et al. (2020)
             eq_prod_above_def[gn, t] = @constraint(
                 model,
                 prod_above[gn, t] == sum(segprod[gn, t, k] for k in 1:K)
             )
 
             # Objective function
-            # Equation (44) in Knueven et al. (2020)
+            # Equation (44) in Kneuven et al. (2020)
             add_to_expression!(
                 model[:obj],
                 segprod[gn, t, k],

src/model/formulations/CarArr2006/structs.jl

@@ -14,16 +14,6 @@ module CarArr2006
 
 import ..PiecewiseLinearCostsFormulation
 
-"""
-Based on Garver (1962) and Carrión and Arryo (2006),
-which replaces (42) in Knueven et al. (2020) with a weaker version missing the on/off variable.
-Equations (45), (43), (44) in Knueven et al. (2020).
-
-Constraints
----
-* `eq_prod_above_def`: Equation (43) in Knueven et al. (2020)
-* `eq_segprod_limit`: Equation (45) in Knueven et al. (2020)
-"""
 struct PwlCosts <: PiecewiseLinearCostsFormulation end
 
 end

src/model/formulations/DamKucRajAta2016/ramp.jl

@@ -2,26 +2,6 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-"""
-    _add_ramp_eqs!
-
-Ensure constraints on ramping are met.
-Based on Damcı-Kurt et al. (2016).
-Eqns. (35), (36) in Knueven et al. (2020).
-
-Variables
----
-* :prod_above
-* :reserve
-* :is_on
-* :switch_on
-* :switch_off],
-
-Constraints
----
-* :eq_str_ramp_up
-* :eq_str_ramp_down
-"""
 function _add_ramp_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -34,14 +14,12 @@ function _add_ramp_eqs!(
     RESERVES_WHEN_RAMP_UP = true
     RESERVES_WHEN_RAMP_DOWN = true
     RESERVES_WHEN_SHUT_DOWN = true
-    is_initially_on = _is_initially_on(g)
+    known_initial_conditions = true
-
+    is_initially_on = (g.initial_status > 0)
-    # The following are the same for generator g across all time periods
+    SU = g.startup_limit
-    SU = g.startup_limit   # startup rate
+    SD = g.shutdown_limit
-    SD = g.shutdown_limit  # shutdown rate
+    RU = g.ramp_up_limit
-    RU = g.ramp_up_limit   # ramp up rate
+    RD = g.ramp_down_limit
-    RD = g.ramp_down_limit # ramp down rate
-
     gn = g.name
     eq_str_ramp_down = _init(model, :eq_str_ramp_down)
     eq_str_ramp_up = _init(model, :eq_str_ramp_up)
@@ -78,7 +56,7 @@ function _add_ramp_eqs!(
         if t > 1 && time_invariant
             min_prod_last_period = prod_above[gn, t-1]
 
-            # Equation (35) in Knueven et al. (2020)
+            # Equation (35) in Kneuven et al. (2020)
             # Sparser version of (24)
             eq_str_ramp_up[gn, t] = @constraint(
                 model,
@@ -98,7 +76,7 @@ function _add_ramp_eqs!(
             # (instead of using the amount above minimum, as min prod for t < 1 is unknown)
             max_prod_this_period += g.min_power[t] * is_on[gn, t]
 
-            # Modified version of equation (35) in Knueven et al. (2020)
+            # Modified version of equation (35) in Kneuven et al. (2020)
             # Equivalent to (24)
             eq_str_ramp_up[gn, t] = @constraint(
                 model,
@@ -116,12 +94,12 @@ function _add_ramp_eqs!(
         on_last_period = 0.0
         if t > 1
             on_last_period = is_on[gn, t-1]
-        elseif is_initially_on
+        elseif (known_initial_conditions && g.initial_status > 0)
             on_last_period = 1.0
         end
 
         if t > 1 && time_invariant
-            # Equation (36) in Knueven et al. (2020)
+            # Equation (36) in Kneuven et al. (2020)
             eq_str_ramp_down[gn, t] = @constraint(
                 model,
                 max_prod_last_period - min_prod_this_period <=
@@ -132,7 +110,7 @@ function _add_ramp_eqs!(
             # Add back in min power
             min_prod_this_period += g.min_power[t] * is_on[gn, t]
 
-            # Modified version of equation (36) in Knueven et al. (2020)
+            # Modified version of equation (36) in Kneuven et al. (2020)
             # Equivalent to (25)
             eq_str_ramp_down[gn, t] = @constraint(
                 model,

src/model/formulations/Gar1962/prod.jl

@@ -2,11 +2,6 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-"""
-    _add_production_vars!(model, unit, formulation_prod_vars)
-
-Adds symbols identified by `Gar1962.ProdVars` to `model`.
-"""
 function _add_production_vars!(
     model::JuMP.Model,
     g::Unit,
@@ -23,23 +18,6 @@ function _add_production_vars!(
     return
 end
 
-"""
-    _add_production_limit_eqs!(model, unit, formulation_prod_vars)
-
-Ensure production limit constraints are met.
-Based on Garver (1962) and Morales-España et al. (2013).
-Eqns. (18), part of (69) in Knueven et al. (2020).
-
-===
-Variables
-* :is_on
-* :prod_above
-* :reserve
-
-===
-Constraints
-* :eq_prod_limit
-"""
 function _add_production_limit_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -52,13 +30,13 @@ function _add_production_limit_eqs!(
     gn = g.name
     for t in 1:model[:instance].time
         # Objective function terms for production costs
-        # Part of (69) of Knueven et al. (2020) as C^R_g * u_g(t) term
+        # Part of (69) of Kneuven et al. (2020) as C^R_g * u_g(t) term
         add_to_expression!(model[:obj], is_on[gn, t], g.min_power_cost[t])
 
         # Production limit
-        # Equation (18) in Knueven et al. (2020)
+        # Equation (18) in Kneuven et al. (2020)
         #   as \bar{p}_g(t) \le \bar{P}_g u_g(t)
-        # amk: this is a weaker version of (20) and (21) in Knueven et al. (2020)
+        # amk: this is a weaker version of (20) and (21) in Kneuven et al. (2020)
         #      but keeping it here in case those are not present
         power_diff = max(g.max_power[t], 0.0) - max(g.min_power[t], 0.0)
         if power_diff < 1e-7

src/model/formulations/Gar1962/pwlcosts.jl

@@ -2,28 +2,6 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-"""
-    _add_production_piecewise_linear_eqs!
-
-Ensure respect of production limits along each segment.
-Based on Garver (1962).
-Equations (42), (43), (44) in Knueven et al. (2020).
-NB: when reading instance, UnitCommitment.jl already calculates difference between max power for segments k and k-1,
-so the value of cost_segments[k].mw[t] is the max production *for that segment*.
-
-Added to `model`: `:eq_prod_above_def` and `:eq_segprod_limit`.
-
-===
-Variables
-* :segprod
-* :is_on
-* :prod_above
-
-===
-Constraints
-* :eq_prod_above_def
-* :eq_segprod_limit
-"""
 function _add_production_piecewise_linear_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -45,14 +23,14 @@ function _add_production_piecewise_linear_eqs!(
     K = length(g.cost_segments)
     for t in 1:model[:instance].time
         # Definition of production
-        # Equation (43) in Knueven et al. (2020)
+        # Equation (43) in Kneuven et al. (2020)
         eq_prod_above_def[gn, t] = @constraint(
             model,
             prod_above[gn, t] == sum(segprod[gn, t, k] for k in 1:K)
         )
 
         for k in 1:K
-            # Equation (42) in Knueven et al. (2020)
+            # Equation (42) in Kneuven et al. (2020)
             # Without this, solvers will add a lot of implied bound cuts to
             # have this same effect.
             # NB: when reading instance, UnitCommitment.jl already calculates
@@ -69,7 +47,7 @@ function _add_production_piecewise_linear_eqs!(
             set_upper_bound(segprod[gn, t, k], g.cost_segments[k].mw[t])
 
             # Objective function
-            # Equation (44) in Knueven et al. (2020)
+            # Equation (44) in Kneuven et al. (2020)
             add_to_expression!(
                 model[:obj],
                 segprod[gn, t, k],

src/model/formulations/Gar1962/status.jl

@@ -2,12 +2,6 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-"""
-    _add_status_vars!
-
-Adds symbols identified by `Gar1962.StatusVars` to `model`.
-Fix variables if a certain generator _must_ run or based on initial conditions.
-"""
 function _add_status_vars!(
     model::JuMP.Model,
     g::Unit,
@@ -16,108 +10,20 @@ function _add_status_vars!(
     is_on = _init(model, :is_on)
     switch_on = _init(model, :switch_on)
     switch_off = _init(model, :switch_off)
-    FIX_VARS = !formulation_status_vars.fix_vars_via_constraint
-    is_initially_on = _is_initially_on(g) > 0
     for t in 1:model[:instance].time
+        if g.must_run[t]
+            is_on[g.name, t] = 1.0
+            switch_on[g.name, t] = (t == 1 ? 1.0 - _is_initially_on(g) : 0.0)
+            switch_off[g.name, t] = 0.0
+        else
             is_on[g.name, t] = @variable(model, binary = true)
             switch_on[g.name, t] = @variable(model, binary = true)
             switch_off[g.name, t] = @variable(model, binary = true)
-
-        # Use initial conditions and whether a unit must run to fix variables
-        if FIX_VARS
-            # Fix variables using fix function
-            if g.must_run[t]
-                # If the generator _must_ run, then it is obviously on and cannot be switched off
-                # In the first time period, force unit to switch on if was off before
-                # Otherwise, unit is on, and will never turn off, so will never need to turn on
-                fix(is_on[g.name, t], 1.0; force = true)
-                fix(
-                    switch_on[g.name, t],
-                    (t == 1 ? 1.0 - _is_initially_on(g) : 0.0);
-                    force = true,
-                )
-                fix(switch_off[g.name, t], 0.0; force = true)
-            elseif t == 1
-                if is_initially_on
-                    # Generator was on (for g.initial_status time periods),
-                    # so cannot be more switched on until the period after the first time it can be turned off
-                    fix(switch_on[g.name, 1], 0.0; force = true)
-                else
-                    # Generator is initially off (for -g.initial_status time periods)
-                    # Cannot be switched off more
-                    fix(switch_off[g.name, 1], 0.0; force = true)
-                end
-            end
-        else
-            # Add explicit constraint if !FIX_VARS
-            if g.must_run[t]
-                is_on[g.name, t] = 1.0
-                switch_on[g.name, t] =
-                    (t == 1 ? 1.0 - _is_initially_on(g) : 0.0)
-                switch_off[g.name, t] = 0.0
-            elseif t == 1
-                if is_initially_on
-                    switch_on[g.name, t] = 0.0
-                else
-                    switch_off[g.name, t] = 0.0
-                end
-            end
-        end
-
-        # Use initial conditions and whether a unit must run to fix variables
-        if FIX_VARS
-            # Fix variables using fix function
-            if g.must_run[t]
-                # If the generator _must_ run, then it is obviously on and cannot be switched off
-                # In the first time period, force unit to switch on if was off before
-                # Otherwise, unit is on, and will never turn off, so will never need to turn on
-                fix(is_on[g.name, t], 1.0; force = true)
-                fix(
-                    switch_on[g.name, t],
-                    (t == 1 ? 1.0 - _is_initially_on(g) : 0.0);
-                    force = true,
-                )
-                fix(switch_off[g.name, t], 0.0; force = true)
-            elseif t == 1
-                if is_initially_on
-                    # Generator was on (for g.initial_status time periods),
-                    # so cannot be more switched on until the period after the first time it can be turned off
-                    fix(switch_on[g.name, 1], 0.0; force = true)
-                else
-                    # Generator is initially off (for -g.initial_status time periods)
-                    # Cannot be switched off more
-                    fix(switch_off[g.name, 1], 0.0; force = true)
-                end
-            end
-        else
-            # Add explicit constraint if !FIX_VARS
-            if g.must_run[t]
-                is_on[g.name, t] = 1.0
-                switch_on[g.name, t] =
-                    (t == 1 ? 1.0 - _is_initially_on(g) : 0.0)
-                switch_off[g.name, t] = 0.0
-            elseif t == 1
-                if is_initially_on
-                    switch_on[g.name, t] = 0.0
-                else
-                    switch_off[g.name, t] = 0.0
-                end
-            end
         end
     end
     return
 end
 
-"""
-    _add_status_eqs!
-
-Creates constraints `eq_binary_link` and `eq_switch_on_off` using variables in `Gar1962.StatusVars`.
-
-Constraints
----
-* `eq_binary_link`
-* `eq_switch_on_off`
-"""
 function _add_status_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -129,12 +35,8 @@ function _add_status_eqs!(
     switch_off = model[:switch_off]
     switch_on = model[:switch_on]
     for t in 1:model[:instance].time
-        if g.must_run[t]
+        if !g.must_run[t]
-            continue
-        end
-
             # Link binary variables
-        # Equation (2) in Knueven et al. (2020), originally from Garver (1962)
             if t == 1
                 eq_binary_link[g.name, t] = @constraint(
                     model,
@@ -148,13 +50,12 @@ function _add_status_eqs!(
                     switch_on[g.name, t] - switch_off[g.name, t]
                 )
             end
-
             # Cannot switch on and off at the same time
-        # amk: I am not sure this is in Knueven et al. (2020)
             eq_switch_on_off[g.name, t] = @constraint(
                 model,
                 switch_on[g.name, t] + switch_off[g.name, t] <= 1
             )
         end
+    end
     return
 end

src/model/formulations/Gar1962/structs.jl

@@ -17,53 +17,8 @@ import ..PiecewiseLinearCostsFormulation
 import ..ProductionVarsFormulation
 import ..StatusVarsFormulation
 
-"""
-Variables
----
-* `prod_above`:
-        [gen, t];
-        *production above minimum required level*;
-        lb: 0, ub: Inf.
-        KnuOstWat2020: `p'_g(t)`
-* `segprod`:
-        [gen, segment, t];
-        *how much generator produces on cost segment in time t*;
-        lb: 0, ub: Inf.
-        KnuOstWat2020: `p_g^l(t)`
-"""
 struct ProdVars <: ProductionVarsFormulation end
-
 struct PwlCosts <: PiecewiseLinearCostsFormulation end
-
+struct StatusVars <: StatusVarsFormulation end
-"""
-Variables
----
-* `is_on`:
-        [gen, t];
-        *is generator on at time t?*
-        lb: 0, ub: 1, binary.
-        KnuOstWat2020: `u_g(t)`
-* `switch_on`:
-        [gen, t];
-        *indicator that generator will be turned on at t*;
-        lb: 0, ub: 1, binary.
-        KnuOstWat2020: `v_g(t)`
-* `switch_off`: binary;
-        [gen, t];
-        *indicator that generator will be turned off at t*;
-        lb: 0, ub: 1, binary.
-        KnuOstWat2020: `w_g(t)`
-
-Arguments
----
-* `fix_vars_via_constraint`:
-        indicator for whether to set vars to a constant using `fix` or by adding an explicit constraint
-        (particulary useful for debugging purposes).
-"""
-struct StatusVars <: StatusVarsFormulation
-    fix_vars_via_constraint::Bool
-
-    StatusVars() = new(false)
-end
 
 end

src/model/formulations/GenMorRam2017/startstop.jl

@@ -1,100 +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.
-
-"""
-    _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_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)
-        if formulation_status_vars.always_create_vars
-            fix(switch_off[gi, 1], 0.0; force = true)
-            @constraint(mip, vars.switch_off[gi, 1] <= 0)
-        else
-            switch_off[gi, 1] = 0.0
-        end
-    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/KnuOstWat2018/pwlcosts.jl

@@ -2,30 +2,6 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-"""
-    _add_production_piecewise_linear_eqs!
-
-Ensure respect of production limits along each segment.
-Based on Knueven et al. (2018b).
-Eqns. (43), (44), (46), (48) in Knueven et al. (2020).
-NB: when reading instance, UnitCommitment.jl already calculates difference between max power for segments k and k-1
-so the value of cost_segments[k].mw[t] is the max production *for that segment*.
-
-===
-Variables
-* :segprod
-* :is_on
-* :switch_on
-* :switch_off
-* :prod_above
-
-===
-Constraints
-* :eq_prod_above_def
-* :eq_segprod_limit_a
-* :eq_segprod_limit_b
-* :eq_segprod_limit_c
-"""
 function _add_production_piecewise_linear_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -81,7 +57,7 @@ function _add_production_piecewise_linear_eqs!(
             end
 
             if g.min_uptime > 1
-                # Equation (46) in Knueven et al. (2020)
+                # Equation (46) in Kneuven et al. (2020)
                 eq_segprod_limit_a[gn, t, k] = @constraint(
                     model,
                     segprod[gn, t, k] <=
@@ -90,7 +66,7 @@ function _add_production_piecewise_linear_eqs!(
                     (t < T ? Cw * switch_off[gn, t+1] : 0.0)
                 )
             else
-                # Equation (47a)/(48a) in Knueven et al. (2020)
+                # Equation (47a)/(48a) in Kneuven et al. (2020)
                 eq_segprod_limit_b[gn, t, k] = @constraint(
                     model,
                     segprod[gn, t, k] <=
@@ -99,7 +75,7 @@ function _add_production_piecewise_linear_eqs!(
                     (t < T ? max(0, Cv - Cw) * switch_off[gn, t+1] : 0.0)
                 )
 
-                # Equation (47b)/(48b) in Knueven et al. (2020)
+                # Equation (47b)/(48b) in Kneuven et al. (2020)
                 eq_segprod_limit_c[gn, t, k] = @constraint(
                     model,
                     segprod[gn, t, k] <=
@@ -110,14 +86,14 @@ function _add_production_piecewise_linear_eqs!(
             end
 
             # Definition of production
-            # Equation (43) in Knueven et al. (2020)
+            # Equation (43) in Kneuven et al. (2020)
             eq_prod_above_def[gn, t] = @constraint(
                 model,
                 prod_above[gn, t] == sum(segprod[gn, t, k] for k in 1:K)
             )
 
             # Objective function
-            # Equation (44) in Knueven et al. (2020)
+            # Equation (44) in Kneuven et al. (2020)
             add_to_expression!(
                 model[:obj],
                 segprod[gn, t, k],

src/model/formulations/KnuOstWat2018/scosts.jl

@@ -1,123 +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.
-
-"""
-    _add_startup_cost_eqs!
-
-Extended formulation of startup costs using indicator variables
-based on Knueven, Ostrowski, and Watson, 2020
---- equations (59), (60), (61).
-
-Variables
----
-* switch_on
-* switch_off
-* downtime_arc
-
-Constraints
----
-* eq_startup_at_t
-* eq_shutdown_at_t
-"""
-function _add_startup_cost_eqs!(
-    model::JuMP.Model,
-    g::Unit,
-    formulation::MorLatRam2013.StartupCosts,
-)::Nothing
-    S = length(g.startup_categories)
-    if S == 0
-        return
-    end
-    gn = g.name
-
-    _init(model, eq_startup_at_t)
-    _init(model, eq_shutdown_at_t)
-
-    switch_on = model[:switch_on]
-    switch_off = model[:switch_off]
-    downtime_arc = model[:downtime_arc]
-
-    DT = g.min_downtime # minimum time offline
-    TC = g.startup_categories[S].delay # time offline until totally cold
-
-    # If initial_status < 0, then this is the amount of time the generator has been off
-    initial_time_shutdown = (g.initial_status < 0 ? -g.initial_status : 0)
-
-    for t in 1:model[:instance].time
-        # Fix to zero values of downtime_arc outside the feasible time pairs
-        # Specifically, x(t,t') = 0 if t' does not belong to 𝒢 = [t+DT, t+TC-1]
-        # This is because DT is the minimum downtime, so there is no way x(t,t')=1 for t'<t+DT
-        # and TC is the "time until cold" => if the generator starts afterwards, always has max cost
-        #start_time = min(t + DT, T)
-        #end_time = min(t + TC - 1, T)
-        #for tmp_t in t+1:start_time
-        #  fix(vars.downtime_arc[gn, t, tmp_t], 0.; force = true)
-        #end
-        #for tmp_t in end_time+1:T
-        #  fix(vars.downtime_arc[gn, t, tmp_t], 0.; force = true)
-        #end
-
-        # Equation (59) in Knueven et al. (2020)
-        # Relate downtime_arc with switch_on
-        # "switch_on[g,t] >= x_g(t',t) for all t' \in [t-TC+1, t-DT]"
-        eq_startup_at_t[gn, t] = @constraint(
-            model,
-            switch_on[gn, t] >= sum(
-                downtime_arc[gn, tmp_t, t] for
-                tmp_t in t-TC+1:t-DT if tmp_t >= 1
-            )
-        )
-
-        # Equation (60) in Knueven et al. (2020)
-        # "switch_off[g,t] >= x_g(t,t') for all t' \in [t+DT, t+TC-1]"
-        eqs.shutdown_at_t[gn, t] = @constraint(
-            model,
-            switch_off[gn, t] >= sum(
-                downtime_arc[gn, t, tmp_t] for
-                tmp_t in t+DT:t+TC-1 if tmp_t <= T
-            )
-        )
-
-        # Objective function terms for start-up costs
-        # Equation (61) in Knueven et al. (2020)
-        default_category = S
-        if initial_time_shutdown > 0 && t + initial_time_shutdown - 1 < TC
-            for s in 1:S-1
-                # If off for x periods before, then belongs to category s
-                # if -x+1 in [t-delay[s+1]+1,t-delay[s]]
-                # or, equivalently, if total time off in [delay[s], delay[s+1]-1]
-                # where total time off = t - 1 + initial_time_shutdown
-                # (the -1 because not off for current time period)
-                if t + initial_time_shutdown - 1 <
-                   g.startup_categories[s+1].delay
-                    default_category = s
-                    break # does not go into next category
-                end
-            end
-        end
-        add_to_expression!(
-            model[:obj],
-            switch_on[gn, t],
-            g.startup_categories[default_category].cost,
-        )
-
-        for s in 1:S-1
-            # Objective function terms for start-up costs
-            # Equation (61) in Knueven et al. (2020)
-            # Says to replace the cost of last category with cost of category s
-            start_range = max((t - g.startup_categories[s+1].delay + 1), 1)
-            end_range = min((t - g.startup_categories[s].delay), T - 1)
-            for tmp_t in start_range:end_range
-                if (t < tmp_t + DT) || (t >= tmp_t + TC) # the second clause should never be true for s < S
-                    continue
-                end
-                add_to_expression!(
-                    model[:obj],
-                    downtime_arc[gn, tmp_t, t],
-                    g.startup_categories[s].cost - g.startup_categories[S].cost,
-                )
-            end
-        end # iterate over startup categories
-    end # iterate over time
-end # add_startup_costs_KneOstWat20

src/model/formulations/MorLatRam2013/ramp.jl

@@ -2,27 +2,6 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-"""
-    _add_ramp_eqs!
-
-Ensure constraints on ramping are met.
-Needs to be used in combination with shutdown rate constraints, e.g., (21b) in Knueven et al. (2020).
-Based on Morales-España, Latorre, and Ramos, 2013.
-Eqns. (26)+(27) [replaced by (24)+(25) if time-varying min demand] in Knueven et al. (2020).
-
-Variables
----
-* :is_on
-* :switch_off
-* :switch_on
-* :prod_above
-* :reserve
-
-Constraints
----
-* :eq_ramp_up
-* :eq_ramp_down
-"""
 function _add_ramp_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -36,10 +15,10 @@ function _add_ramp_eqs!(
     RESERVES_WHEN_RAMP_DOWN = true
     RESERVES_WHEN_SHUT_DOWN = true
     is_initially_on = (g.initial_status > 0)
-    SU = g.startup_limit   # startup rate
+    SU = g.startup_limit
-    SD = g.shutdown_limit  # shutdown rate
+    SD = g.shutdown_limit
-    RU = g.ramp_up_limit   # ramp up rate
+    RU = g.ramp_up_limit
-    RD = g.ramp_down_limit # ramp down rate
+    RD = g.ramp_down_limit
     gn = g.name
     eq_ramp_down = _init(model, :eq_ramp_down)
     eq_ramp_up = _init(model, :eq_str_ramp_up)
@@ -92,7 +71,7 @@ function _add_ramp_eqs!(
                     RU * is_on[gn, t-1] + SU * switch_on[gn, t]
                 )
             else
-                # Equation (26) in Knueven et al. (2020)
+                # Equation (26) in Kneuven et al. (2020)
                 # TODO: what if RU < SU? places too stringent upper bound
                 # prod_above[gn, t] when starting up, and creates diff with (24).
                 eq_ramp_up[gn, t] = @constraint(
@@ -136,7 +115,7 @@ function _add_ramp_eqs!(
                     RD * is_on[gn, t] + SD * switch_off[gn, t]
                 )
             else
-                # Equation (27) in Knueven et al. (2020)
+                # Equation (27) in Kneuven et al. (2020)
                 # TODO: Similar to above, what to do if shutting down in time t
                 # and RD < SD? There is a difference with (25).
                 eq_ramp_down[gn, t] = @constraint(

src/model/formulations/MorLatRam2013/scosts.jl

@@ -2,56 +2,21 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-"""
-    _add_startup_cost_eqs!
-
-Extended formulation of startup costs using indicator variables
-based on Muckstadt and Wilson, 1968;
-this version by Morales-España, Latorre, and Ramos, 2013.
-Eqns. (54), (55), and (56) in Knueven et al. (2020).
-Note that the last 'constraint' is actually setting the objective.
-
-\tstartup[gi,s,t] ≤ sum_{i=s.delay}^{(s+1).delay-1} switch_off[gi,t-i]
-\tswitch_on[gi,t] = sum_{s=1}^{length(startup_categories)} startup[gi,s,t]
-\tstartup_cost[gi,t] = sum_{s=1}^{length(startup_categories)} cost_segments[s].cost * startup[gi,s,t]
-
-Variables
----
-* startup
-* switch_on
-* switch_off
-
-Constraints
----
-* eq_startup_choose
-* eq_startup_restrict
-"""
 function _add_startup_cost_eqs!(
     model::JuMP.Model,
     g::Unit,
     formulation::MorLatRam2013.StartupCosts,
 )::Nothing
-    S = length(g.startup_categories)
-    if S == 0
-        return
-    end
-
-    # Constraints created
     eq_startup_choose = _init(model, :eq_startup_choose)
     eq_startup_restrict = _init(model, :eq_startup_restrict)
-
+    S = length(g.startup_categories)
-    # Variables needed
     startup = model[:startup]
-    switch_on = model[:switch_on]
-    switch_off = model[:switch_off]
-
-    gn = g.name
     for t in 1:model[:instance].time
         # If unit is switching on, we must choose a startup category
-        # Equation (55) in Knueven et al. (2020)
+        eq_startup_choose[g.name, t] = @constraint(
-        eq_startup_choose[gn, t] = @constraint(
             model,
-            switch_on[gn, t] == sum(startup[gn, t, s] for s in 1:S)
+            model[:switch_on][g.name, t] ==
+            sum(startup[g.name, t, s] for s in 1:S)
         )
 
         for s in 1:S
@@ -61,28 +26,25 @@ function _add_startup_cost_eqs!(
                 range_start = t - g.startup_categories[s+1].delay + 1
                 range_end = t - g.startup_categories[s].delay
                 range = (range_start:range_end)
-                # If initial_status < 0, then this is the amount of time the generator has been off
                 initial_sum = (
                     g.initial_status < 0 && (g.initial_status + 1 in range) ? 1.0 : 0.0
                 )
-                # Change of index version of equation (54) in Knueven et al. (2020):
+                eq_startup_restrict[g.name, t, s] = @constraint(
-                #   startup[gi,s,t] ≤ sum_{i=s.delay}^{(s+1).delay-1} switch_off[gi,t-i]
-                eq_startup_restrict[gn, t, s] = @constraint(
                     model,
-                    startup[gn, t, s] <=
+                    startup[g.name, t, s] <=
-                    initial_sum +
+                    initial_sum + sum(
-                    sum(switch_off[gn, i] for i in range if i >= 1)
+                        model[:switch_off][g.name, i] for i in range if i >= 1
                     )
-            end # if s < S (not the last category)
+                )
+            end
 
             # Objective function terms for start-up costs
-            # Equation (56) in Knueven et al. (2020)
             add_to_expression!(
                 model[:obj],
-                startup[gn, t, s],
+                startup[g.name, t, s],
                 g.startup_categories[s].cost,
             )
-        end # iterate over startup categories
+        end
-    end # iterate over time
+    end
     return
 end

src/model/formulations/MorLatRam2013/startstop.jl

@@ -1,89 +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.
-
-"""
-    _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).
-
-Variables
----
-* :is_on
-* :prod_above
-* :reserve
-* :switch_on
-* :switch_off
-
-Constraints
----
-* :eq_startstop_limit
-* :eq_startup_limit
-* :eq_shutdown_limit
-"""
-function _add_startup_shutdown_limit_eqs!(model::JuMP.Model, g::Unit)::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 # check if g.min_uptime > 1
-    end # loop over time
-end # _add_startup_shutdown_limit_eqs!

src/model/formulations/NowRom2000/scosts.jl

@@ -1,20 +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.
-
-"""
-    _add_startup_cost_eqs!
-
-Based on Nowak and Römisch, 2000.
-Introduces auxiliary startup cost variable, c_g^SU(t) for each time period,
-and uses startup status variable, u_g(t);
-there are exponentially many facets in this space,
-but there is a linear-time separation algorithm (Brandenburg et al., 2017).
-"""
-function _add_startup_cost_eqs!(
-    model::JuMP.Model,
-    g::Unit,
-    formulation::MorLatRam2013.StartupCosts,
-)::Nothing
-    return error("Not implemented.")
-end

src/model/formulations/OstAnjVan2012/ramp.jl

@@ -1,85 +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.
-
-"""
-    _add_ramp_eqs!
-
-Ensure constraints on ramping are met.
-Based on Ostrowski, Anjos, Vannelli (2012).
-Eqn (37) in Knueven et al. (2020).
-
-Variables
----
-* :is_on
-* :prod_above
-* :reserve
-
-Constraints
----
-* :eq_str_prod_limit
-"""
-function _add_ramp_eqs!(
-    model::JuMP.Model,
-    g::Unit,
-    formulation_prod_vars::Gar1962.ProdVars,
-    formulation_ramping::MorLatRam2013.Ramping,
-    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
-    is_initially_on = _is_initially_on(g)
-
-    gn = g.name
-    eq_str_prod_limit = _init(model, :eq_str_prod_limit)
-
-    # Variables that we need
-    reserve = model[:reserve]
-
-    # Gar1962.ProdVars
-    prod_above = model[:prod_above]
-
-    # Gar1962.StatusVars
-    is_on = model[:is_on]
-    switch_off = model[:switch_off]
-
-    # The following are the same for generator g across all time periods
-    UT = g.min_uptime
-
-    SU = g.startup_limit   # startup rate
-    SD = g.shutdown_limit  # shutdown rate
-    RU = g.ramp_up_limit   # ramp up rate
-    RD = g.ramp_down_limit # ramp down rate
-
-    # TODO check initial conditions, but maybe okay as long as (35) and (36) are also used
-    for t in 1:model[:instance].time
-        Pbar = g.max_power[t]
-
-        #TRD = floor((Pbar - SU)/RD)
-        # TODO check amk changed TRD wrt Knueven et al.
-        TRD = ceil((Pbar - SD) / RD) # ramp down time
-
-        if Pbar < 1e-7
-            # Skip this time period if max power = 0
-            continue
-        end
-
-        if UT >= 1
-            # Equation (37) in Knueven et al. (2020)
-            KSD = min(TRD, UT - 1, T - t - 1)
-            eq_str_prod_limit[gn, t] = @constraint(
-                model,
-                prod_above[gn, t] +
-                g.min_power[t] * is_on[gn, t] +
-                (RESERVES_WHEN_RAMP_DOWN ? reserve[gn, t] : 0.0) <=
-                Pbar * is_on[gi, t] - sum(
-                    (Pbar - (SD + i * RD)) * switch_off[gi, t+1+i] for
-                    i in 0:KSD
-                )
-            )
-        end # check UT >= 1
-    end # loop over time
-end

src/model/formulations/PanGua2016/ramp.jl

@@ -2,28 +2,6 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-"""
-    _add_ramp_eqs!
-
-Add tighter upper bounds on production based on ramp-down trajectory.
-Based on (28) in Pan and Guan (2016).
-But there is an extra time period covered using (40) of Knueven et al. (2020).
-Eqns. (38), (40), (41) in Knueven et al. (2020).
-
-Variables
----
-* :prod_above
-* :reserve
-* :is_on
-* :switch_on
-* :switch_off
-
-Constraints
----
-* :str_prod_limit
-* :prod_limit_ramp_up_extra_period
-* :prod_limit_shutdown_trajectory
-"""
 function _add_ramp_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -63,14 +41,14 @@ function _add_ramp_eqs!(
         end
 
         #TRD = floor((Pbar - SU) / RD) # ramp down time
-        # TODO check amk changed TRD wrt Knueven et al.
+        # TODO check amk changed TRD wrt Kneuven et al.
         TRD = ceil((Pbar - SD) / RD)  # ramp down time
         TRU = floor((Pbar - SU) / RU) # ramp up time, can be negative if Pbar < SU
 
         # TODO check initial time periods: what if generator has been running for x periods?
         # But maybe ok as long as (35) and (36) are also used...
         if UT > 1
-            # Equation (38) in Knueven et al. (2020)
+            # Equation (38) in Kneuven et al. (2020)
             # Generalization of (20)
             # Necessary that if any of the switch_on = 1 in the sum,
             # then switch_off[gn, t+1] = 0
@@ -87,7 +65,7 @@ function _add_ramp_eqs!(
             )
 
             if UT - 2 < TRU
-                # Equation (40) in Knueven et al. (2020)
+                # Equation (40) in Kneuven et al. (2020)
                 # Covers an additional time period of the ramp-up trajectory, compared to (38)
                 eq_prod_limit_ramp_up_extra_period[gn, t] = @constraint(
                     model,
@@ -105,7 +83,7 @@ function _add_ramp_eqs!(
             KSD = min(TRD, UT - 1, T - t - 1)
             if KSD > 0
                 KSU = min(TRU, UT - 2 - KSD, t - 1)
-                # Equation (41) in Knueven et al. (2020)
+                # Equation (41) in Kneuven et al. (2020)
                 eq_prod_limit_shutdown_trajectory[gn, t] = @constraint(
                     model,
                     prod_above[gn, t] +

src/model/formulations/base/bus.jl

@@ -2,11 +2,6 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-"""
-    _add_bus!(model::JuMP.Model, b::Bus)::Nothing
-
-Creates `expr_net_injection` and adds `curtail` variable to `model`.
-"""
 function _add_bus!(model::JuMP.Model, b::Bus)::Nothing
     net_injection = _init(model, :expr_net_injection)
     curtail = _init(model, :curtail)

src/model/formulations/base/psload.jl

@@ -2,9 +2,6 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-"""
-    _add_price_sensitive_load!(model::JuMP.Model, ps::PriceSensitiveLoad)
-"""
 function _add_price_sensitive_load!(
     model::JuMP.Model,
     ps::PriceSensitiveLoad,

src/model/formulations/base/sensitivity.jl

@@ -18,7 +18,7 @@ function _injection_shift_factors(;
     lines::Array{TransmissionLine},
 )
     susceptance = _susceptance_matrix(lines)
-    incidence = _reduced_incidence_matrix(buses = buses, lines = lines)
+    incidence = _reduced_incidence_matrix(lines = lines, buses = buses)
     laplacian = transpose(incidence) * susceptance * incidence
     isf = susceptance * incidence * inv(Array(laplacian))
     return isf

src/model/formulations/base/structs.jl

@@ -9,15 +9,6 @@ abstract type StartupCostsFormulation end
 abstract type StatusVarsFormulation end
 abstract type ProductionVarsFormulation end
 
-"""
-    struct Formulation
-
-Every formulation has to specify components for setting production variables and limits,
-startup costs and piecewise-linear costs, ramping variables and constraints,
-status variables (on/off, starting up, shutting down), and transmission constraints.
-
-Some of these components are allowed to be empty, as long as overall validity of the formulation is maintained.
-"""
 struct Formulation
     prod_vars::ProductionVarsFormulation
     pwl_costs::PiecewiseLinearCostsFormulation

src/model/formulations/base/system.jl

@@ -2,32 +2,12 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-"""
-    _add_system_wide_eqs!(model::JuMP.Model)::Nothing
-
-Adds constraints that apply to the whole system, such as relating to net injection and reserves.
-"""
 function _add_system_wide_eqs!(model::JuMP.Model)::Nothing
     _add_net_injection_eqs!(model)
     _add_reserve_eqs!(model)
     return
 end
 
-"""
-    _add_net_injection_eqs!(model::JuMP.Model)::Nothing
-
-Adds `net_injection`, `eq_net_injection_def`, and `eq_power_balance` identifiers into `model`.
-
-Variables
----
-* `expr_net_injection`
-* `net_injection`
-
-Constraints
----
-* `eq_net_injection_def`
-* `eq_power_balance`
-"""
 function _add_net_injection_eqs!(model::JuMP.Model)::Nothing
     T = model[:instance].time
     net_injection = _init(model, :net_injection)
@@ -47,30 +27,11 @@ function _add_net_injection_eqs!(model::JuMP.Model)::Nothing
     return
 end
 
-"""
-    _add_reserve_eqs!(model::JuMP.Model)::Nothing
-
-Ensure constraints on reserves are met.
-Based on Morales-España et al. (2013a).
-Eqn. (68) from Knueven et al. (2020).
-
-Adds `eq_min_reserve` identifier to `model`, and corresponding constraint.
-
-Variables
----
-* `reserve`
-* `reserve_shortfall`
-
-Constraints
----
-* `eq_min_reserve`
-"""
 function _add_reserve_eqs!(model::JuMP.Model)::Nothing
-    instance = model[:instance]
     eq_min_reserve = _init(model, :eq_min_reserve)
     instance = model[:instance]
     for t in 1:instance.time
-        # Equation (68) in Knueven et al. (2020)
+        # Equation (68) in Kneuven et al. (2020)
         # As in Morales-España et al. (2013a)
         # Akin to the alternative formulation with max_power_avail
         # from Carrión and Arroyo (2006) and Ostrowski et al. (2012)

src/model/formulations/base/unit.jl

@@ -2,15 +2,6 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-"""
-    _add_unit!(model::JuMP.Model, g::Unit, formulation::Formulation)
-
-Add production, reserve, startup, shutdown, and status variables,
-and constraints for min uptime/downtime, net injection, production, ramping, startup, shutdown, and status.
-
-Fix variables if a certain generator _must_ run or if a generator provides spinning reserves.
-Also, add overflow penalty to objective for each transmission line.
-"""
 function _add_unit!(model::JuMP.Model, g::Unit, formulation::Formulation)
     if !all(g.must_run) && any(g.must_run)
         error("Partially must-run units are not currently supported")
@@ -44,42 +35,22 @@ function _add_unit!(model::JuMP.Model, g::Unit, formulation::Formulation)
         formulation.status_vars,
     )
     _add_startup_cost_eqs!(model, g, formulation.startup_costs)
-    _add_shutdown_cost_eqs!(model, g)
+    _add_startup_shutdown_limit_eqs!(model, g)
-    _add_startup_shutdown_limit_eqs!(
-        model,
-        g,
-        formulation.status_vars,
-        formulation.prod_vars,
-    )
     _add_status_eqs!(model, g, formulation.status_vars)
     return
 end
 
 _is_initially_on(g::Unit)::Float64 = (g.initial_status > 0 ? 1.0 : 0.0)
 
-"""
+function _add_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
-    _add_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
-
-Add `:reserve` variable to `model`, fixed to zero if no spinning reserves specified.
-"""
-function _add_reserve_vars!(
-    model::JuMP.Model,
-    g::Unit,
-    ALWAYS_CREATE_VARS = false,
-)::Nothing
     reserve = _init(model, :reserve)
-    reserve_shortfall = _init(model, :reserve_shortfall) # for accounting for shortfall penalty in the objective
+    reserve_shortfall = _init(model, :reserve_shortfall)
     for t in 1:model[:instance].time
         if g.provides_spinning_reserves[t]
             reserve[g.name, t] = @variable(model, lower_bound = 0)
-        else
-            if ALWAYS_CREATE_VARS
-                reserve[g.name, t] = @variable(model, lower_bound = 0)
-                fix(reserve[g.name, t], 0.0; force = true)
         else
             reserve[g.name, t] = 0.0
         end
-        end
         reserve_shortfall[t] =
             (model[:instance].shortfall_penalty[t] >= 0) ?
             @variable(model, lower_bound = 0) : 0.0
@@ -87,19 +58,14 @@ function _add_reserve_vars!(
     return
 end
 
-"""
-    _add_reserve_eqs!(model::JuMP.Model, g::Unit)::Nothing
-"""
 function _add_reserve_eqs!(model::JuMP.Model, g::Unit)::Nothing
-    # nothing to do here
+    reserve = model[:reserve]
+    for t in 1:model[:instance].time
+        add_to_expression!(expr_reserve[g.bus.name, t], reserve[g.name, t], 1.0)
+    end
     return
 end
 
-"""
-    _add_startup_shutdown_vars!(model::JuMP.Model, g::Unit)::Nothing
-
-Add `startup` to model.
-"""
 function _add_startup_shutdown_vars!(model::JuMP.Model, g::Unit)::Nothing
     startup = _init(model, :startup)
     for t in 1:model[:instance].time
@@ -110,31 +76,14 @@ 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_status_vars::Gar1962.StatusVars,
-    formulation_prod_vars::Gar1962.ProdVars,
-)::Nothing
     eq_shutdown_limit = _init(model, :eq_shutdown_limit)
     eq_startup_limit = _init(model, :eq_startup_limit)
-
     is_on = model[:is_on]
-    switch_off = model[:switch_off]
-    switch_on = model[:switch_on]
     prod_above = model[:prod_above]
     reserve = model[:reserve]
-
+    switch_off = model[:switch_off]
+    switch_on = model[:switch_on]
     T = model[:instance].time
     for t in 1:T
         # Startup limit
@@ -146,15 +95,8 @@ function _add_startup_shutdown_limit_eqs!(
         )
         # Shutdown limit
         if g.initial_power > g.shutdown_limit
-            # TODO check what happens with these variables when exporting the model
-            # Generator producing too much to be turned off in the first time period
-            # (can a binary variable have bounds x = 0?)
-            if formulation_status_vars.fix_vars_via_constraint
             eq_shutdown_limit[g.name, 0] =
-                    @constraint(model, model[:switch_off][g.name, 1] <= 0.0)
+                @constraint(model, switch_off[g.name, 1] <= 0)
-            else
-                fix(model[:switch_off][g.name, 1], 0.0; force = true)
-            end
         end
         if t < T
             eq_shutdown_limit[g.name, t] = @constraint(
@@ -169,32 +111,6 @@ function _add_startup_shutdown_limit_eqs!(
     return
 end
 
-"""
-    _add_shutdown_cost_eqs!(model::JuMP.Model, g::Unit)::Nothing
-
-Variables
----
-* `switch_off`
-"""
-function _add_shutdown_cost_eqs!(model::JuMP.Model, g::Unit)::Nothing
-    T = model[:instance].time
-    gi = g.name
-    for t in 1:T
-        shutdown_cost = 0.0
-        if shutdown_cost > 1e-7
-            # Equation (62) in Knueven et al. (2020)
-            add_to_expression!(
-                model[:obj],
-                model[:switch_off][gi, t],
-                shutdown_cost,
-            )
-        end
-    end # loop over time
-end
-
-"""
-    _add_ramp_eqs!(model, unit, formulation)
-"""
 function _add_ramp_eqs!(
     model::JuMP.Model,
     g::Unit,
@@ -241,24 +157,6 @@ function _add_ramp_eqs!(
     end
 end
 
-"""
-    _add_min_uptime_downtime_eqs!(model::JuMP.Model, g::Unit)::Nothing
-
-Ensure constraints on up/down time are met.
-Based on Garver (1962), Malkin (2003), and Rajan and Takritti (2005).
-Eqns. (3), (4), (5) in Knueven et al. (2020).
-
-Variables
----
-* `is_on`
-* `switch_off`
-* `switch_on`
-
-Constraints
----
-* `eq_min_uptime`
-* `eq_min_downtime`
-"""
 function _add_min_uptime_downtime_eqs!(model::JuMP.Model, g::Unit)::Nothing
     is_on = model[:is_on]
     switch_off = model[:switch_off]
@@ -268,24 +166,18 @@ function _add_min_uptime_downtime_eqs!(model::JuMP.Model, g::Unit)::Nothing
     T = model[:instance].time
     for t in 1:T
         # Minimum up-time
-        # Equation (4) in Knueven et al. (2020)
         eq_min_uptime[g.name, t] = @constraint(
             model,
             sum(switch_on[g.name, i] for i in (t-g.min_uptime+1):t if i >= 1) <= is_on[g.name, t]
         )
-
         # Minimum down-time
-        # Equation (5) in Knueven et al. (2020)
         eq_min_downtime[g.name, t] = @constraint(
             model,
             sum(
                 switch_off[g.name, i] for i in (t-g.min_downtime+1):t if i >= 1
             ) <= 1 - is_on[g.name, t]
         )
-
         # Minimum up/down-time for initial periods
-        # Equations (3a) and (3b) in Knueven et al. (2020)
-        # (using :switch_on and :switch_off instead of :is_on)
         if t == 1
             if g.initial_status > 0
                 eq_min_uptime[g.name, 0] = @constraint(
@@ -308,9 +200,6 @@ function _add_min_uptime_downtime_eqs!(model::JuMP.Model, g::Unit)::Nothing
     end
 end
 
-"""
-    _add_net_injection_eqs!(model::JuMP.Model, g::Unit)::Nothing
-"""
 function _add_net_injection_eqs!(model::JuMP.Model, g::Unit)::Nothing
     expr_net_injection = model[:expr_net_injection]
     for t in 1:model[:instance].time

src/transform/randomize.jl

@@ -1,53 +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.
-
-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

@@ -0,0 +1,209 @@
+# 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!

src/utils/sysimage.jl

@@ -3,26 +3,31 @@
 # Released under the modified BSD license. See COPYING.md for more details.
 
 using PackageCompiler
+using TOML
+using Logging
 
-using DataStructures
+Logging.disable_logging(Logging.Info)
-using Distributions
+mkpath("build")
-using JSON
-using JuMP
-using MathOptInterface
-using SparseArrays
 
-pkg = [
+println("Generating precompilation statements...")
-    :DataStructures,
+run(`julia --project=. --trace-compile=build/precompile.jl $(ARGS)`)
-    :Distributions,
-    :JSON,
-    :JuMP,
-    :MathOptInterface,
-    :SparseArrays,
-]
 
-@info "Building system image..."
+println("Finding dependencies...")
+project = TOML.parsefile("Project.toml")
+manifest = TOML.parsefile("Manifest.toml")
+deps = Symbol[]
+for dep in keys(project["deps"])
+    if "path" in keys(manifest[dep][1])
+        println("  - $(dep) [skip]")
+    else
+        println("  - $(dep)")
+        push!(deps, Symbol(dep))
+    end
+end
+
+println("Building system image...")
 create_sysimage(
-    pkg,
+    deps,
     precompile_statements_file = "build/precompile.jl",
     sysimage_path = "build/sysimage.so",
 )

test/Project.toml

@@ -0,0 +1,26 @@
+[deps]
+Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
+DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
+Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
+GZip = "92fee26a-97fe-5a0c-ad85-20a5f3185b63"
+Gurobi = "2e9cd046-0924-5485-92f1-d5272153d98b"
+JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
+JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
+LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+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"
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
+[compat]
+DataStructures = "0.18"
+Distributions = "0.25"
+GZip = "0.5"
+JSON = "0.21"
+JuMP = "0.21"
+MathOptInterface = "0.9"
+PackageCompiler = "1"
+julia = "1"

test/import/egret_test.jl

@@ -4,9 +4,12 @@
 
 using UnitCommitment
 
+basedir = @__DIR__
+
 @testset "read_egret_solution" begin
-    solution =
+    solution = UnitCommitment.read_egret_solution(
-        UnitCommitment.read_egret_solution("fixtures/egret_output.json.gz")
+        "$basedir/../fixtures/egret_output.json.gz",
+    )
     for attr in ["Is on", "Production (MW)", "Production cost (\$)"]
         @test attr in keys(solution)
         @test "115_STEAM_1" in keys(solution[attr])

test/instance/read_test.jl

@@ -22,6 +22,7 @@ using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
     @test instance.lines[5].normal_flow_limit == [1e8 for t in 1:4]
     @test instance.lines[5].emergency_flow_limit == [1e8 for t in 1:4]
     @test instance.lines[5].flow_limit_penalty == [5e3 for t in 1:4]
+    @test instance.lines_by_name["l5"].name == "l5"
 
     @test instance.lines[1].name == "l1"
     @test instance.lines[1].source.name == "b1"
@@ -34,6 +35,7 @@ using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
 
     @test instance.buses[9].name == "b9"
     @test instance.buses[9].load == [35.36638, 33.25495, 31.67138, 31.14353]
+    @test instance.buses_by_name["b9"].name == "b9"
 
     unit = instance.units[1]
     @test unit.name == "g1"
@@ -62,6 +64,7 @@ using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
     @test unit.startup_categories[1].cost == 1000.0
     @test unit.startup_categories[2].cost == 1500.0
     @test unit.startup_categories[3].cost == 2000.0
+    @test instance.units_by_name["g1"].name == "g1"
 
     unit = instance.units[2]
     @test unit.name == "g2"
@@ -92,12 +95,15 @@ using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
 
     @test instance.contingencies[1].lines == [instance.lines[1]]
     @test instance.contingencies[1].units == []
+    @test instance.contingencies[1].name == "c1"
+    @test instance.contingencies_by_name["c1"].name == "c1"
 
     load = instance.price_sensitive_loads[1]
     @test load.name == "ps1"
     @test load.bus.name == "b3"
     @test load.revenue == [100.0 for t in 1:4]
     @test load.demand == [50.0 for t in 1:4]
+    @test instance.price_sensitive_loads_by_name["ps1"].name == "ps1"
 end
 
 @testset "read_benchmark sub-hourly" begin

test/runtests.jl

@@ -5,6 +5,7 @@
 using Test
 using UnitCommitment
 
+push!(Base.LOAD_PATH, @__DIR__)
 UnitCommitment._setup_logger()
 
 const ENABLE_LARGE_TESTS = ("UCJL_LARGE_TESTS" in keys(ENV))
@@ -28,7 +29,9 @@ const ENABLE_LARGE_TESTS = ("UCJL_LARGE_TESTS" in keys(ENV))
     @testset "transform" begin
         include("transform/initcond_test.jl")
         include("transform/slice_test.jl")
-        include("transform/randomize_test.jl")
+        @testset "randomize" begin
+            include("transform/randomize/XavQiuAhm2021_test.jl")
+        end
     end
     @testset "validation" begin
         include("validation/repair_test.jl")

test/transform/initcond_test.jl

@@ -4,9 +4,12 @@
 
 using UnitCommitment, Cbc, JuMP
 
+basedir = @__DIR__
+
 @testset "generate_initial_conditions!" begin
     # Load instance
-    instance = UnitCommitment.read("$(pwd())/fixtures/case118-initcond.json.gz")
+    instance =
+        UnitCommitment.read("$basedir/../fixtures/case118-initcond.json.gz")
     optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
 
     # All units should have unknown initial conditions

test/transform/randomize/XavQiuAhm2021_test.jl

@@ -0,0 +1,63 @@
+# 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

@@ -1,43 +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.
-
-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

test/validation/repair_test.jl

@@ -4,9 +4,11 @@
 
 using UnitCommitment, JSON, GZip, DataStructures
 
+basedir = @__DIR__
+
 function parse_case14()
     return JSON.parse(
-        GZip.gzopen("../instances/test/case14.json.gz"),
+        GZip.gzopen("$basedir/../../instances/test/case14.json.gz"),
         dicttype = () -> DefaultOrderedDict(nothing),
     )
 end