Format source code with JuliaFormatter; set up GH Actions

bugfix/formulations
Alinson S. Xavier 4 years ago
parent fb9221b8fb
commit 9224cd2efb

@ -0,0 +1,5 @@
always_for_in = true
always_use_return = true
margin = 80
remove_extra_newlines = true
short_to_long_function_def = true

@ -0,0 +1,28 @@
name: lint
on:
push:
pull_request:
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: julia-actions/setup-julia@latest
with:
version: '1'
- uses: actions/checkout@v1
- name: Format check
shell: julia --color=yes {0}
run: |
using Pkg
Pkg.add(PackageSpec(name="JuliaFormatter", version="0.14.4"))
using JuliaFormatter
format("src", verbose=true)
format("test", verbose=true)
format("benchmark", verbose=true)
out = String(read(Cmd(`git diff`)))
if isempty(out)
exit(0)
end
@error "Some files have not been formatted !!!"
write(stdout, out)
exit(1)

@ -22,4 +22,8 @@ test: build/sysimage.so
@echo Running tests...
$(JULIA) --sysimage build/sysimage.so -e 'using Pkg; Pkg.test("UnitCommitment")' | tee build/test.log
format:
julia -e 'using JuliaFormatter; format("src"); format("test"); format("benchmark")'
.PHONY: docs test

@ -30,34 +30,37 @@ function main()
time_model = @elapsed begin
model = build_model(
instance=instance,
optimizer=optimizer_with_attributes(
instance = instance,
optimizer = optimizer_with_attributes(
Gurobi.Optimizer,
"Threads" => 4,
"Seed" => rand(1:1000),
),
variable_names=true,
variable_names = true,
)
end
@info "Optimizing..."
BLAS.set_num_threads(1)
UnitCommitment.optimize!(model, time_limit=time_limit, gap_limit=1e-3)
UnitCommitment.optimize!(
model,
time_limit = time_limit,
gap_limit = 1e-3,
)
end
@info @sprintf("Total time was %.2f seconds", total_time)
@info "Writing: $solution_filename"
solution = UnitCommitment.solution(model)
open(solution_filename, "w") do file
JSON.print(file, solution, 2)
return JSON.print(file, solution, 2)
end
@info "Verifying solution..."
UnitCommitment.validate(instance, solution)
UnitCommitment.validate(instance, solution)
@info "Exporting model..."
JuMP.write_to_file(model, model_filename)
return JuMP.write_to_file(model, model_filename)
end
main()

@ -3,12 +3,12 @@
# Released under the modified BSD license. See COPYING.md for more details.
module UnitCommitment
include("log.jl")
include("instance.jl")
include("screening.jl")
include("model.jl")
include("sensitivity.jl")
include("validate.jl")
include("convert.jl")
include("initcond.jl")
include("log.jl")
include("instance.jl")
include("screening.jl")
include("model.jl")
include("sensitivity.jl")
include("validate.jl")
include("convert.jl")
include("initcond.jl")
end

@ -10,20 +10,20 @@ function _read_json(path::String)::OrderedDict
else
file = open(path)
end
return JSON.parse(file, dicttype=()->DefaultOrderedDict(nothing))
return JSON.parse(file, dicttype = () -> DefaultOrderedDict(nothing))
end
function _read_egret_solution(path::String)::OrderedDict
egret = _read_json(path)
T = length(egret["system"]["time_keys"])
solution = OrderedDict()
is_on = solution["Is on"] = OrderedDict()
production = solution["Production (MW)"] = OrderedDict()
reserve = solution["Reserve (MW)"] = OrderedDict()
production_cost = solution["Production cost (\$)"] = OrderedDict()
startup_cost = solution["Startup cost (\$)"] = OrderedDict()
for (gen_name, gen_dict) in egret["elements"]["generator"]
if endswith(gen_name, "_T") || endswith(gen_name, "_R")
gen_name = gen_name[1:end-2]
@ -39,18 +39,18 @@ function _read_egret_solution(path::String)::OrderedDict
else
reserve[gen_name] = zeros(T)
end
startup_cost[gen_name] = zeros(T)
startup_cost[gen_name] = zeros(T)
production_cost[gen_name] = zeros(T)
if "commitment_cost" in keys(gen_dict)
for t in 1:T
x = gen_dict["commitment"]["values"][t]
commitment_cost = gen_dict["commitment_cost"]["values"][t]
prod_above_cost = gen_dict["production_cost"]["values"][t]
prod_base_cost = gen_dict["p_cost"]["values"][1][2] * x
prod_base_cost = gen_dict["p_cost"]["values"][1][2] * x
startup_cost[gen_name][t] = commitment_cost - prod_base_cost
production_cost[gen_name][t] = prod_above_cost + prod_base_cost
end
end
end
return solution
end
end

@ -19,33 +19,31 @@ function generate_initial_conditions!(
B = instance.buses
t = 1
mip = JuMP.Model(optimizer)
# Decision variables
@variable(mip, x[G], Bin)
@variable(mip, p[G] >= 0)
# Constraint: Minimum power
@constraint(mip,
min_power[g in G],
p[g] >= g.min_power[t] * x[g])
@constraint(mip, min_power[g in G], p[g] >= g.min_power[t] * x[g])
# Constraint: Maximum power
@constraint(mip,
max_power[g in G],
p[g] <= g.max_power[t] * x[g])
@constraint(mip, max_power[g in G], p[g] <= g.max_power[t] * x[g])
# Constraint: Production equals demand
@constraint(mip,
power_balance,
sum(b.load[t] for b in B) == sum(p[g] for g in G))
@constraint(
mip,
power_balance,
sum(b.load[t] for b in B) == sum(p[g] for g in G)
)
# Constraint: Must run
for g in G
if g.must_run[t]
@constraint(mip, x[g] == 1)
end
end
# Objective function
function cost_slope(g)
mw = g.min_power[t]
@ -60,12 +58,10 @@ function generate_initial_conditions!(
return c / mw
end
end
@objective(mip,
Min,
sum(p[g] * cost_slope(g) for g in G))
@objective(mip, Min, sum(p[g] * cost_slope(g) for g in G))
JuMP.optimize!(mip)
for g in G
if JuMP.value(x[g]) > 0
g.initial_power = JuMP.value(p[g])

@ -8,7 +8,6 @@ using DataStructures
using GZip
import Base: getindex, time
mutable struct Bus
name::String
offset::Int
@ -17,19 +16,16 @@ mutable struct Bus
price_sensitive_loads::Vector
end
mutable struct CostSegment
mw::Vector{Float64}
cost::Vector{Float64}
end
mutable struct StartupCategory
delay::Int
cost::Float64
end
mutable struct Unit
name::String
bus::Bus
@ -50,7 +46,6 @@ mutable struct Unit
startup_categories::Vector{StartupCategory}
end
mutable struct TransmissionLine
name::String
offset::Int
@ -63,19 +58,16 @@ mutable struct TransmissionLine
flow_limit_penalty::Vector{Float64}
end
mutable struct Reserves
spinning::Vector{Float64}
end
mutable struct Contingency
name::String
lines::Vector{TransmissionLine}
units::Vector{Unit}
end
mutable struct PriceSensitiveLoad
name::String
bus::Bus
@ -83,7 +75,6 @@ mutable struct PriceSensitiveLoad
revenue::Vector{Float64}
end
mutable struct UnitCommitmentInstance
time::Int
power_balance_penalty::Vector{Float64}
@ -95,25 +86,26 @@ mutable struct UnitCommitmentInstance
price_sensitive_loads::Vector{PriceSensitiveLoad}
end
function Base.show(io::IO, instance::UnitCommitmentInstance)
print(io, "UnitCommitmentInstance(")
print(io, "$(length(instance.units)) units, ")
print(io, "$(length(instance.buses)) buses, ")
print(io, "$(length(instance.lines)) lines, ")
print(io, "$(length(instance.contingencies)) contingencies, ")
print(io, "$(length(instance.price_sensitive_loads)) price sensitive loads, ")
print(
io,
"$(length(instance.price_sensitive_loads)) price sensitive loads, ",
)
print(io, "$(instance.time) time steps")
print(io, ")")
return
end
function read_benchmark(name::AbstractString) :: UnitCommitmentInstance
function read_benchmark(name::AbstractString)::UnitCommitmentInstance
basedir = dirname(@__FILE__)
return UnitCommitment.read("$basedir/../instances/$name.json.gz")
end
function read(path::AbstractString)::UnitCommitmentInstance
if endswith(path, ".gz")
return _read(gzopen(path))
@ -122,50 +114,51 @@ function read(path::AbstractString)::UnitCommitmentInstance
end
end
function _read(file::IO)::UnitCommitmentInstance
return _from_json(JSON.parse(file, dicttype=()->DefaultOrderedDict(nothing)))
return _from_json(
JSON.parse(file, dicttype = () -> DefaultOrderedDict(nothing)),
)
end
function _from_json(json; repair=true)
function _from_json(json; repair = true)
units = Unit[]
buses = Bus[]
contingencies = Contingency[]
lines = TransmissionLine[]
loads = PriceSensitiveLoad[]
function scalar(x; default=nothing)
function scalar(x; default = nothing)
x !== nothing || return default
x
return x
end
time_horizon = json["Parameters"]["Time (h)"]
if time_horizon === nothing
time_horizon = json["Parameters"]["Time horizon (h)"]
end
time_horizon !== nothing || error("Missing required parameter: Time horizon (h)")
time_step = scalar(json["Parameters"]["Time step (min)"], default=60)
(60 % time_step == 0) || error("Time step $time_step is not a divisor of 60")
time_horizon !== nothing || error("Missing parameter: Time horizon (h)")
time_step = scalar(json["Parameters"]["Time step (min)"], default = 60)
(60 % time_step == 0) ||
error("Time step $time_step is not a divisor of 60")
time_multiplier = 60 ÷ time_step
T = time_horizon * time_multiplier
name_to_bus = Dict{String, Bus}()
name_to_line = Dict{String, TransmissionLine}()
name_to_unit = Dict{String, Unit}()
function timeseries(x; default=nothing)
name_to_bus = Dict{String,Bus}()
name_to_line = Dict{String,TransmissionLine}()
name_to_unit = Dict{String,Unit}()
function timeseries(x; default = nothing)
x !== nothing || return default
x isa Array || return [x for t in 1:T]
return x
end
# Read parameters
power_balance_penalty = timeseries(
json["Parameters"]["Power balance penalty (\$/MW)"],
default=[1000.0 for t in 1:T],
default = [1000.0 for t in 1:T],
)
# Read buses
for (bus_name, dict) in json["Buses"]
bus = Bus(
@ -178,15 +171,19 @@ function _from_json(json; repair=true)
name_to_bus[bus_name] = bus
push!(buses, bus)
end
# Read units
for (unit_name, dict) in json["Generators"]
bus = name_to_bus[dict["Bus"]]
# Read production cost curve
K = length(dict["Production cost curve (MW)"])
curve_mw = hcat([timeseries(dict["Production cost curve (MW)"][k]) for k in 1:K]...)
curve_cost = hcat([timeseries(dict["Production cost curve (\$)"][k]) for k in 1:K]...)
curve_mw = hcat(
[timeseries(dict["Production cost curve (MW)"][k]) for k in 1:K]...,
)
curve_cost = hcat(
[timeseries(dict["Production cost curve (\$)"][k]) for k in 1:K]...,
)
min_power = curve_mw[:, 1]
max_power = curve_mw[:, K]
min_power_cost = curve_cost[:, 1]
@ -194,13 +191,13 @@ function _from_json(json; repair=true)
for k in 2:K
amount = curve_mw[:, k] - curve_mw[:, k-1]
cost = (curve_cost[:, k] - curve_cost[:, k-1]) ./ amount
replace!(cost, NaN=>0.0)
replace!(cost, NaN => 0.0)
push!(segments, CostSegment(amount, cost))
end
# Read startup costs
startup_delays = scalar(dict["Startup delays (h)"], default=[1])
startup_costs = scalar(dict["Startup costs (\$)"], default=[0.])
startup_delays = scalar(dict["Startup delays (h)"], default = [1])
startup_costs = scalar(dict["Startup costs (\$)"], default = [0.0])
startup_categories = StartupCategory[]
for k in 1:length(startup_delays)
push!(
@ -211,40 +208,43 @@ function _from_json(json; repair=true)
),
)
end
# Read and validate initial conditions
initial_power = scalar(dict["Initial power (MW)"], default=nothing)
initial_status = scalar(dict["Initial status (h)"], default=nothing)
initial_power = scalar(dict["Initial power (MW)"], default = nothing)
initial_status = scalar(dict["Initial status (h)"], default = nothing)
if initial_power === nothing
initial_status === nothing || error("unit $unit_name has initial status but no initial power")
initial_status === nothing ||
error("unit $unit_name has initial status but no initial power")
else
initial_status !== nothing || error("unit $unit_name has initial power but no initial status")
initial_status != 0 || error("unit $unit_name has invalid initial status")
initial_status !== nothing ||
error("unit $unit_name has initial power but no initial status")
initial_status != 0 ||
error("unit $unit_name has invalid initial status")
if initial_status < 0 && initial_power > 1e-3
error("unit $unit_name has invalid initial power")
end
initial_status *= time_multiplier
end
unit = Unit(
unit_name,
bus,
max_power,
min_power,
timeseries(dict["Must run?"], default=[false for t in 1:T]),
timeseries(dict["Must run?"], default = [false for t in 1:T]),
min_power_cost,
segments,
scalar(dict["Minimum uptime (h)"], default=1) * time_multiplier,
scalar(dict["Minimum downtime (h)"], default=1) * time_multiplier,
scalar(dict["Ramp up limit (MW)"], default=1e6),
scalar(dict["Ramp down limit (MW)"], default=1e6),
scalar(dict["Startup limit (MW)"], default=1e6),
scalar(dict["Shutdown limit (MW)"], default=1e6),
scalar(dict["Minimum uptime (h)"], default = 1) * time_multiplier,
scalar(dict["Minimum downtime (h)"], default = 1) * time_multiplier,
scalar(dict["Ramp up limit (MW)"], default = 1e6),
scalar(dict["Ramp down limit (MW)"], default = 1e6),
scalar(dict["Startup limit (MW)"], default = 1e6),
scalar(dict["Shutdown limit (MW)"], default = 1e6),
initial_status,
initial_power,
timeseries(
dict["Provides spinning reserves?"],
default=[true for t in 1:T],
default = [true for t in 1:T],
),
startup_categories,
)
@ -252,16 +252,14 @@ function _from_json(json; repair=true)
name_to_unit[unit_name] = unit
push!(units, unit)
end
# Read reserves
reserves = Reserves(zeros(T))
if "Reserves" in keys(json)
reserves.spinning = timeseries(
json["Reserves"]["Spinning (MW)"],
default=zeros(T),
)
reserves.spinning =
timeseries(json["Reserves"]["Spinning (MW)"], default = zeros(T))
end
# Read transmission lines
if "Transmission lines" in keys(json)
for (line_name, dict) in json["Transmission lines"]
@ -274,38 +272,40 @@ function _from_json(json; repair=true)
scalar(dict["Susceptance (S)"]),
timeseries(
dict["Normal flow limit (MW)"],
default=[1e8 for t in 1:T],
default = [1e8 for t in 1:T],
),
timeseries(
dict["Emergency flow limit (MW)"],
default=[1e8 for t in 1:T],
default = [1e8 for t in 1:T],
),
timeseries(
dict["Flow limit penalty (\$/MW)"],
default=[5000.0 for t in 1:T],
default = [5000.0 for t in 1:T],
),
)
name_to_line[line_name] = line
push!(lines, line)
end
end
# Read contingencies
if "Contingencies" in keys(json)
for (cont_name, dict) in json["Contingencies"]
affected_units = Unit[]
affected_lines = TransmissionLine[]
if "Affected lines" in keys(dict)
affected_lines = [name_to_line[l] for l in dict["Affected lines"]]
affected_lines =
[name_to_line[l] for l in dict["Affected lines"]]
end
if "Affected units" in keys(dict)
affected_units = [name_to_unit[u] for u in dict["Affected units"]]
affected_units =
[name_to_unit[u] for u in dict["Affected units"]]
end
cont = Contingency(cont_name, affected_lines, affected_units)
push!(contingencies, cont)
end
end
# Read price-sensitive loads
if "Price-sensitive loads" in keys(json)
for (load_name, dict) in json["Price-sensitive loads"]
@ -320,7 +320,7 @@ function _from_json(json; repair=true)
push!(loads, load)
end
end
instance = UnitCommitmentInstance(
T,
power_balance_penalty,
@ -337,7 +337,6 @@ function _from_json(json; repair=true)
return instance
end
"""
slice(instance, range)
@ -387,5 +386,4 @@ function slice(
return modified
end
export UnitCommitmentInstance

@ -7,35 +7,37 @@ using Base.CoreLogging, Logging, Printf
struct TimeLogger <: AbstractLogger
initial_time::Float64
file::Union{Nothing, IOStream}
screen_log_level
io_log_level
file::Union{Nothing,IOStream}
screen_log_level::Any
io_log_level::Any
end
function TimeLogger(;
initial_time::Float64,
file::Union{Nothing, IOStream} = nothing,
screen_log_level = CoreLogging.Info,
io_log_level = CoreLogging.Info,
) :: TimeLogger
initial_time::Float64,
file::Union{Nothing,IOStream} = nothing,
screen_log_level = CoreLogging.Info,
io_log_level = CoreLogging.Info,
)::TimeLogger
return TimeLogger(initial_time, file, screen_log_level, io_log_level)
end
min_enabled_level(logger::TimeLogger) = logger.io_log_level
shouldlog(logger::TimeLogger, level, _module, group, id) = true
function handle_message(logger::TimeLogger,
level,
message,
_module,
group,
id,
filepath,
line;
kwargs...)
function handle_message(
logger::TimeLogger,
level,
message,
_module,
group,
id,
filepath,
line;
kwargs...,
)
elapsed_time = time() - logger.initial_time
time_string = @sprintf("[%12.3f] ", elapsed_time)
if level >= Logging.Error
color = :light_red
elseif level >= Logging.Warn
@ -43,9 +45,9 @@ function handle_message(logger::TimeLogger,
else
color = :light_green
end
if level >= logger.screen_log_level
printstyled(time_string, color=color)
printstyled(time_string, color = color)
println(message)
end
if logger.file !== nothing && level >= logger.io_log_level
@ -58,5 +60,5 @@ end
function _setup_logger()
initial_time = time()
global_logger(TimeLogger(initial_time=initial_time))
return global_logger(TimeLogger(initial_time = initial_time))
end

@ -5,15 +5,14 @@
using JuMP, MathOptInterface, DataStructures
import JuMP: value, fix, set_name
# Extend some JuMP functions so that decision variables can be safely replaced by
# (constant) floating point numbers.
function value(x::Float64)
x
return x
end
function fix(x::Float64, v::Float64; force)
abs(x - v) < 1e-6 || error("Value mismatch: $x != $v")
return abs(x - v) < 1e-6 || error("Value mismatch: $x != $v")
end
function set_name(x::Float64, n::String)
@ -21,20 +20,19 @@ function set_name(x::Float64, n::String)
end
function build_model(;
filename::Union{String, Nothing}=nothing,
instance::Union{UnitCommitmentInstance, Nothing}=nothing,
isf::Union{Matrix{Float64}, Nothing}=nothing,
lodf::Union{Matrix{Float64}, Nothing}=nothing,
isf_cutoff::Float64=0.005,
lodf_cutoff::Float64=0.001,
optimizer=nothing,
variable_names::Bool=false,
filename::Union{String,Nothing} = nothing,
instance::Union{UnitCommitmentInstance,Nothing} = nothing,
isf::Union{Matrix{Float64},Nothing} = nothing,
lodf::Union{Matrix{Float64},Nothing} = nothing,
isf_cutoff::Float64 = 0.005,
lodf_cutoff::Float64 = 0.001,
optimizer = nothing,
variable_names::Bool = false,
)::JuMP.Model
if (filename === nothing) && (instance === nothing)
error("Either filename or instance must be specified")
end
if filename !== nothing
@info "Reading: $(filename)"
time_read = @elapsed begin
@ -42,7 +40,7 @@ function build_model(;
end
@info @sprintf("Read problem in %.2f seconds", time_read)
end
if length(instance.buses) == 1
isf = zeros(0, 0)
lodf = zeros(0, 0)
@ -51,25 +49,29 @@ function build_model(;
@info "Computing injection shift factors..."
time_isf = @elapsed begin
isf = UnitCommitment._injection_shift_factors(
lines=instance.lines,
buses=instance.buses,
lines = instance.lines,
buses = instance.buses,
)
end
@info @sprintf("Computed ISF in %.2f seconds", time_isf)
@info "Computing line outage factors..."
time_lodf = @elapsed begin
lodf = UnitCommitment._line_outage_factors(
lines=instance.lines,
buses=instance.buses,
isf=isf,
lines = instance.lines,
buses = instance.buses,
isf = isf,
)
end
@info @sprintf("Computed LODF in %.2f seconds", time_lodf)
@info @sprintf("Applying PTDF and LODF cutoffs (%.5f, %.5f)", isf_cutoff, lodf_cutoff)
isf[abs.(isf) .< isf_cutoff] .= 0
lodf[abs.(lodf) .< lodf_cutoff] .= 0
@info @sprintf(
"Applying PTDF and LODF cutoffs (%.5f, %.5f)",
isf_cutoff,
lodf_cutoff
)
isf[abs.(isf).<isf_cutoff] .= 0
lodf[abs.(lodf).<lodf_cutoff] .= 0
end
end
@ -138,21 +140,19 @@ function build_model(;
if variable_names
_set_names!(model)
end
return model
end
function _add_transmission_line!(model, lm)
obj, T = model[:obj], model[:instance].time
overflow = model[:overflow]
for t in 1:T
v = overflow[lm.name, t] = @variable(model, lower_bound=0)
v = overflow[lm.name, t] = @variable(model, lower_bound = 0)
add_to_expression!(obj, v, lm.flow_limit_penalty[t])
end
end
function _add_bus!(model::JuMP.Model, b::Bus)
mip = model
net_injection = model[:expr_net_injection]
@ -161,12 +161,13 @@ function _add_bus!(model::JuMP.Model, b::Bus)
for t in 1:model[:instance].time
# Fixed load
net_injection[b.name, t] = AffExpr(-b.load[t])
# Reserves
reserve[b.name, t] = AffExpr()
# Load curtailment
curtail[b.name, t] = @variable(mip, lower_bound=0, upper_bound=b.load[t])
# Load curtailment
curtail[b.name, t] =
@variable(mip, lower_bound = 0, upper_bound = b.load[t])
add_to_expression!(net_injection[b.name, t], curtail[b.name, t], 1.0)
add_to_expression!(
model[:obj],
@ -176,24 +177,27 @@ function _add_bus!(model::JuMP.Model, b::Bus)
end
end
function _add_price_sensitive_load!(model::JuMP.Model, ps::PriceSensitiveLoad)
mip = model
loads = model[:loads]
net_injection = model[:expr_net_injection]
for t in 1:model[:instance].time
# Decision variable
loads[ps.name, t] = @variable(mip, lower_bound=0, upper_bound=ps.demand[t])
loads[ps.name, t] =
@variable(mip, lower_bound = 0, upper_bound = ps.demand[t])
# Objective function terms
add_to_expression!(model[:obj], loads[ps.name, t], -ps.revenue[t])
# Net injection
add_to_expression!(net_injection[ps.bus.name, t], loads[ps.name, t], -1.0)
add_to_expression!(
net_injection[ps.bus.name, t],
loads[ps.name, t],
-1.0,
)
end
end
function _add_unit!(model::JuMP.Model, g::Unit)
mip, T = model, model[:instance].time
gi, K, S = g.name, length(g.cost_segments), length(g.startup_categories)
@ -207,11 +211,11 @@ function _add_unit!(model::JuMP.Model, g::Unit)
switch_off = model[:switch_off]
expr_net_injection = model[:expr_net_injection]
expr_reserve = model[:expr_reserve]
if !all(g.must_run) && any(g.must_run)
error("Partially must-run units are not currently supported")
end
if g.initial_power === nothing || g.initial_status === nothing
error("Initial conditions for $(g.name) must be provided")
end
@ -221,25 +225,25 @@ function _add_unit!(model::JuMP.Model, g::Unit)
# Decision variables
for t in 1:T
for k in 1:K
segprod[gi, t, k] = @variable(model, lower_bound=0)
segprod[gi, t, k] = @variable(model, lower_bound = 0)
end
prod_above[gi, t] = @variable(model, lower_bound=0)
prod_above[gi, t] = @variable(model, lower_bound = 0)
if g.provides_spinning_reserves[t]
reserve[gi, t] = @variable(model, lower_bound=0)
reserve[gi, t] = @variable(model, lower_bound = 0)
else
reserve[gi, t] = 0.0
end
for s in 1:S
startup[gi, t, s] = @variable(model, binary=true)
startup[gi, t, s] = @variable(model, binary = true)
end
if g.must_run[t]
is_on[gi, t] = 1.0
switch_on[gi, t] = (t == 1 ? 1.0 - is_initially_on : 0.0)
switch_off[gi, t] = 0.0
else
is_on[gi, t] = @variable(model, binary=true)
switch_on[gi, t] = @variable(model, binary=true)
switch_off[gi, t] = @variable(model, binary=true)
is_on[gi, t] = @variable(model, binary = true)
switch_on[gi, t] = @variable(model, binary = true)
switch_off[gi, t] = @variable(model, binary = true)
end
end
@ -247,19 +251,28 @@ function _add_unit!(model::JuMP.Model, g::Unit)
# Time-dependent start-up costs
for s in 1:S
# If unit is switching on, we must choose a startup category
model[:eq_startup_choose][gi, t, s] =
@constraint(mip, switch_on[gi, t] == sum(startup[gi, t, s] for s in 1:S))
model[:eq_startup_choose][gi, t, s] = @constraint(
mip,
switch_on[gi, t] == sum(startup[gi, t, s] for s in 1:S)
)
# If unit has not switched off in the last `delay` time periods, startup category is forbidden.
# The last startup category is always allowed.
if s < S
range = (t - g.startup_categories[s + 1].delay + 1):(t - g.startup_categories[s].delay)
initial_sum = (g.initial_status < 0 && (g.initial_status + 1 in range) ? 1.0 : 0.0)
model[:eq_startup_restrict][gi, t, s] =
@constraint(mip, startup[gi, t, s]
<= initial_sum + sum(switch_off[gi, i] for i in range if i >= 1))
range_start = t - g.startup_categories[s+1].delay + 1
range_end = t - g.startup_categories[s].delay
range = (range_start:range_end)
initial_sum = (
g.initial_status < 0 && (g.initial_status + 1 in range) ? 1.0 : 0.0
)
model[:eq_startup_restrict][gi, t, s] = @constraint(
mip,
startup[gi, t, s] <=
initial_sum +
sum(switch_off[gi, i] for i in range if i >= 1)
)
end
# Objective function terms for start-up costs
add_to_expression!(
model[:obj],
@ -267,142 +280,171 @@ function _add_unit!(model::JuMP.Model, g::Unit)
g.startup_categories[s].cost,
)
end
# Objective function terms for production costs
add_to_expression!(model[:obj], is_on[gi, t], g.min_power_cost[t])
for k in 1:K
add_to_expression!(model[:obj], segprod[gi, t, k], g.cost_segments[k].cost[t])
add_to_expression!(
model[:obj],
segprod[gi, t, k],
g.cost_segments[k].cost[t],
)
end
# Production limits (piecewise-linear segments)
for k in 1:K
model[:eq_segprod_limit][gi, t, k] =
@constraint(mip, segprod[gi, t, k] <= g.cost_segments[k].mw[t] * is_on[gi, t])
model[:eq_segprod_limit][gi, t, k] = @constraint(
mip,
segprod[gi, t, k] <= g.cost_segments[k].mw[t] * is_on[gi, t]
)
end
# Definition of production
model[:eq_prod_above_def][gi, t] =
@constraint(mip, prod_above[gi, t] == sum(segprod[gi, t, k] for k in 1:K))
model[:eq_prod_above_def][gi, t] = @constraint(
mip,
prod_above[gi, t] == sum(segprod[gi, t, k] for k in 1:K)
)
# Production limit
model[:eq_prod_limit][gi, t] =
@constraint(mip,
prod_above[gi, t] + reserve[gi, t]
<= (g.max_power[t] - g.min_power[t]) * is_on[gi, t])
model[:eq_prod_limit][gi, t] = @constraint(
mip,
prod_above[gi, t] + reserve[gi, t] <=
(g.max_power[t] - g.min_power[t]) * is_on[gi, t]
)
# Binary variable equations for economic units
if !g.must_run[t]
# Link binary variables
if t == 1
model[:eq_binary_link][gi, t] =
@constraint(mip,
is_on[gi, t] - is_initially_on ==
switch_on[gi, t] - switch_off[gi, t])
model[:eq_binary_link][gi, t] = @constraint(
mip,
is_on[gi, t] - is_initially_on ==
switch_on[gi, t] - switch_off[gi, t]
)
else
model[:eq_binary_link][gi, t] =
@constraint(mip,
is_on[gi, t] - is_on[gi, t-1] ==
switch_on[gi, t] - switch_off[gi, t])
model[:eq_binary_link][gi, t] = @constraint(
mip,
is_on[gi, t] - is_on[gi, t-1] ==
switch_on[gi, t] - switch_off[gi, t]
)
end
# Cannot switch on and off at the same time
model[:eq_switch_on_off][gi, t] =
@constraint(mip, switch_on[gi, t] + switch_off[gi, t] <= 1)
end
# Ramp up limit
if t == 1
if is_initially_on == 1
model[:eq_ramp_up][gi, t] =
@constraint(mip,
prod_above[gi, t] + reserve[gi, t] <=
(g.initial_power - g.min_power[t]) + g.ramp_up_limit)
model[:eq_ramp_up][gi, t] = @constraint(
mip,
prod_above[gi, t] + reserve[gi, t] <=
(g.initial_power - g.min_power[t]) + g.ramp_up_limit
)
end
else
model[:eq_ramp_up][gi, t] =
@constraint(mip,
prod_above[gi, t] + reserve[gi, t] <=
prod_above[gi, t-1] + g.ramp_up_limit)
model[:eq_ramp_up][gi, t] = @constraint(
mip,
prod_above[gi, t] + reserve[gi, t] <=
prod_above[gi, t-1] + g.ramp_up_limit
)
end
# Ramp down limit
if t == 1
if is_initially_on == 1
model[:eq_ramp_down][gi, t] =
@constraint(mip,
prod_above[gi, t] >=
(g.initial_power - g.min_power[t]) - g.ramp_down_limit)
model[:eq_ramp_down][gi, t] = @constraint(
mip,
prod_above[gi, t] >=
(g.initial_power - g.min_power[t]) - g.ramp_down_limit
)
end
else
model[:eq_ramp_down][gi, t] =
@constraint(mip,
prod_above[gi, t] >=
prod_above[gi, t-1] - g.ramp_down_limit)
model[:eq_ramp_down][gi, t] = @constraint(
mip,
prod_above[gi, t] >= prod_above[gi, t-1] - g.ramp_down_limit
)
end
# Startup limit
model[:eq_startup_limit][gi, t] =
@constraint(mip,
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])
model[:eq_startup_limit][gi, t] = @constraint(
mip,
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 limit
if g.initial_power > g.shutdown_limit
model[:eq_shutdown_limit][gi, 0] =
model[:eq_shutdown_limit][gi, 0] =
@constraint(mip, switch_off[gi, 1] <= 0)
end
if t < T
model[:eq_shutdown_limit][gi, t] =
@constraint(mip,
prod_above[gi, t] <=
(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])
model[:eq_shutdown_limit][gi, t] = @constraint(
mip,
prod_above[gi, t] <=
(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
# Minimum up-time
model[:eq_min_uptime][gi, t] =
@constraint(mip,
sum(switch_on[gi, i]
for i in (t - g.min_uptime + 1):t if i >= 1
) <= is_on[gi, t])
model[:eq_min_uptime][gi, t] = @constraint(
mip,
sum(switch_on[gi, i] for i in (t-g.min_uptime+1):t if i >= 1) <=
is_on[gi, t]
)
# # Minimum down-time
model[:eq_min_downtime][gi, t] =
@constraint(mip,
sum(switch_off[gi, i]
for i in (t - g.min_downtime + 1):t if i >= 1
) <= 1 - is_on[gi, t])
model[:eq_min_downtime][gi, t] = @constraint(
mip,
sum(switch_off[gi, i] for i in (t-g.min_downtime+1):t if i >= 1) <= 1 - is_on[gi, t]
)
# Minimum up/down-time for initial periods
if t == 1
if g.initial_status > 0
model[:eq_min_uptime][gi, 0] =
@constraint(mip, sum(switch_off[gi, i]
for i in 1:(g.min_uptime - g.initial_status) if i <= T) == 0)
model[:eq_min_uptime][gi, 0] = @constraint(
mip,
sum(
switch_off[gi, i] for
i in 1:(g.min_uptime-g.initial_status) if i <= T
) == 0
)
else
model[:eq_min_downtime][gi, 0] =
@constraint(mip, sum(switch_on[gi, i]
for i in 1:(g.min_downtime + g.initial_status) if i <= T) == 0)
model[:eq_min_downtime][gi, 0] = @constraint(
mip,
sum(
switch_on[gi, i] for
i in 1:(g.min_downtime+g.initial_status) if i <= T
) == 0
)
end
end
# Add to net injection expression
add_to_expression!(expr_net_injection[g.bus.name, t], prod_above[g.name, t], 1.0)
add_to_expression!(expr_net_injection[g.bus.name, t], is_on[g.name, t], g.min_power[t])
add_to_expression!(
expr_net_injection[g.bus.name, t],
prod_above[g.name, t],
1.0,
)
add_to_expression!(
expr_net_injection[g.bus.name, t],
is_on[g.name, t],
g.min_power[t],
)
# Add to reserves expression
add_to_expression!(expr_reserve[g.bus.name, t], reserve[gi, t], 1.0)
end
end
function _build_obj_function!(model::JuMP.Model)
@objective(model, Min, model[:obj])
end
function _build_net_injection_eqs!(model::JuMP.Model)
T = model[:instance].time
net_injection = model[:net_injection]
@ -412,45 +454,36 @@ function _build_net_injection_eqs!(model::JuMP.Model)
@constraint(model, n == model[:expr_net_injection][b.name, t])
end
for t in 1:T
model[:eq_power_balance][t] =
@constraint(
model,
sum(
net_injection[b.name, t]
for b in model[:instance].buses
) == 0
)
model[:eq_power_balance][t] = @constraint(
model,
sum(net_injection[b.name, t] for b in model[:instance].buses) == 0
)
end
end
function _build_reserve_eqs!(model::JuMP.Model)
reserves = model[:instance].reserves
for t in 1:model[:instance].time
model[:eq_min_reserve][t] =
@constraint(
model,
sum(
model[:expr_reserve][b.name, t]
for b in model[:instance].buses
) >= reserves.spinning[t]
)
model[:eq_min_reserve][t] = @constraint(
model,
sum(
model[:expr_reserve][b.name, t] for b in model[:instance].buses
) >= reserves.spinning[t]
)
end
end
function _enforce_transmission(
;
function _enforce_transmission(;
model::JuMP.Model,
violation::Violation,
isf::Matrix{Float64},
lodf::Matrix{Float64},
)::Nothing
instance = model[:instance]
instance = model[:instance]
limit::Float64 = 0.0
overflow = model[:overflow]
net_injection = model[:net_injection]
if violation.outage_line === nothing
limit = violation.monitored_line.normal_flow_limit[violation.time]
@info @sprintf(
@ -469,34 +502,42 @@ function _enforce_transmission(
violation.outage_line.name,
)
end
fm = violation.monitored_line.name
t = violation.time
flow = @variable(model, base_name="flow[$fm,$t]")
flow = @variable(model, base_name = "flow[$fm,$t]")
v = overflow[violation.monitored_line.name, violation.time]
@constraint(model, flow <= limit + v)
@constraint(model, flow <= limit + v)
@constraint(model, -flow <= limit + v)
if violation.outage_line === nothing
@constraint(model, flow == sum(net_injection[b.name, violation.time] *
isf[violation.monitored_line.offset, b.offset]
for b in instance.buses
if b.offset > 0))
@constraint(
model,
flow == sum(
net_injection[b.name, violation.time] *
isf[violation.monitored_line.offset, b.offset] for
b in instance.buses if b.offset > 0
)
)
else
@constraint(model, flow == sum(net_injection[b.name, violation.time] * (
isf[violation.monitored_line.offset, b.offset] + (
lodf[violation.monitored_line.offset, violation.outage_line.offset] *
isf[violation.outage_line.offset, b.offset]
)
)
for b in instance.buses
if b.offset > 0))
end
nothing
@constraint(
model,
flow == sum(
net_injection[b.name, violation.time] * (
isf[violation.monitored_line.offset, b.offset] + (
lodf[
violation.monitored_line.offset,
violation.outage_line.offset,
] * isf[violation.outage_line.offset, b.offset]
)
) for b in instance.buses if b.offset > 0
)
)
end
return nothing
end
function _set_names!(model::JuMP.Model)
@info "Setting variable and constraint names..."
time_varnames = @elapsed begin
@ -505,7 +546,6 @@ function _set_names!(model::JuMP.Model)
@info @sprintf("Set names in %.2f seconds", time_varnames)
end
function _set_names!(dict::Dict)
for name in keys(dict)
dict[name] isa AbstractDict || continue
@ -519,72 +559,75 @@ function _set_names!(dict::Dict)
end
end
function solution(model::JuMP.Model)
instance, T = model[:instance], model[:instance].time
function timeseries(vars, collection)
return OrderedDict(
b.name => [round(value(vars[b.name, t]), digits=5) for t in 1:T]
b.name => [round(value(vars[b.name, t]), digits = 5) for t in 1:T]
for b in collection
)
end
function production_cost(g)
return [
value(model[:is_on][g.name, t]) * g.min_power_cost[t] +
sum(
value(model[:is_on][g.name, t]) * g.min_power_cost[t] + sum(
Float64[
value(model[:segprod][g.name, t, k]) * g.cost_segments[k].cost[t]
for k in 1:length(g.cost_segments)
]
)
for t in 1:T
value(model[:segprod][g.name, t, k]) *
g.cost_segments[k].cost[t] for
k in 1:length(g.cost_segments)
],
) for t in 1:T
]
end
function production(g)
return [
value(model[:is_on][g.name, t]) * g.min_power[t] +
sum(
value(model[:is_on][g.name, t]) * g.min_power[t] + sum(
Float64[
value(model[:segprod][g.name, t, k])
for k in 1:length(g.cost_segments)
]
)
for t in 1:T
value(model[:segprod][g.name, t, k]) for
k in 1:length(g.cost_segments)
],
) for t in 1:T
]
end
function startup_cost(g)
S = length(g.startup_categories)
return [sum(g.startup_categories[s].cost * value(model[:startup][g.name, t, s])
for s in 1:S)
for t in 1:T]
return [
sum(
g.startup_categories[s].cost *
value(model[:startup][g.name, t, s]) for s in 1:S
) for t in 1:T
]
end
sol = OrderedDict()
sol["Production (MW)"] = OrderedDict(g.name => production(g) for g in instance.units)
sol["Production cost (\$)"] = OrderedDict(g.name => production_cost(g) for g in instance.units)
sol["Startup cost (\$)"] = OrderedDict(g.name => startup_cost(g) for g in instance.units)
sol["Production (MW)"] =
OrderedDict(g.name => production(g) for g in instance.units)
sol["Production cost (\$)"] =
OrderedDict(g.name => production_cost(g) for g in instance.units)
sol["Startup cost (\$)"] =
OrderedDict(g.name => startup_cost(g) for g in instance.units)
sol["Is on"] = timeseries(model[:is_on], instance.units)
sol["Switch on"] = timeseries(model[:switch_on], instance.units)
sol["Switch off"] = timeseries(model[:switch_off], instance.units)
sol["Reserve (MW)"] = timeseries(model[:reserve], instance.units)
sol["Net injection (MW)"] = timeseries(model[:net_injection], instance.buses)
sol["Net injection (MW)"] =
timeseries(model[:net_injection], instance.buses)
sol["Load curtail (MW)"] = timeseries(model[:curtail], instance.buses)
if !isempty(instance.lines)
sol["Line overflow (MW)"] = timeseries(model[:overflow], instance.lines)
end
if !isempty(instance.price_sensitive_loads)
sol["Price-sensitive loads (MW)"] = timeseries(model[:loads], instance.price_sensitive_loads)
sol["Price-sensitive loads (MW)"] =
timeseries(model[:loads], instance.price_sensitive_loads)
end
return sol
end
function write(filename::AbstractString, solution::AbstractDict)::Nothing
open(filename, "w") do file
JSON.print(file, solution, 2)
end
return JSON.print(file, solution, 2)
end
return
end
function fix!(model::JuMP.Model, solution::AbstractDict)::Nothing
instance, T = model[:instance], model[:instance].time
is_on = model[:is_on]
@ -593,20 +636,22 @@ function fix!(model::JuMP.Model, solution::AbstractDict)::Nothing
for g in instance.units
for t in 1:T
is_on_value = round(solution["Is on"][g.name][t])
production_value = round(solution["Production (MW)"][g.name][t], digits=5)
reserve_value = round(solution["Reserve (MW)"][g.name][t], digits=5)
JuMP.fix(is_on[g.name, t], is_on_value, force=true)
production_value =
round(solution["Production (MW)"][g.name][t], digits = 5)
reserve_value =
round(solution["Reserve (MW)"][g.name][t], digits = 5)
JuMP.fix(is_on[g.name, t], is_on_value, force = true)
JuMP.fix(
prod_above[g.name, t],
production_value - is_on_value * g.min_power[t],
force=true,
force = true,
)
JuMP.fix(reserve[g.name, t], reserve_value, force=true)
JuMP.fix(reserve[g.name, t], reserve_value, force = true)
end
end
return
end
function set_warm_start!(model::JuMP.Model, solution::AbstractDict)::Nothing
instance, T = model[:instance], model[:instance].time
is_on = model[:is_on]
@ -615,20 +660,25 @@ function set_warm_start!(model::JuMP.Model, solution::AbstractDict)::Nothing
for g in instance.units
for t in 1:T
JuMP.set_start_value(is_on[g.name, t], solution["Is on"][g.name][t])
JuMP.set_start_value(switch_on[g.name, t], solution["Switch on"][g.name][t])
JuMP.set_start_value(switch_off[g.name, t], solution["Switch off"][g.name][t])
JuMP.set_start_value(
switch_on[g.name, t],
solution["Switch on"][g.name][t],
)
JuMP.set_start_value(
switch_off[g.name, t],
solution["Switch off"][g.name][t],
)
end
end
return
end
function optimize!(
model::JuMP.Model;
time_limit=3600,
gap_limit=1e-4,
two_phase_gap=true,
time_limit = 3600,
gap_limit = 1e-4,
two_phase_gap = true,
)::Nothing
function set_gap(gap)
try
JuMP.set_optimizer_attribute(model, "MIPGap", gap)
@ -637,20 +687,20 @@ function optimize!(
@warn "Could not change MIP gap tolerance"
end
end
instance = model[:instance]
initial_time = time()
large_gap = false
has_transmission = (length(model[:isf]) > 0)
if has_transmission && two_phase_gap
set_gap(1e-2)
large_gap = true
else
set_gap(gap_limit)
end
while true
time_elapsed = time() - initial_time
time_remaining = time_limit - time_elapsed
@ -658,18 +708,21 @@ function optimize!(
@info "Time limit exceeded"
break
end
@info @sprintf("Setting MILP time limit to %.2f seconds", time_remaining)
@info @sprintf(
"Setting MILP time limit to %.2f seconds",
time_remaining
)
JuMP.set_time_limit_sec(model, time_remaining)
@info "Solving MILP..."
JuMP.optimize!(model)
has_transmission || break
violations = _find_violations(model)
if isempty(violations)
@info "No violations found"
@info "No violations found"
if large_gap
large_gap = false
set_gap(gap_limit)
@ -680,10 +733,9 @@ function optimize!(
_enforce_transmission(model, violations)
end
end
nothing
end
return
end
function _find_violations(model::JuMP.Model)
instance = model[:instance]
@ -695,36 +747,38 @@ function _find_violations(model::JuMP.Model)
time_screening = @elapsed begin
non_slack_buses = [b for b in instance.buses if b.offset > 0]
net_injection_values = [
value(net_injection[b.name, t])
for b in non_slack_buses, t in 1:instance.time
value(net_injection[b.name, t]) for b in non_slack_buses,
t in 1:instance.time
]
overflow_values = [
value(overflow[lm.name, t])
for lm in instance.lines, t in 1:instance.time
value(overflow[lm.name, t]) for lm in instance.lines,
t in 1:instance.time
]
violations = UnitCommitment._find_violations(
instance=instance,
net_injections=net_injection_values,
overflow=overflow_values,
isf=model[:isf],
lodf=model[:lodf],
instance = instance,
net_injections = net_injection_values,
overflow = overflow_values,
isf = model[:isf],
lodf = model[:lodf],
)
end
@info @sprintf("Verified transmission limits in %.2f seconds", time_screening)
@info @sprintf(
"Verified transmission limits in %.2f seconds",
time_screening
)
return violations
end
function _enforce_transmission(
model::JuMP.Model,
violations::Vector{Violation},
)::Nothing
for v in violations
_enforce_transmission(
model=model,
violation=v,
isf=model[:isf],
lodf=model[:lodf],
model = model,
violation = v,
isf = model[:isf],
lodf = model[:lodf],
)
end
return

@ -4,49 +4,44 @@
# Copyright (C) 2019 Argonne National Laboratory
# Written by Alinson Santos Xavier <axavier@anl.gov>
using DataStructures
using Base.Threads
struct Violation
time::Int
monitored_line::TransmissionLine
outage_line::Union{TransmissionLine, Nothing}
outage_line::Union{TransmissionLine,Nothing}
amount::Float64 # Violation amount (in MW)
end
function Violation(;
time::Int,
monitored_line::TransmissionLine,
outage_line::Union{TransmissionLine, Nothing},
amount::Float64,
)::Violation
time::Int,
monitored_line::TransmissionLine,
outage_line::Union{TransmissionLine,Nothing},
amount::Float64,
)::Violation
return Violation(time, monitored_line, outage_line, amount)
end
mutable struct ViolationFilter
max_per_line::Int
max_total::Int
queues::Dict{Int, PriorityQueue{Violation, Float64}}
queues::Dict{Int,PriorityQueue{Violation,Float64}}
end
function ViolationFilter(;
max_per_line::Int=1,
max_total::Int=5,
)::ViolationFilter
max_per_line::Int = 1,
max_total::Int = 5,
)::ViolationFilter
return ViolationFilter(max_per_line, max_total, Dict())
end
function _offer(filter::ViolationFilter, v::Violation)::Nothing
if v.monitored_line.offset keys(filter.queues)
filter.queues[v.monitored_line.offset] = PriorityQueue{Violation, Float64}()
filter.queues[v.monitored_line.offset] =
PriorityQueue{Violation,Float64}()
end
q::PriorityQueue{Violation, Float64} = filter.queues[v.monitored_line.offset]
q::PriorityQueue{Violation,Float64} = filter.queues[v.monitored_line.offset]
if length(q) < filter.max_per_line
enqueue!(q, v => v.amount)
else
@ -55,13 +50,12 @@ function _offer(filter::ViolationFilter, v::Violation)::Nothing
enqueue!(q, v => v.amount)
end
end
nothing
return nothing
end
function _query(filter::ViolationFilter)::Array{Violation, 1}
function _query(filter::ViolationFilter)::Array{Violation,1}
violations = Array{Violation,1}()
time_queue = PriorityQueue{Violation, Float64}()
time_queue = PriorityQueue{Violation,Float64}()
for l in keys(filter.queues)
line_queue = filter.queues[l]
while length(line_queue) > 0
@ -82,7 +76,6 @@ function _query(filter::ViolationFilter)::Array{Violation, 1}
return violations
end
"""
function _find_violations(
@ -104,49 +97,46 @@ UnitCommitment.line_outage_factors. The argument `overflow` specifies how much
flow above the transmission limits (in MW) is allowed. It should be an L x T
matrix, where L is the number of transmission lines.
"""
function _find_violations(
;
function _find_violations(;
instance::UnitCommitmentInstance,
net_injections::Array{Float64, 2},
overflow::Array{Float64, 2},
net_injections::Array{Float64,2},
overflow::Array{Float64,2},
isf::Array{Float64,2},
lodf::Array{Float64,2},
max_per_line::Int = 1,
max_per_period::Int = 5,
)::Array{Violation, 1}
)::Array{Violation,1}
B = length(instance.buses) - 1
L = length(instance.lines)
T = instance.time
K = nthreads()
size(net_injections) == (B, T) || error("net_injections has incorrect size")
size(isf) == (L, B) || error("isf has incorrect size")
size(lodf) == (L, L) || error("lodf has incorrect size")
filters = Dict(
t => ViolationFilter(
max_total=max_per_period,
max_per_line=max_per_line,
)
for t in 1:T
max_total = max_per_period,
max_per_line = max_per_line,
) for t in 1:T
)
pre_flow::Array{Float64} = zeros(L, K) # pre_flow[lm, thread]
post_flow::Array{Float64} = zeros(L, L, K) # post_flow[lm, lc, thread]
pre_v::Array{Float64} = zeros(L, K) # pre_v[lm, thread]
post_v::Array{Float64} = zeros(L, L, K) # post_v[lm, lc, thread]
normal_limits::Array{Float64,2} = [
l.normal_flow_limit[t] + overflow[l.offset, t]
for l in instance.lines, t in 1:T
l.normal_flow_limit[t] + overflow[l.offset, t] for
l in instance.lines, t in 1:T
]
emergency_limits::Array{Float64,2} = [
l.emergency_flow_limit[t] + overflow[l.offset, t]
for l in instance.lines, t in 1:T
l.emergency_flow_limit[t] + overflow[l.offset, t] for
l in instance.lines, t in 1:T
]
is_vulnerable::Array{Bool} = zeros(Bool, L)
for c in instance.contingencies
is_vulnerable[c.lines[1].offset] = true
@ -154,68 +144,69 @@ function _find_violations(
@threads for t in 1:T
k = threadid()
# Pre-contingency flows
pre_flow[:, k] = isf * net_injections[:, t]
# Post-contingency flows
for lc in 1:L, lm in 1:L
post_flow[lm, lc, k] = pre_flow[lm, k] + pre_flow[lc, k] * lodf[lm, lc]
post_flow[lm, lc, k] =
pre_flow[lm, k] + pre_flow[lc, k] * lodf[lm, lc]
end
# Pre-contingency violations
for lm in 1:L
pre_v[lm, k] = max(
0.0,
pre_flow[lm, k] - normal_limits[lm, t],
- pre_flow[lm, k] - normal_limits[lm, t],
-pre_flow[lm, k] - normal_limits[lm, t],
)
end
# Post-contingency violations
for lc in 1:L, lm in 1:L
post_v[lm, lc, k] = max(
0.0,
post_flow[lm, lc, k] - emergency_limits[lm, t],
- post_flow[lm, lc, k] - emergency_limits[lm, t],
-post_flow[lm, lc, k] - emergency_limits[lm, t],
)
end
# Offer pre-contingency violations
for lm in 1:L
if pre_v[lm, k] > 1e-5
_offer(
filters[t],
Violation(
time=t,
monitored_line=instance.lines[lm],
outage_line=nothing,
amount=pre_v[lm, k],
time = t,
monitored_line = instance.lines[lm],
outage_line = nothing,
amount = pre_v[lm, k],
),
)
end
end
# Offer post-contingency violations
for lm in 1:L, lc in 1:L
if post_v[lm, lc, k] > 1e-5 && is_vulnerable[lc]
_offer(
filters[t],
Violation(
time=t,
monitored_line=instance.lines[lm],
outage_line=instance.lines[lc],
amount=post_v[lm, lc, k],
time = t,
monitored_line = instance.lines[lm],
outage_line = instance.lines[lc],
amount = post_v[lm, lc, k],
),
)
end
end
end
violations = Violation[]
for t in 1:instance.time
append!(violations, _query(filters[t]))
end
return violations
end

@ -13,15 +13,17 @@ M[l.offset, b.offset] indicates the amount of power (in MW) that flows through
transmission line l when 1 MW of power is injected at the slack bus (the bus
that has offset zero) and withdrawn from b.
"""
function _injection_shift_factors(; buses::Array{Bus}, lines::Array{TransmissionLine})
function _injection_shift_factors(;
buses::Array{Bus},
lines::Array{TransmissionLine},
)
susceptance = _susceptance_matrix(lines)
incidence = _reduced_incidence_matrix(lines=lines, buses=buses)
incidence = _reduced_incidence_matrix(lines = lines, buses = buses)
laplacian = transpose(incidence) * susceptance * incidence
isf = susceptance * incidence * inv(Array(laplacian))
return isf
end
"""
_reduced_incidence_matrix(; buses::Array{Bus}, lines::Array{TransmissionLine})
@ -31,7 +33,10 @@ is the number of buses and L is the number of lines. For each row, there is a 1
element and a -1 element, indicating the source and target buses, respectively,
for that line.
"""
function _reduced_incidence_matrix(; buses::Array{Bus}, lines::Array{TransmissionLine})
function _reduced_incidence_matrix(;
buses::Array{Bus},
lines::Array{TransmissionLine},
)
matrix = spzeros(Float64, length(lines), length(buses) - 1)
for line in lines
if line.source.offset > 0
@ -41,7 +46,7 @@ function _reduced_incidence_matrix(; buses::Array{Bus}, lines::Array{Transmissio
matrix[line.offset, line.target.offset] = -1
end
end
matrix
return matrix
end
"""
@ -54,7 +59,6 @@ function _susceptance_matrix(lines::Array{TransmissionLine})
return Diagonal([l.susceptance for l in lines])
end
"""
_line_outage_factors(; buses, lines, isf)
@ -63,19 +67,13 @@ Returns a LxL matrix containing the Line Outage Distribution Factors (LODFs)
for the given network. This matrix how does the pre-contingency flow change
when each individual transmission line is removed.
"""
function _line_outage_factors(
;
buses::Array{Bus, 1},
lines::Array{TransmissionLine, 1},
function _line_outage_factors(;
buses::Array{Bus,1},
lines::Array{TransmissionLine,1},
isf::Array{Float64,2},
) :: Array{Float64,2}
)::Array{Float64,2}
n_lines, n_buses = size(isf)
incidence = Array(
_reduced_incidence_matrix(
lines=lines,
buses=buses,
),
)
incidence = Array(_reduced_incidence_matrix(lines = lines, buses = buses))
lodf::Array{Float64,2} = isf * transpose(incidence)
m, n = size(lodf)
for i in 1:n

@ -10,17 +10,11 @@ using JuMP
using MathOptInterface
using SparseArrays
pkg = [
:DataStructures,
:JSON,
:JuMP,
:MathOptInterface,
:SparseArrays,
]
pkg = [:DataStructures, :JSON, :JuMP, :MathOptInterface, :SparseArrays]
@info "Building system image..."
create_sysimage(
pkg,
precompile_statements_file="build/precompile.jl",
sysimage_path="build/sysimage.so",
precompile_statements_file = "build/precompile.jl",
sysimage_path = "build/sysimage.so",
)

@ -18,9 +18,9 @@ Returns the number of validation errors found.
"""
function repair!(instance::UnitCommitmentInstance)::Int
n_errors = 0
for g in instance.units
# Startup costs and delays must be increasing
for s in 2:length(g.startup_categories)
if g.startup_categories[s].delay <= g.startup_categories[s-1].delay
@ -31,7 +31,7 @@ function repair!(instance::UnitCommitmentInstance)::Int
g.startup_categories[s].delay = new_value
n_errors += 1
end
if g.startup_categories[s].cost < g.startup_categories[s-1].cost
prev_value = g.startup_categories[s].cost
new_value = g.startup_categories[s-1].cost
@ -40,9 +40,8 @@ function repair!(instance::UnitCommitmentInstance)::Int
g.startup_categories[s].cost = new_value
n_errors += 1
end
end
for t in 1:instance.time
# Production cost curve should be convex
for k in 2:length(g.cost_segments)
@ -67,19 +66,16 @@ function repair!(instance::UnitCommitmentInstance)::Int
end
end
end
return n_errors
end
function validate(instance_filename::String, solution_filename::String)
instance = UnitCommitment.read(instance_filename)
solution = JSON.parse(open(solution_filename))
return validate(instance, solution)
end
"""
validate(instance, solution)::Bool
@ -92,38 +88,39 @@ This function is implemented independently from the optimization model in
producing valid solutions. It can also be used to verify the solutions produced
by other optimization packages.
"""
function validate(instance::UnitCommitmentInstance,
solution::Union{Dict,OrderedDict};
)::Bool
function validate(
instance::UnitCommitmentInstance,
solution::Union{Dict,OrderedDict},
)::Bool
err_count = 0
err_count += _validate_units(instance, solution)
err_count += _validate_reserve_and_demand(instance, solution)
if err_count > 0
@error "Found $err_count validation errors"
return false
end
return true
end
function _validate_units(instance, solution; tol=0.01)
function _validate_units(instance, solution; tol = 0.01)
err_count = 0
for unit in instance.units
production = solution["Production (MW)"][unit.name]
reserve = solution["Reserve (MW)"][unit.name]
actual_production_cost = solution["Production cost (\$)"][unit.name]
actual_startup_cost = solution["Startup cost (\$)"][unit.name]
is_on = bin(solution["Is on"][unit.name])
for t in 1:instance.time
# Auxiliary variables
if t == 1
is_starting_up = (unit.initial_status < 0) && is_on[t]
is_shutting_down = (unit.initial_status > 0) && !is_on[t]
ramp_up = max(0, production[t] + reserve[t] - unit.initial_power)
ramp_up =
max(0, production[t] + reserve[t] - unit.initial_power)
ramp_down = max(0, unit.initial_power - production[t])
else
is_starting_up = !is_on[t-1] && is_on[t]
@ -131,7 +128,7 @@ function _validate_units(instance, solution; tol=0.01)
ramp_up = max(0, production[t] + reserve[t] - production[t-1])
ramp_down = max(0, production[t-1] - production[t])
end
# Compute production costs
production_cost, startup_cost = 0, 0
if is_on[t]
@ -143,84 +140,133 @@ function _validate_units(instance, solution; tol=0.01)
residual = max(0, residual - s.mw[t])
end
end
# Production should be non-negative
if production[t] < -tol
@error @sprintf("Unit %s produces negative amount of power at time %d (%.2f)",
unit.name, t, production[t])
@error @sprintf(
"Unit %s produces negative amount of power at time %d (%.2f)",
unit.name,
t,
production[t]
)
err_count += 1
end
# Verify must-run
if !is_on[t] && unit.must_run[t]
@error @sprintf("Must-run unit %s is offline at time %d",
unit.name, t)
@error @sprintf(
"Must-run unit %s is offline at time %d",
unit.name,
t
)
err_count += 1
end
# Verify reserve eligibility
if !unit.provides_spinning_reserves[t] && reserve[t] > tol
@error @sprintf("Unit %s is not eligible to provide spinning reserves at time %d",
unit.name, t)
@error @sprintf(
"Unit %s is not eligible to provide spinning reserves at time %d",
unit.name,
t
)
err_count += 1
end
# If unit is on, must produce at least its minimum power
if is_on[t] && (production[t] < unit.min_power[t] - tol)
@error @sprintf("Unit %s produces below its minimum limit at time %d (%.2f < %.2f)",
unit.name, t, production[t], unit.min_power[t])
@error @sprintf(
"Unit %s produces below its minimum limit at time %d (%.2f < %.2f)",
unit.name,
t,
production[t],
unit.min_power[t]
)
err_count += 1
end
# If unit is on, must produce at most its maximum power
if is_on[t] && (production[t] + reserve[t] > unit.max_power[t] + tol)
@error @sprintf("Unit %s produces above its maximum limit at time %d (%.2f + %.2f> %.2f)",
unit.name, t, production[t], reserve[t], unit.max_power[t])
if is_on[t] &&
(production[t] + reserve[t] > unit.max_power[t] + tol)
@error @sprintf(
"Unit %s produces above its maximum limit at time %d (%.2f + %.2f> %.2f)",
unit.name,
t,
production[t],
reserve[t],
unit.max_power[t]
)
err_count += 1
end
# If unit is off, must produce zero
if !is_on[t] && production[t] + reserve[t] > tol
@error @sprintf("Unit %s produces power at time %d while off",
unit.name, t)
@error @sprintf(
"Unit %s produces power at time %d while off",
unit.name,
t
)
err_count += 1
end
# Startup limit
if is_starting_up && (ramp_up > unit.startup_limit + tol)
@error @sprintf("Unit %s exceeds startup limit at time %d (%.2f > %.2f)",
unit.name, t, ramp_up, unit.startup_limit)
@error @sprintf(
"Unit %s exceeds startup limit at time %d (%.2f > %.2f)",
unit.name,
t,
ramp_up,
unit.startup_limit
)
err_count += 1
end
# Shutdown limit
if is_shutting_down && (ramp_down > unit.shutdown_limit + tol)
@error @sprintf("Unit %s exceeds shutdown limit at time %d (%.2f > %.2f)",
unit.name, t, ramp_down, unit.shutdown_limit)
@error @sprintf(
"Unit %s exceeds shutdown limit at time %d (%.2f > %.2f)",
unit.name,
t,
ramp_down,
unit.shutdown_limit
)
err_count += 1
end
# Ramp-up limit
if !is_starting_up && !is_shutting_down && (ramp_up > unit.ramp_up_limit + tol)
@error @sprintf("Unit %s exceeds ramp up limit at time %d (%.2f > %.2f)",
unit.name, t, ramp_up, unit.ramp_up_limit)
if !is_starting_up &&
!is_shutting_down &&
(ramp_up > unit.ramp_up_limit + tol)
@error @sprintf(
"Unit %s exceeds ramp up limit at time %d (%.2f > %.2f)",
unit.name,
t,
ramp_up,
unit.ramp_up_limit
)
err_count += 1
end
# Ramp-down limit
if !is_starting_up && !is_shutting_down && (ramp_down > unit.ramp_down_limit + tol)
@error @sprintf("Unit %s exceeds ramp down limit at time %d (%.2f > %.2f)",
unit.name, t, ramp_down, unit.ramp_down_limit)
if !is_starting_up &&
!is_shutting_down &&
(ramp_down > unit.ramp_down_limit + tol)
@error @sprintf(
"Unit %s exceeds ramp down limit at time %d (%.2f > %.2f)",
unit.name,
t,
ramp_down,
unit.ramp_down_limit
)
err_count += 1
end
# Verify startup costs & minimum downtime
if is_starting_up
# Calculate how much time the unit has been offline
time_down = 0
for k in 1:(t-1)
if !is_on[t - k]
if !is_on[t-k]
time_down += 1
else
break
@ -233,29 +279,32 @@ function _validate_units(instance, solution; tol=0.01)
end
time_down += initial_down
end
# Calculate startup costs
for c in unit.startup_categories
if time_down >= c.delay
startup_cost = c.cost
end
end
# Check minimum downtime
if time_down < unit.min_downtime
@error @sprintf("Unit %s violates minimum downtime at time %d",
unit.name, t)
@error @sprintf(
"Unit %s violates minimum downtime at time %d",
unit.name,
t
)
err_count += 1
end
end
# Verify minimum uptime
if is_shutting_down
# Calculate how much time the unit has been online
time_up = 0
for k in 1:(t-1)
if is_on[t - k]
if is_on[t-k]
time_up += 1
else
break
@ -268,61 +317,70 @@ function _validate_units(instance, solution; tol=0.01)
end
time_up += initial_up
end
if (t == time_up + 1) && (unit.initial_status > 0)
time_up += unit.initial_status
end
# Check minimum uptime
if time_up < unit.min_uptime
@error @sprintf("Unit %s violates minimum uptime at time %d",
unit.name, t)
@error @sprintf(
"Unit %s violates minimum uptime at time %d",
unit.name,
t
)
err_count += 1
end
end
# Verify production costs
if abs(actual_production_cost[t] - production_cost) > 1.00
@error @sprintf("Unit %s has unexpected production cost at time %d (%.2f should be %.2f)",
unit.name, t, actual_production_cost[t], production_cost)
@error @sprintf(
"Unit %s has unexpected production cost at time %d (%.2f should be %.2f)",
unit.name,
t,
actual_production_cost[t],
production_cost
)
err_count += 1
end
# Verify startup costs
if abs(actual_startup_cost[t] - startup_cost) > 1.00
@error @sprintf("Unit %s has unexpected startup cost at time %d (%.2f should be %.2f)",
unit.name, t, actual_startup_cost[t], startup_cost)
@error @sprintf(
"Unit %s has unexpected startup cost at time %d (%.2f should be %.2f)",
unit.name,
t,
actual_startup_cost[t],
startup_cost
)
err_count += 1
end
end
end
return err_count
end
function _validate_reserve_and_demand(instance, solution, tol=0.01)
function _validate_reserve_and_demand(instance, solution, tol = 0.01)
err_count = 0
for t in 1:instance.time
load_curtail = 0
fixed_load = sum(b.load[t] for b in instance.buses)
ps_load = sum(
solution["Price-sensitive loads (MW)"][ps.name][t]
for ps in instance.price_sensitive_loads
)
production = sum(
solution["Production (MW)"][g.name][t]
for g in instance.units
solution["Price-sensitive loads (MW)"][ps.name][t] for
ps in instance.price_sensitive_loads
)
production =
sum(solution["Production (MW)"][g.name][t] for g in instance.units)
if "Load curtail (MW)" in keys(solution)
load_curtail = sum(
solution["Load curtail (MW)"][b.name][t]
for b in instance.buses
solution["Load curtail (MW)"][b.name][t] for
b in instance.buses
)
end
balance = fixed_load - load_curtail - production + ps_load
# Verify that production equals demand
if abs(balance) > tol
@error @sprintf(
@ -335,9 +393,10 @@ function _validate_reserve_and_demand(instance, solution, tol=0.01)
)
err_count += 1
end
# Verify spinning reserves
reserve = sum(solution["Reserve (MW)"][g.name][t] for g in instance.units)
reserve =
sum(solution["Reserve (MW)"][g.name][t] for g in instance.units)
if reserve < instance.reserves.spinning[t] - tol
@error @sprintf(
"Insufficient spinning reserves at time %d (%.2f should be %.2f)",
@ -348,7 +407,6 @@ function _validate_reserve_and_demand(instance, solution, tol=0.01)
err_count += 1
end
end
return err_count
end

@ -6,14 +6,17 @@ using UnitCommitment
@testset "convert" begin
@testset "EGRET solution" begin
solution = UnitCommitment._read_egret_solution("fixtures/egret_output.json.gz")
solution =
UnitCommitment._read_egret_solution("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 length(solution[attr]["115_STEAM_1"]) == 48
end
@test solution["Production cost (\$)"]["315_CT_6"][15:20] == [0., 0., 884.44, 1470.71, 1470.71, 884.44]
@test solution["Startup cost (\$)"]["315_CT_6"][15:20] == [0., 0., 5665.23, 0., 0., 0.]
@test solution["Production cost (\$)"]["315_CT_6"][15:20] ==
[0.0, 0.0, 884.44, 1470.71, 1470.71, 884.44]
@test solution["Startup cost (\$)"]["315_CT_6"][15:20] ==
[0.0, 0.0, 5665.23, 0.0, 0.0, 0.0]
@test length(keys(solution["Is on"])) == 154
end
end

@ -8,21 +8,21 @@ using UnitCommitment, Cbc, JuMP
# Load instance
instance = UnitCommitment.read("$(pwd())/fixtures/case118-initcond.json.gz")
optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
# All units should have unknown initial conditions
for g in instance.units
@test g.initial_power === nothing
@test g.initial_status === nothing
end
# Generate initial conditions
UnitCommitment.generate_initial_conditions!(instance, optimizer)
# All units should now have known initial conditions
for g in instance.units
@test g.initial_power !== nothing
@test g.initial_status !== nothing
end
# TODO: Check that initial conditions are feasible
end

@ -15,46 +15,46 @@ using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
@test length(instance.price_sensitive_loads) == 1
@test instance.time == 4
@test instance.lines[5].name == "l5"
@test instance.lines[5].source.name == "b2"
@test instance.lines[5].target.name == "b5"
@test instance.lines[5].reactance 0.17388
@test instance.lines[5].susceptance 10.037550333
@test instance.lines[5].normal_flow_limit == [1e8 for t in 1:4]
@test instance.lines[5].name == "l5"
@test instance.lines[5].source.name == "b2"
@test instance.lines[5].target.name == "b5"
@test instance.lines[5].reactance 0.17388
@test instance.lines[5].susceptance 10.037550333
@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[1].name == "l1"
@test instance.lines[1].source.name == "b1"
@test instance.lines[1].target.name == "b2"
@test instance.lines[1].reactance 0.059170
@test instance.lines[1].susceptance 29.496860773945
@test instance.lines[1].normal_flow_limit == [300.0 for t in 1:4]
@test instance.lines[5].flow_limit_penalty == [5e3 for t in 1:4]
@test instance.lines[1].name == "l1"
@test instance.lines[1].source.name == "b1"
@test instance.lines[1].target.name == "b2"
@test instance.lines[1].reactance 0.059170
@test instance.lines[1].susceptance 29.496860773945
@test instance.lines[1].normal_flow_limit == [300.0 for t in 1:4]
@test instance.lines[1].emergency_flow_limit == [400.0 for t in 1:4]
@test instance.lines[1].flow_limit_penalty == [1e3 for t in 1:4]
@test instance.lines[1].flow_limit_penalty == [1e3 for t in 1:4]
@test instance.buses[9].name == "b9"
@test instance.buses[9].load == [35.36638, 33.25495, 31.67138, 31.14353]
unit = instance.units[1]
@test unit.name == "g1"
@test unit.bus.name == "b1"
@test unit.ramp_up_limit == 1e6
@test unit.ramp_down_limit == 1e6
@test unit.startup_limit == 1e6
@test unit.shutdown_limit == 1e6
@test unit.must_run == [false for t in 1:4]
@test unit.min_power_cost == [1400. for t in 1:4]
@test unit.min_uptime == 1
@test unit.min_downtime == 1
@test unit.provides_spinning_reserves == [true for t in 1:4]
@test unit.name == "g1"
@test unit.bus.name == "b1"
@test unit.ramp_up_limit == 1e6
@test unit.ramp_down_limit == 1e6
@test unit.startup_limit == 1e6
@test unit.shutdown_limit == 1e6
@test unit.must_run == [false for t in 1:4]
@test unit.min_power_cost == [1400.0 for t in 1:4]
@test unit.min_uptime == 1
@test unit.min_downtime == 1
@test unit.provides_spinning_reserves == [true for t in 1:4]
for t in 1:1
@test unit.cost_segments[1].mw[t] == 10.0
@test unit.cost_segments[2].mw[t] == 20.0
@test unit.cost_segments[3].mw[t] == 5.0
@test unit.cost_segments[1].cost[t] 20.0
@test unit.cost_segments[2].cost[t] 30.0
@test unit.cost_segments[3].cost[t] 40.0
@test unit.cost_segments[1].mw[t] == 10.0
@test unit.cost_segments[2].mw[t] == 20.0
@test unit.cost_segments[3].mw[t] == 5.0
@test unit.cost_segments[1].cost[t] 20.0
@test unit.cost_segments[2].cost[t] 30.0
@test unit.cost_segments[3].cost[t] 40.0
end
@test length(unit.startup_categories) == 3
@test unit.startup_categories[1].delay == 1
@ -63,42 +63,42 @@ 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
unit = instance.units[2]
@test unit.name == "g2"
@test unit.name == "g2"
@test unit.must_run == [false for t in 1:4]
unit = instance.units[3]
@test unit.name == "g3"
@test unit.bus.name == "b3"
@test unit.ramp_up_limit == 70.0
@test unit.ramp_down_limit == 70.0
@test unit.startup_limit == 70.0
@test unit.shutdown_limit == 70.0
@test unit.must_run == [true for t in 1:4]
@test unit.min_power_cost == [0. for t in 1:4]
@test unit.min_uptime == 1
@test unit.min_downtime == 1
@test unit.provides_spinning_reserves == [true for t in 1:4]
@test unit.name == "g3"
@test unit.bus.name == "b3"
@test unit.ramp_up_limit == 70.0
@test unit.ramp_down_limit == 70.0
@test unit.startup_limit == 70.0
@test unit.shutdown_limit == 70.0
@test unit.must_run == [true for t in 1:4]
@test unit.min_power_cost == [0.0 for t in 1:4]
@test unit.min_uptime == 1
@test unit.min_downtime == 1
@test unit.provides_spinning_reserves == [true for t in 1:4]
for t in 1:4
@test unit.cost_segments[1].mw[t] 33
@test unit.cost_segments[2].mw[t] 33
@test unit.cost_segments[3].mw[t] 34
@test unit.cost_segments[1].mw[t] 33
@test unit.cost_segments[2].mw[t] 33
@test unit.cost_segments[3].mw[t] 34
@test unit.cost_segments[1].cost[t] 33.75
@test unit.cost_segments[2].cost[t] 38.04
@test unit.cost_segments[3].cost[t] 44.77853
end
@test instance.reserves.spinning == zeros(4)
@test instance.contingencies[1].lines == [instance.lines[1]]
@test instance.contingencies[1].units == []
load = instance.price_sensitive_loads[1]
@test load.name == "ps1"
@test load.name == "ps1"
@test load.bus.name == "b3"
@test load.revenue == [100. for t in 1:4]
@test load.demand == [50. for t in 1:4]
@test load.revenue == [100.0 for t in 1:4]
@test load.demand == [50.0 for t in 1:4]
end
@testset "read sub-hourly" begin
@ -114,11 +114,11 @@ using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
@test unit.startup_categories[3].delay == 6
@test unit.initial_status == -200
end
@testset "slice" begin
instance = UnitCommitment.read_benchmark("test/case14")
modified = UnitCommitment.slice(instance, 1:2)
# Should update all time-dependent fields
@test modified.time == 2
@test length(modified.power_balance_penalty) == 2
@ -146,11 +146,13 @@ using UnitCommitment, LinearAlgebra, Cbc, JuMP, JSON, GZip
@test length(ps.demand) == 2
@test length(ps.revenue) == 2
end
# Should be able to build model without errors
optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
model = build_model(instance=modified,
optimizer=optimizer,
variable_names=true)
model = build_model(
instance = modified,
optimizer = optimizer,
variable_names = true,
)
end
end

@ -12,9 +12,9 @@ using UnitCommitment, LinearAlgebra, Cbc, JuMP
end
optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
model = build_model(
instance=instance,
optimizer=optimizer,
variable_names=true,
instance = instance,
optimizer = optimizer,
variable_names = true,
)
@test name(model[:is_on]["g1", 1]) == "is_on[g1,1]"
@ -27,7 +27,7 @@ using UnitCommitment, LinearAlgebra, Cbc, JuMP
UnitCommitment.write(filename, solution)
loaded = JSON.parsefile(filename)
@test length(loaded["Is on"]) == 6
# Verify solution
@test UnitCommitment.validate(instance, solution)

@ -8,81 +8,81 @@ import UnitCommitment: Violation, _offer, _query
@testset "Screening" begin
@testset "Violation filter" begin
instance = UnitCommitment.read_benchmark("test/case14")
filter = UnitCommitment.ViolationFilter(max_per_line=1, max_total=2)
filter = UnitCommitment.ViolationFilter(max_per_line = 1, max_total = 2)
_offer(
filter,
Violation(
time=1,
monitored_line=instance.lines[1],
outage_line=nothing,
amount=100.,
time = 1,
monitored_line = instance.lines[1],
outage_line = nothing,
amount = 100.0,
),
)
_offer(
filter,
Violation(
time=1,
monitored_line=instance.lines[1],
outage_line=instance.lines[1],
amount=300.,
time = 1,
monitored_line = instance.lines[1],
outage_line = instance.lines[1],
amount = 300.0,
),
)
_offer(
filter,
Violation(
time=1,
monitored_line=instance.lines[1],
outage_line=instance.lines[5],
amount=500.,
time = 1,
monitored_line = instance.lines[1],
outage_line = instance.lines[5],
amount = 500.0,
),
)
_offer(
filter,
Violation(
time=1,
monitored_line=instance.lines[1],
outage_line=instance.lines[4],
amount=400.,
time = 1,
monitored_line = instance.lines[1],
outage_line = instance.lines[4],
amount = 400.0,
),
)
_offer(
filter,
Violation(
time=1,
monitored_line=instance.lines[2],
outage_line=instance.lines[1],
amount=200.,
time = 1,
monitored_line = instance.lines[2],
outage_line = instance.lines[1],
amount = 200.0,
),
)
_offer(
filter,
Violation(
time=1,
monitored_line=instance.lines[2],
outage_line=instance.lines[8],
amount=100.,
)
time = 1,
monitored_line = instance.lines[2],
outage_line = instance.lines[8],
amount = 100.0,
),
)
actual = _query(filter)
expected = [
Violation(
time=1,
monitored_line=instance.lines[2],
outage_line=instance.lines[1],
amount=200.,
time = 1,
monitored_line = instance.lines[2],
outage_line = instance.lines[1],
amount = 200.0,
),
Violation(
time=1,
monitored_line=instance.lines[1],
outage_line=instance.lines[5],
amount=500.,
time = 1,
monitored_line = instance.lines[1],
outage_line = instance.lines[5],
amount = 500.0,
),
]
@test actual == expected
end
@testset "find_violations" begin
instance = UnitCommitment.read_benchmark("test/case14")
for line in instance.lines, t in 1:instance.time
@ -90,22 +90,22 @@ import UnitCommitment: Violation, _offer, _query
line.emergency_flow_limit[t] = 1.0
end
isf = UnitCommitment._injection_shift_factors(
lines=instance.lines,
buses=instance.buses,
lines = instance.lines,
buses = instance.buses,
)
lodf = UnitCommitment._line_outage_factors(
lines=instance.lines,
buses=instance.buses,
isf=isf,
lines = instance.lines,
buses = instance.buses,
isf = isf,
)
inj = [1000.0 for b in 1:13, t in 1:instance.time]
overflow = [0.0 for l in instance.lines, t in 1:instance.time]
violations = UnitCommitment._find_violations(
instance=instance,
net_injections=inj,
overflow=overflow,
isf=isf,
lodf=lodf,
instance = instance,
net_injections = inj,
overflow = overflow,
isf = isf,
lodf = lodf,
)
@test length(violations) == 20
end

@ -9,117 +9,137 @@ using UnitCommitment, Test, LinearAlgebra
instance = UnitCommitment.read_benchmark("test/case14")
actual = UnitCommitment._susceptance_matrix(instance.lines)
@test size(actual) == (20, 20)
expected = Diagonal([29.5, 7.83, 8.82, 9.9, 10.04,
10.2, 41.45, 8.35, 3.14, 6.93,
8.77, 6.82, 13.4, 9.91, 15.87,
20.65, 6.46, 9.09, 8.73, 5.02])
@test round.(actual, digits=2) == expected
expected = Diagonal([
29.5,
7.83,
8.82,
9.9,
10.04,
10.2,
41.45,
8.35,
3.14,
6.93,
8.77,
6.82,
13.4,
9.91,
15.87,
20.65,
6.46,
9.09,
8.73,
5.02,
])
@test round.(actual, digits = 2) == expected
end
@testset "Reduced incidence matrix" begin
instance = UnitCommitment.read_benchmark("test/case14")
actual = UnitCommitment._reduced_incidence_matrix(
lines=instance.lines,
buses=instance.buses,
lines = instance.lines,
buses = instance.buses,
)
@test size(actual) == (20, 13)
@test actual[1, 1] == -1.0
@test actual[3, 1] == 1.0
@test actual[4, 1] == 1.0
@test actual[5, 1] == 1.0
@test actual[3, 2] == -1.0
@test actual[6, 2] == 1.0
@test actual[4, 3] == -1.0
@test actual[6, 3] == -1.0
@test actual[7, 3] == 1.0
@test actual[8, 3] == 1.0
@test actual[9, 3] == 1.0
@test actual[2, 4] == -1.0
@test actual[5, 4] == -1.0
@test actual[7, 4] == -1.0
@test actual[10, 4] == 1.0
@test actual[10, 5] == -1.0
@test actual[11, 5] == 1.0
@test actual[12, 5] == 1.0
@test actual[13, 5] == 1.0
@test actual[8, 6] == -1.0
@test actual[14, 6] == 1.0
@test actual[15, 6] == 1.0
@test actual[14, 7] == -1.0
@test actual[9, 8] == -1.0
@test actual[15, 8] == -1.0
@test actual[16, 8] == 1.0
@test actual[17, 8] == 1.0
@test actual[16, 9] == -1.0
@test actual[18, 9] == 1.0
@test actual[11, 10] == -1.0
@test actual[18, 10] == -1.0
@test actual[12, 11] == -1.0
@test actual[19, 11] == 1.0
@test actual[13, 12] == -1.0
@test actual[19, 12] == -1.0
@test actual[20, 12] == 1.0
@test actual[17, 13] == -1.0
@test actual[20, 13] == -1.0
@test actual[1, 1] == -1.0
@test actual[3, 1] == 1.0
@test actual[4, 1] == 1.0
@test actual[5, 1] == 1.0
@test actual[3, 2] == -1.0
@test actual[6, 2] == 1.0
@test actual[4, 3] == -1.0
@test actual[6, 3] == -1.0
@test actual[7, 3] == 1.0
@test actual[8, 3] == 1.0
@test actual[9, 3] == 1.0
@test actual[2, 4] == -1.0
@test actual[5, 4] == -1.0
@test actual[7, 4] == -1.0
@test actual[10, 4] == 1.0
@test actual[10, 5] == -1.0
@test actual[11, 5] == 1.0
@test actual[12, 5] == 1.0
@test actual[13, 5] == 1.0
@test actual[8, 6] == -1.0
@test actual[14, 6] == 1.0
@test actual[15, 6] == 1.0
@test actual[14, 7] == -1.0
@test actual[9, 8] == -1.0
@test actual[15, 8] == -1.0
@test actual[16, 8] == 1.0
@test actual[17, 8] == 1.0
@test actual[16, 9] == -1.0
@test actual[18, 9] == 1.0
@test actual[11, 10] == -1.0
@test actual[18, 10] == -1.0
@test actual[12, 11] == -1.0
@test actual[19, 11] == 1.0
@test actual[13, 12] == -1.0
@test actual[19, 12] == -1.0
@test actual[20, 12] == 1.0
@test actual[17, 13] == -1.0
@test actual[20, 13] == -1.0
end
@testset "Injection Shift Factors (ISF)" begin
instance = UnitCommitment.read_benchmark("test/case14")
actual = UnitCommitment._injection_shift_factors(
lines=instance.lines,
buses=instance.buses,
lines = instance.lines,
buses = instance.buses,
)
@test size(actual) == (20, 13)
@test round.(actual, digits=2) == [
-0.84 -0.75 -0.67 -0.61 -0.63 -0.66 -0.66 -0.65 -0.65 -0.64 -0.63 -0.63 -0.64;
-0.16 -0.25 -0.33 -0.39 -0.37 -0.34 -0.34 -0.35 -0.35 -0.36 -0.37 -0.37 -0.36;
0.03 -0.53 -0.15 -0.1 -0.12 -0.14 -0.14 -0.14 -0.13 -0.13 -0.12 -0.12 -0.13;
0.06 -0.14 -0.32 -0.22 -0.25 -0.3 -0.3 -0.29 -0.28 -0.27 -0.25 -0.26 -0.27;
0.08 -0.07 -0.2 -0.29 -0.26 -0.22 -0.22 -0.22 -0.23 -0.25 -0.26 -0.26 -0.24;
0.03 0.47 -0.15 -0.1 -0.12 -0.14 -0.14 -0.14 -0.13 -0.13 -0.12 -0.12 -0.13;
0.08 0.31 0.5 -0.3 -0.03 0.36 0.36 0.28 0.23 0.1 -0.0 0.02 0.17;
0.0 0.01 0.02 -0.01 -0.22 -0.63 -0.63 -0.45 -0.41 -0.32 -0.24 -0.25 -0.36;
0.0 0.01 0.01 -0.01 -0.12 -0.17 -0.17 -0.26 -0.24 -0.18 -0.14 -0.14 -0.21;
-0.0 -0.02 -0.03 0.02 -0.66 -0.2 -0.2 -0.29 -0.36 -0.5 -0.63 -0.61 -0.43;
-0.0 -0.01 -0.02 0.01 0.21 -0.12 -0.12 -0.17 -0.28 -0.53 0.18 0.15 -0.03;
-0.0 -0.0 -0.0 0.0 0.03 -0.02 -0.02 -0.03 -0.02 0.01 -0.52 -0.17 -0.09;
-0.0 -0.01 -0.01 0.01 0.11 -0.06 -0.06 -0.09 -0.05 0.02 -0.28 -0.59 -0.31;
-0.0 -0.0 -0.0 -0.0 -0.0 -0.0 -1.0 -0.0 -0.0 -0.0 -0.0 -0.0 0.0 ;
0.0 0.01 0.02 -0.01 -0.22 0.37 0.37 -0.45 -0.41 -0.32 -0.24 -0.25 -0.36;
0.0 0.01 0.02 -0.01 -0.21 0.12 0.12 0.17 -0.72 -0.47 -0.18 -0.15 0.03;
0.0 0.01 0.01 -0.01 -0.14 0.08 0.08 0.12 0.07 -0.03 -0.2 -0.24 -0.6 ;
0.0 0.01 0.02 -0.01 -0.21 0.12 0.12 0.17 0.28 -0.47 -0.18 -0.15 0.03;
-0.0 -0.0 -0.0 0.0 0.03 -0.02 -0.02 -0.03 -0.02 0.01 0.48 -0.17 -0.09;
-0.0 -0.01 -0.01 0.01 0.14 -0.08 -0.08 -0.12 -0.07 0.03 0.2 0.24 -0.4 ]
@test round.(actual, digits = 2) == [
-0.84 -0.75 -0.67 -0.61 -0.63 -0.66 -0.66 -0.65 -0.65 -0.64 -0.63 -0.63 -0.64
-0.16 -0.25 -0.33 -0.39 -0.37 -0.34 -0.34 -0.35 -0.35 -0.36 -0.37 -0.37 -0.36
0.03 -0.53 -0.15 -0.1 -0.12 -0.14 -0.14 -0.14 -0.13 -0.13 -0.12 -0.12 -0.13
0.06 -0.14 -0.32 -0.22 -0.25 -0.3 -0.3 -0.29 -0.28 -0.27 -0.25 -0.26 -0.27
0.08 -0.07 -0.2 -0.29 -0.26 -0.22 -0.22 -0.22 -0.23 -0.25 -0.26 -0.26 -0.24
0.03 0.47 -0.15 -0.1 -0.12 -0.14 -0.14 -0.14 -0.13 -0.13 -0.12 -0.12 -0.13
0.08 0.31 0.5 -0.3 -0.03 0.36 0.36 0.28 0.23 0.1 -0.0 0.02 0.17
0.0 0.01 0.02 -0.01 -0.22 -0.63 -0.63 -0.45 -0.41 -0.32 -0.24 -0.25 -0.36
0.0 0.01 0.01 -0.01 -0.12 -0.17 -0.17 -0.26 -0.24 -0.18 -0.14 -0.14 -0.21
-0.0 -0.02 -0.03 0.02 -0.66 -0.2 -0.2 -0.29 -0.36 -0.5 -0.63 -0.61 -0.43
-0.0 -0.01 -0.02 0.01 0.21 -0.12 -0.12 -0.17 -0.28 -0.53 0.18 0.15 -0.03
-0.0 -0.0 -0.0 0.0 0.03 -0.02 -0.02 -0.03 -0.02 0.01 -0.52 -0.17 -0.09
-0.0 -0.01 -0.01 0.01 0.11 -0.06 -0.06 -0.09 -0.05 0.02 -0.28 -0.59 -0.31
-0.0 -0.0 -0.0 -0.0 -0.0 -0.0 -1.0 -0.0 -0.0 -0.0 -0.0 -0.0 0.0
0.0 0.01 0.02 -0.01 -0.22 0.37 0.37 -0.45 -0.41 -0.32 -0.24 -0.25 -0.36
0.0 0.01 0.02 -0.01 -0.21 0.12 0.12 0.17 -0.72 -0.47 -0.18 -0.15 0.03
0.0 0.01 0.01 -0.01 -0.14 0.08 0.08 0.12 0.07 -0.03 -0.2 -0.24 -0.6
0.0 0.01 0.02 -0.01 -0.21 0.12 0.12 0.17 0.28 -0.47 -0.18 -0.15 0.03
-0.0 -0.0 -0.0 0.0 0.03 -0.02 -0.02 -0.03 -0.02 0.01 0.48 -0.17 -0.09
-0.0 -0.01 -0.01 0.01 0.14 -0.08 -0.08 -0.12 -0.07 0.03 0.2 0.24 -0.4
]
end
@testset "Line Outage Distribution Factors (LODF)" begin
instance = UnitCommitment.read_benchmark("test/case14")
isf_before = UnitCommitment._injection_shift_factors(
lines=instance.lines,
buses=instance.buses,
lines = instance.lines,
buses = instance.buses,
)
lodf = UnitCommitment._line_outage_factors(
lines=instance.lines,
buses=instance.buses,
isf=isf_before,
lines = instance.lines,
buses = instance.buses,
isf = isf_before,
)
for contingency in instance.contingencies
for lc in contingency.lines
prev_susceptance = lc.susceptance
lc.susceptance = 0.0
isf_after = UnitCommitment._injection_shift_factors(
lines=instance.lines,
buses=instance.buses,
isf_after = UnitCommitment._injection_shift_factors(
lines = instance.lines,
buses = instance.buses,
)
lc.susceptance = prev_susceptance
for lm in instance.lines
expected = isf_after[lm.offset, :]
actual = isf_before[lm.offset, :] +
lodf[lm.offset, lc.offset] * isf_before[lc.offset, :]
actual =
isf_before[lm.offset, :] +
lodf[lm.offset, lc.offset] * isf_before[lc.offset, :]
@test norm(expected - actual) < 1e-6
end
end
end
end
end
end

@ -4,36 +4,40 @@
using UnitCommitment, JSON, GZip, DataStructures
parse_case14() = JSON.parse(GZip.gzopen("../instances/test/case14.json.gz"),
dicttype=()->DefaultOrderedDict(nothing))
function parse_case14()
return JSON.parse(
GZip.gzopen("../instances/test/case14.json.gz"),
dicttype = () -> DefaultOrderedDict(nothing),
)
end
@testset "Validation" begin
@testset "repair!" begin
@testset "Cost curve should be convex" begin
json = parse_case14()
json["Generators"]["g1"]["Production cost curve (MW)"] = [100, 150, 200]
json["Generators"]["g1"]["Production cost curve (\$)"] = [10, 25, 30]
instance = UnitCommitment._from_json(json, repair=false)
json["Generators"]["g1"]["Production cost curve (MW)"] =
[100, 150, 200]
json["Generators"]["g1"]["Production cost curve (\$)"] =
[10, 25, 30]
instance = UnitCommitment._from_json(json, repair = false)
@test UnitCommitment.repair!(instance) == 4
end
@testset "Startup limit must be greater than Pmin" begin
json = parse_case14()
json["Generators"]["g1"]["Production cost curve (MW)"] = [100, 150]
json["Generators"]["g1"]["Production cost curve (\$)"] = [100, 150]
json["Generators"]["g1"]["Startup limit (MW)"] = 80
instance = UnitCommitment._from_json(json, repair=false)
instance = UnitCommitment._from_json(json, repair = false)
@test UnitCommitment.repair!(instance) == 1
end
@testset "Startup costs and delays must be increasing" begin
json = parse_case14()
json["Generators"]["g1"]["Startup costs (\$)"] = [300, 200, 100]
json["Generators"]["g1"]["Startup delays (h)"] = [8, 4, 2]
instance = UnitCommitment._from_json(json, repair=false)
instance = UnitCommitment._from_json(json, repair = false)
@test UnitCommitment.repair!(instance) == 4
end
end
end

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