add in after_build and after_optimize

pull/31/head
Jun He 2 years ago
parent 2d510ca7ea
commit 6ea769a68c

@ -7,22 +7,64 @@
instance::UnitCommitmentInstance,
method::TimeDecomposition;
optimizer,
after_build = nothing,
after_optimize = nothing,
)::OrderedDict
Solve the given unit commitment instance with time decomposition.
The model solves each sub-problem of a given time length specified by method.time_window,
and proceeds to the next sub-problem by incrementing the time length of method.time_increment.
and proceeds to the next sub-problem by incrementing the time length of `method.time_increment`.
Arguments
---------
- `instance`:
the UnitCommitment instance.
- `method`:
the `TimeDecomposition` method.
- `optimizer`:
the optimizer for solving the problem.
- `after_build`:
a user-defined function that allows modifying the model after building,
must have 2 arguments `model` and `instance` in order.
- `after_optimize`:
a user-defined function that allows handling additional steps after optimizing,
must have 3 arguments `solution`, `model` and `instance` in order.
Examples
--------
```julia
using UnitCommitment, Cbc
using UnitCommitment, JuMP, Cbc, HiGHS
import UnitCommitment:
TimeDecomposition,
Formulation,
XavQiuWanThi2019
ConventionalLMP,
XavQiuWanThi2019,
Formulation
# specifying the after_build and after_optimize functions
function after_build(model, instance)
@constraint(
model,
model[:is_on]["g3", 1] + model[:is_on]["g4", 1] <= 1,
)
end
lmps = []
function after_optimize(solution, model, instance)
lmp = UnitCommitment.compute_lmp(
model,
ConventionalLMP(),
optimizer = HiGHS.Optimizer,
)
return push!(lmps, lmp)
end
# assume the instance is given as a 120h problem
instance = UnitCommitment.read("instance.json")
@ -35,7 +77,9 @@ solution = UnitCommitment.optimize!(
inner_method = XavQiuWanThi2019.Method(),
formulation = Formulation(),
),
optimizer=Cbc.Optimizer
optimizer = Cbc.Optimizer,
after_build = after_build,
after_optimize = after_optimize,
)
"""
@ -43,6 +87,8 @@ function optimize!(
instance::UnitCommitmentInstance,
method::TimeDecomposition;
optimizer,
after_build = nothing,
after_optimize = nothing,
)::OrderedDict
# get instance total length
T = instance.time
@ -58,16 +104,26 @@ function optimize!(
# if t_end exceed total T
t_end = t_end > T ? T : t_end
# slice the model
modified = UnitCommitment.slice(instance, t_start:t_end)
# solve the model
model = UnitCommitment.build_model(
instance = modified,
@info "Solving the sub-problem of time $t_start to $t_end..."
sub_instance = UnitCommitment.slice(instance, t_start:t_end)
# build and optimize the model
sub_model = UnitCommitment.build_model(
instance = sub_instance,
optimizer = optimizer,
formulation = method.formulation,
)
UnitCommitment.optimize!(model, method.inner_method)
if after_build !== nothing
@info "Calling after build..."
after_build(sub_model, sub_instance)
end
UnitCommitment.optimize!(sub_model, method.inner_method)
# get the result of each time period
sub_solution = UnitCommitment.solution(model)
sub_solution = UnitCommitment.solution(sub_model)
if after_optimize !== nothing
@info "Calling after optimize..."
after_optimize(sub_solution, sub_model, sub_instance)
end
# merge solution
if length(instance.scenarios) == 1
_update_solution!(solution, sub_solution, method.time_increment)
else

@ -2,8 +2,8 @@
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, DataStructures, Cbc
import UnitCommitment: TimeDecomposition, XavQiuWanThi2019, Formulation
using UnitCommitment, DataStructures, Cbc, HiGHS
import UnitCommitment: TimeDecomposition, ConventionalLMP
function solution_methods_TimeDecomposition_optimize_test()
@testset "optimize_time_decomposition" begin
@ -11,12 +11,7 @@ function solution_methods_TimeDecomposition_optimize_test()
instance = UnitCommitment.read(fixture("case14.json.gz"))
solution = UnitCommitment.optimize!(
instance,
TimeDecomposition(
time_window = 3,
time_increment = 2,
inner_method = XavQiuWanThi2019.Method(),
formulation = Formulation(),
),
TimeDecomposition(time_window = 3, time_increment = 2),
optimizer = optimizer_with_attributes(
Cbc.Optimizer,
"logLevel" => 0,
@ -26,6 +21,41 @@ function solution_methods_TimeDecomposition_optimize_test()
@test length(solution["Is on"]["g2"]) == 4
@test length(solution["Spinning reserve (MW)"]["r1"]["g2"]) == 4
# read one scenario with after_build and after_optimize
function after_build(model, instance)
@constraint(
model,
model[:is_on]["g3", 1] + model[:is_on]["g4", 1] <= 1,
)
end
lmps = []
function after_optimize(solution, model, instance)
lmp = UnitCommitment.compute_lmp(
model,
ConventionalLMP(),
optimizer = HiGHS.Optimizer,
)
return push!(lmps, lmp)
end
instance = UnitCommitment.read(fixture("case14-profiled.json.gz"))
solution = UnitCommitment.optimize!(
instance,
TimeDecomposition(time_window = 3, time_increment = 2),
optimizer = optimizer_with_attributes(
Cbc.Optimizer,
"logLevel" => 0,
),
after_build = after_build,
after_optimize = after_optimize,
)
@test length(lmps) == 2
@test lmps[1]["s1", "b1", 1] == 50.0
@test lmps[2]["s1", "b10", 2] 38.04 atol = 0.1
@test solution["Is on"]["g3"][1] == 1.0
@test solution["Is on"]["g4"][1] == 0.0
# read multiple scenarios
instance = UnitCommitment.read([
fixture("case14.json.gz"),
@ -33,12 +63,7 @@ function solution_methods_TimeDecomposition_optimize_test()
])
solution = UnitCommitment.optimize!(
instance,
TimeDecomposition(
time_window = 3,
time_increment = 2,
inner_method = XavQiuWanThi2019.Method(),
formulation = Formulation(),
),
TimeDecomposition(time_window = 3, time_increment = 2),
optimizer = optimizer_with_attributes(
Cbc.Optimizer,
"logLevel" => 0,

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