ANL-CEEESA/UnitCommitment.jl
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Merge branch 'dev' into feature/reserves

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This commit is contained in:
Alinson S. Xavier
2022-06-20 17:17:27 -05:00
parent ddebcc6ddb 15de1901c8
commit dc693896a3
27 changed files with 501 additions and 159 deletions
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2
.github/workflows/test.yml vendored
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@@ -9,7 +9,7 @@ jobs:
runs-on: ${{ matrix.os }}
strategy:
matrix:
julia-version: ['1.4', '1.5', '1.6']
julia-version: ['1.6', '1.7']
julia-arch: [x64]
os: [ubuntu-latest, windows-latest, macOS-latest]
exclude:

33
.gitignore vendored
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@@ -1,21 +1,38 @@
*.bak
*.gz
*.lastrun
*.so
*.mps
*.ipynb
*.lastrun
*.mps
*.so
*/Manifest.toml
.AppleDB
.AppleDesktop
.AppleDouble
.DS_Store
.DocumentRevisions-V100
.LSOverride
.Spotlight-V100
.TemporaryItems
.Trashes
.VolumeIcon.icns
._*
.apdisk
.com.apple.timemachine.donotpresent
.fseventsd
.ipy*
.vscode
Icon
Manifest.toml
Network Trash Folder
TODO.md
Temporary Items
benchmark/results
benchmark/runs
benchmark/tables
benchmark/tmp.json
build
docs/_build
instances/**/*.json
instances/_source
local
notebooks
TODO.md
docs/_build
.vscode
Manifest.toml
*/Manifest.toml

2
Makefile
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@@ -5,7 +5,7 @@
VERSION := 0.2
clean:
rm -rfv build
rm -rfv build Manifest.toml test/Manifest.toml deps/formatter/build deps/formatter/Manifest.toml
docs:
cd docs; make clean; make dirhtml

4
Project.toml
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@@ -25,7 +25,7 @@ DataStructures = "0.18"
Distributions = "0.25"
GZip = "0.5"
JSON = "0.21"
JuMP = "0.21"
MathOptInterface = "0.9"
JuMP = "1"
MathOptInterface = "1"
PackageCompiler = "1"
julia = "1"

1
README.md
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@@ -95,6 +95,7 @@ UnitCommitment.write("/tmp/output.json", solution)
## Authors
* **Alinson S. Xavier** (Argonne National Laboratory)
* **Aleksandr M. Kazachkov** (University of Florida)
* **Ogün Yurdakul** (Technische Universität Berlin)
* **Feng Qiu** (Argonne National Laboratory)
## Acknowledgments

16
docs/format.md
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@@ -209,17 +209,17 @@ This section describes the hourly amount of reserves required.
| Key | Description | Default | Time series?
| :-------------------- | :------------------------------------------------- | --------- | :----:
| `Type` | Type of reserve product. Currently, only `Spinning` is supported. | Required | N
| `Type` | Type of reserve product. Must be either "spinning" or "flexiramp". | Required | N
| `Amount (MW)` | Amount of reserves required. | Required | Y
| `Shortfall penalty ($/MW)` | Penalty for shortage in meeting the reserve requirements (in $/MW). This is charged per time step. Negative value implies reserve constraints must always be satisfied. | `-1` | Y
#### Example
#### Example 1
```json
{
"Reserves": {
"r1": {
"Type": "Spinning",
"Type": "spinning",
"Amount (MW)": [
57.30552,
53.88429,
@@ -227,6 +227,15 @@ This section describes the hourly amount of reserves required.
50.46307
],
"Shortfall penalty ($/MW)": 5.0
},
"r2": {
"Type": "flexiramp",
"Amount (MW)": [
20.31042,
23.65273,
27.41784,
25.34057
],
}
}
}
@@ -293,3 +302,4 @@ Current limitations
* Network topology remains the same for all time periods
* Only N-1 transmission contingencies are supported. Generator contingencies are not currently supported.
* Time-varying minimum production amounts are not currently compatible with ramp/startup/shutdown limits.
* Flexible ramping products can only be acquired under the `WanHob2016` formulation, which does not support spinning reserves.

BIN
instances/test/case14-flex.json.gz Normal file
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Binary file not shown.

9
juliaw Normal file → Executable file
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@@ -47,7 +47,14 @@ 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])
if dep in keys(manifest)
# Up to Julia 1.6
dep_entry = manifest[dep][1]
else
# Julia 1.7+
dep_entry = manifest["deps"][dep][1]
end
if "path" in keys(dep_entry)
println(" - \$(dep) [skip]")
else
println(" - \$(dep)")

2
src/UnitCommitment.jl
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@@ -16,6 +16,7 @@ include("model/formulations/KnuOstWat2018/structs.jl")
include("model/formulations/MorLatRam2013/structs.jl")
include("model/formulations/PanGua2016/structs.jl")
include("solution/methods/XavQiuWanThi2019/structs.jl")
include("model/formulations/WanHob2016/structs.jl")
include("import/egret.jl")
include("instance/read.jl")
@@ -36,6 +37,7 @@ include("model/formulations/KnuOstWat2018/pwlcosts.jl")
include("model/formulations/MorLatRam2013/ramp.jl")
include("model/formulations/MorLatRam2013/scosts.jl")
include("model/formulations/PanGua2016/ramp.jl")
include("model/formulations/WanHob2016/ramp.jl")
include("model/jumpext.jl")
include("solution/fix.jl")
include("solution/methods/XavQiuWanThi2019/enforce.jl")

6
src/instance/read.jl
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@@ -119,6 +119,11 @@ function _from_json(json; repair = true)
json["Parameters"]["Power balance penalty (\$/MW)"],
default = [1000.0 for t in 1:T],
)
# Penalty price for shortage in meeting system-wide flexiramp requirements
flexiramp_shortfall_penalty = timeseries(
json["Parameters"]["Flexiramp penalty (\$/MW)"],
default = [500.0 for t in 1:T],
)
shortfall_penalty = timeseries(
json["Parameters"]["Reserve shortfall penalty (\$/MW)"],
default = [-1.0 for t in 1:T],
@@ -317,6 +322,7 @@ function _from_json(json; repair = true)
reserves = reserves,
reserves_by_name = name_to_reserve,
shortfall_penalty = shortfall_penalty,
flexiramp_shortfall_penalty = flexiramp_shortfall_penalty,
time = T,
units_by_name = Dict(g.name => g for g in units),
units = units,

1
src/instance/structs.jl
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@@ -86,6 +86,7 @@ Base.@kwdef mutable struct UnitCommitmentInstance
reserves::Vector{Reserve}
reserves_by_name::Dict{AbstractString,Reserve}
shortfall_penalty::Vector{Float64}
flexiramp_shortfall_penalty::Vector{Float64}
time::Int
units_by_name::Dict{AbstractString,Unit}
units::Vector{Unit}

168
src/model/formulations/WanHob2016/ramp.jl Normal file
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@@ -0,0 +1,168 @@
# UnitCommitmentFL.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.
function _add_ramp_eqs!(
model::JuMP.Model,
g::Unit,
::Gar1962.ProdVars,
::WanHob2016.Ramping,
::Gar1962.StatusVars,
)::Nothing
is_initially_on = (g.initial_status > 0)
SU = g.startup_limit
SD = g.shutdown_limit
RU = g.ramp_up_limit
RD = g.ramp_down_limit
gn = g.name
minp = g.min_power
maxp = g.max_power
initial_power = g.initial_power
is_on = model[:is_on]
prod_above = model[:prod_above]
upflexiramp = model[:upflexiramp]
dwflexiramp = model[:dwflexiramp]
mfg = model[:mfg]
if length(g.reserves) > 1
error("Each generator may only provide one flexiramp reserve")
end
for r in g.reserves
if r.type !== "flexiramp"
error("This formulation only supports flexiramp reserves, not $(r.type)")
end
rn = r.name
for t in 1:model[:instance].time
@constraint(
model,
prod_above[gn, t] + (is_on[gn, t] * minp[t]) <= mfg[rn, gn, t]
) # Eq. (19) in Wang & Hobbs (2016)
@constraint(model, mfg[rn, gn, t] <= is_on[gn, t] * maxp[t]) # Eq. (22) in Wang & Hobbs (2016)
if t != model[:instance].time
@constraint(
model,
minp[t] * (is_on[gn, t+1] + is_on[gn, t] - 1) <=
prod_above[gn, t] - dwflexiramp[rn, gn, t] +
(is_on[gn, t] * minp[t])
) # first inequality of Eq. (20) in Wang & Hobbs (2016)
@constraint(
model,
prod_above[gn, t] - dwflexiramp[rn, gn, t] +
(is_on[gn, t] * minp[t]) <=
mfg[rn, gn, t+1] + (maxp[t] * (1 - is_on[gn, t+1]))
) # second inequality of Eq. (20) in Wang & Hobbs (2016)
@constraint(
model,
minp[t] * (is_on[gn, t+1] + is_on[gn, t] - 1) <=
prod_above[gn, t] +
upflexiramp[rn, gn, t] +
(is_on[gn, t] * minp[t])
) # first inequality of Eq. (21) in Wang & Hobbs (2016)
@constraint(
model,
prod_above[gn, t] +
upflexiramp[rn, gn, t] +
(is_on[gn, t] * minp[t]) <=
mfg[rn, gn, t+1] + (maxp[t] * (1 - is_on[gn, t+1]))
) # second inequality of Eq. (21) in Wang & Hobbs (2016)
if t != 1
@constraint(
model,
mfg[rn, gn, t] <=
prod_above[gn, t-1] +
(is_on[gn, t-1] * minp[t]) +
(RU * is_on[gn, t-1]) +
(SU * (is_on[gn, t] - is_on[gn, t-1])) +
maxp[t] * (1 - is_on[gn, t])
) # Eq. (23) in Wang & Hobbs (2016)
@constraint(
model,
(prod_above[gn, t-1] + (is_on[gn, t-1] * minp[t])) -
(prod_above[gn, t] + (is_on[gn, t] * minp[t])) <=
RD * is_on[gn, t] +
SD * (is_on[gn, t-1] - is_on[gn, t]) +
maxp[t] * (1 - is_on[gn, t-1])
) # Eq. (25) in Wang & Hobbs (2016)
else
@constraint(
model,
mfg[rn, gn, t] <=
initial_power +
(RU * is_initially_on) +
(SU * (is_on[gn, t] - is_initially_on)) +
maxp[t] * (1 - is_on[gn, t])
) # Eq. (23) in Wang & Hobbs (2016) for the first time period
@constraint(
model,
initial_power -
(prod_above[gn, t] + (is_on[gn, t] * minp[t])) <=
RD * is_on[gn, t] +
SD * (is_initially_on - is_on[gn, t]) +
maxp[t] * (1 - is_initially_on)
) # Eq. (25) in Wang & Hobbs (2016) for the first time period
end
@constraint(
model,
mfg[rn, gn, t] <=
(SD * (is_on[gn, t] - is_on[gn, t+1])) +
(maxp[t] * is_on[gn, t+1])
) # Eq. (24) in Wang & Hobbs (2016)
@constraint(
model,
-RD * is_on[gn, t+1] - SD * (is_on[gn, t] - is_on[gn, t+1]) -
maxp[t] * (1 - is_on[gn, t]) <= upflexiramp[rn, gn, t]
) # first inequality of Eq. (26) in Wang & Hobbs (2016)
@constraint(
model,
upflexiramp[rn, gn, t] <=
RU * is_on[gn, t] +
SU * (is_on[gn, t+1] - is_on[gn, t]) +
maxp[t] * (1 - is_on[gn, t+1])
) # second inequality of Eq. (26) in Wang & Hobbs (2016)
@constraint(
model,
-RU * is_on[gn, t] - SU * (is_on[gn, t+1] - is_on[gn, t]) -
maxp[t] * (1 - is_on[gn, t+1]) <= dwflexiramp[rn, gn, t]
) # first inequality of Eq. (27) in Wang & Hobbs (2016)
@constraint(
model,
dwflexiramp[rn, gn, t] <=
RD * is_on[gn, t+1] +
SD * (is_on[gn, t] - is_on[gn, t+1]) +
maxp[t] * (1 - is_on[gn, t])
) # second inequality of Eq. (27) in Wang & Hobbs (2016)
@constraint(
model,
-maxp[t] * is_on[gn, t] + minp[t] * is_on[gn, t+1] <=
upflexiramp[rn, gn, t]
) # first inequality of Eq. (28) in Wang & Hobbs (2016)
@constraint(model, upflexiramp[rn, gn, t] <= maxp[t] * is_on[gn, t+1]) # second inequality of Eq. (28) in Wang & Hobbs (2016)
@constraint(model, -maxp[t] * is_on[gn, t+1] <= dwflexiramp[rn, gn, t]) # first inequality of Eq. (29) in Wang & Hobbs (2016)
@constraint(
model,
dwflexiramp[rn, gn, t] <=
(maxp[t] * is_on[gn, t]) - (minp[t] * is_on[gn, t+1])
) # second inequality of Eq. (29) in Wang & Hobbs (2016)
else
@constraint(
model,
mfg[rn, gn, t] <=
prod_above[gn, t-1] +
(is_on[gn, t-1] * minp[t]) +
(RU * is_on[gn, t-1]) +
(SU * (is_on[gn, t] - is_on[gn, t-1])) +
maxp[t] * (1 - is_on[gn, t])
) # Eq. (23) in Wang & Hobbs (2016) for the last time period
@constraint(
model,
(prod_above[gn, t-1] + (is_on[gn, t-1] * minp[t])) -
(prod_above[gn, t] + (is_on[gn, t] * minp[t])) <=
RD * is_on[gn, t] +
SD * (is_on[gn, t-1] - is_on[gn, t]) +
maxp[t] * (1 - is_on[gn, t-1])
) # Eq. (25) in Wang & Hobbs (2016) for the last time period
end
end
end
end

17
src/model/formulations/WanHob2016/structs.jl Normal file
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@@ -0,0 +1,17 @@
# UnitCommitmentFL.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.
"""
Formulation described in:
B. Wang and B. F. Hobbs, "Real-Time Markets for Flexiramp: A Stochastic
Unit Commitment-Based Analysis," in IEEE Transactions on Power Systems,
vol. 31, no. 2, pp. 846-860, March 2016, doi: 10.1109/TPWRS.2015.2411268.
"""
module WanHob2016
import ..RampingFormulation
struct Ramping <: RampingFormulation end
end

51
src/model/formulations/base/system.jl
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@@ -4,7 +4,8 @@
function _add_system_wide_eqs!(model::JuMP.Model)::Nothing
_add_net_injection_eqs!(model)
_add_reserve_eqs!(model)
_add_spinning_reserve_eqs!(model)
_add_flexiramp_reserve_eqs!(model)
return
end
@@ -27,16 +28,17 @@ function _add_net_injection_eqs!(model::JuMP.Model)::Nothing
return
end
function _add_reserve_eqs!(model::JuMP.Model)::Nothing
function _add_spinning_reserve_eqs!(model::JuMP.Model)::Nothing
instance = model[:instance]
eq_min_reserve = _init(model, :eq_min_reserve)
eq_min_spinning_reserve = _init(model, :eq_min_spinning_reserve)
for r in instance.reserves
r.type == "spinning" || continue
for t in 1:instance.time
# 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)
eq_min_reserve[r.name, t] = @constraint(
eq_min_spinning_reserve[r.name, t] = @constraint(
model,
sum(model[:reserve][r.name, g.name, t] for g in r.units) +
model[:reserve_shortfall][r.name, t] >= r.amount[t]
@@ -54,3 +56,44 @@ function _add_reserve_eqs!(model::JuMP.Model)::Nothing
end
return
end
function _add_flexiramp_reserve_eqs!(model::JuMP.Model)::Nothing
# Note: The flexpramp requirements in Wang & Hobbs (2016) are imposed as hard constraints
# through Eq. (17) and Eq. (18). The constraints eq_min_upflexiramp and eq_min_dwflexiramp
# provided below are modified versions of Eq. (17) and Eq. (18), respectively, in that
# they include slack variables for flexiramp shortfall, which are penalized in the
# objective function.
eq_min_upflexiramp = _init(model, :eq_min_upflexiramp)
eq_min_dwflexiramp = _init(model, :eq_min_dwflexiramp)
instance = model[:instance]
for r in instance.reserves
r.type == "flexiramp" || continue
for t in 1:instance.time
# Eq. (17) in Wang & Hobbs (2016)
eq_min_upflexiramp[r.name, t] = @constraint(
model,
sum(model[:upflexiramp][r.name, g.name, t] for g in r.units) +
model[:upflexiramp_shortfall][r.name, t] >= r.amount[t]
)
# Eq. (18) in Wang & Hobbs (2016)
eq_min_dwflexiramp[r.name, t] = @constraint(
model,
sum(model[:dwflexiramp][r.name, g.name, t] for g in r.units) +
model[:dwflexiramp_shortfall][r.name, t] >= r.amount[t]
)
# Account for flexiramp shortfall contribution to objective
if r.shortfall_penalty >= 0
add_to_expression!(
model[:obj],
r.shortfall_penalty,
(
model[:upflexiramp_shortfall][r.name, t] +
model[:dwflexiramp_shortfall][r.name, t]
),
)
end
end
end
return
end

44
src/model/formulations/base/unit.jl
View File

@@ -12,7 +12,8 @@ function _add_unit!(model::JuMP.Model, g::Unit, formulation::Formulation)
# Variables
_add_production_vars!(model, g, formulation.prod_vars)
_add_reserve_vars!(model, g)
_add_spinning_reserve_vars!(model, g)
_add_flexiramp_reserve_vars!(model, g)
_add_startup_shutdown_vars!(model, g)
_add_status_vars!(model, g, formulation.status_vars)
@@ -42,10 +43,11 @@ 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
function _add_spinning_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
reserve = _init(model, :reserve)
reserve_shortfall = _init(model, :reserve_shortfall)
for r in g.reserves
r.type == "spinning" || continue
for t in 1:model[:instance].time
reserve[r.name, g.name, t] = @variable(model, lower_bound = 0)
if (r.name, t) ∉ keys(reserve_shortfall)
@@ -59,6 +61,32 @@ function _add_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
return
end
function _add_flexiramp_reserve_vars!(model::JuMP.Model, g::Unit)::Nothing
upflexiramp = _init(model, :upflexiramp)
upflexiramp_shortfall = _init(model, :upflexiramp_shortfall)
mfg = _init(model, :mfg)
dwflexiramp = _init(model, :dwflexiramp)
dwflexiramp_shortfall = _init(model, :dwflexiramp_shortfall)
for r in g.reserves
r.type == "flexiramp" || continue
for t in 1:model[:instance].time
# maximum feasible generation, \bar{g_{its}} in Wang & Hobbs (2016)
mfg[r.name, g.name, t] = @variable(model, lower_bound = 0)
upflexiramp[r.name, g.name, t] = @variable(model) # up-flexiramp, ur_{it} in Wang & Hobbs (2016)
dwflexiramp[r.name, g.name, t] = @variable(model) # down-flexiramp, dr_{it} in Wang & Hobbs (2016)
if (r.name, t) ∉ keys(upflexiramp_shortfall)
upflexiramp_shortfall[r.name, t] = @variable(model, lower_bound = 0)
dwflexiramp_shortfall[r.name, t] = @variable(model, lower_bound = 0)
if r.shortfall_penalty < 0
set_upper_bound(upflexiramp_shortfall[r.name, t], 0.0)
set_upper_bound(dwflexiramp_shortfall[r.name, t], 0.0)
end
end
end
end
return
end
function _add_startup_shutdown_vars!(model::JuMP.Model, g::Unit)::Nothing
startup = _init(model, :startup)
for t in 1:model[:instance].time
@@ -176,16 +204,14 @@ function _add_min_uptime_downtime_eqs!(model::JuMP.Model, g::Unit)::Nothing
eq_min_uptime[g.name, 0] = @constraint(
model,
sum(
switch_off[g.name, i] for
i in 1:(g.min_uptime-g.initial_status) if i <= T
switch_off[g.name, i] for i in 1:(g.min_uptime-g.initial_status) if i <= T
) == 0
)
else
eq_min_downtime[g.name, 0] = @constraint(
model,
sum(
switch_on[g.name, i] for
i in 1:(g.min_downtime+g.initial_status) if i <= T
switch_on[g.name, i] for i in 1:(g.min_downtime+g.initial_status) if i <= T
) == 0
)
end
@@ -213,10 +239,10 @@ end
function _total_reserves(model, g)::Vector
T = model[:instance].time
reserve = [0.0 for _ in 1:T]
if !isempty(g.reserves)
spinning_reserves = [r for r in g.reserves if r.type == "spinning"]
if !isempty(spinning_reserves)
reserve += [
sum(model[:reserve][r.name, g.name, t] for r in g.reserves) for
t in 1:model[:instance].time
sum(model[:reserve][r.name, g.name, t] for r in spinning_reserves) for t in 1:model[:instance].time
]
end
return reserve

3
src/solution/fix.jl
View File

@@ -27,10 +27,11 @@ function fix!(model::JuMP.Model, solution::AbstractDict)::Nothing
end
end
for r in instance.reserves
r.type == "spinning" || continue
for g in r.units
for t in 1:T
reserve_value = round(
solution["Reserve (MW)"][r.name][g.name][t],
solution["Spinning reserve (MW)"][r.name][g.name][t],
digits = 5,
)
JuMP.fix(

13
src/solution/methods/XavQiuWanThi2019/optimize.jl
View File

@@ -3,13 +3,12 @@
# Released under the modified BSD license. See COPYING.md for more details.
function optimize!(model::JuMP.Model, method::XavQiuWanThi2019.Method)::Nothing
if !occursin("Gurobi", JuMP.solver_name(model))
method.two_phase_gap = false
end
function set_gap(gap)
try
JuMP.set_optimizer_attribute(model, "MIPGap", gap)
@info @sprintf("MIP gap tolerance set to %f", gap)
catch
@warn "Could not change MIP gap tolerance"
end
JuMP.set_optimizer_attribute(model, "MIPGap", gap)
@info @sprintf("MIP gap tolerance set to %f", gap)
end
initial_time = time()
large_gap = false
@@ -17,8 +16,6 @@ function optimize!(model::JuMP.Model, method::XavQiuWanThi2019.Method)::Nothing
if has_transmission && method.two_phase_gap
set_gap(1e-2)
large_gap = true
else
set_gap(method.gap_limit)
end
while true
time_elapsed = time() - initial_time

6
src/solution/methods/XavQiuWanThi2019/structs.jl
View File

@@ -13,7 +13,7 @@ Lazy constraint solution method described in:
module XavQiuWanThi2019
import ..SolutionMethod
"""
struct Method
mutable struct Method
time_limit::Float64
gap_limit::Float64
two_phase_gap::Bool
@@ -27,7 +27,7 @@ Fields
- `time_limit`:
the time limit over the entire optimization procedure.
- `gap_limit`:
the desired relative optimality gap.
the desired relative optimality gap. Only used when `two_phase_gap=true`.
- `two_phase_gap`:
if true, solve the problem with large gap tolerance first, then reduce
the gap tolerance when no further violated constraints are found.
@@ -39,7 +39,7 @@ Fields
formulation per time period.
"""
struct Method <: SolutionMethod
mutable struct Method <: SolutionMethod
time_limit::Float64
gap_limit::Float64
two_phase_gap::Bool

48
src/solution/solution.jl
View File

@@ -15,8 +15,7 @@ function solution(model::JuMP.Model)::OrderedDict
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)
g.cost_segments[k].cost[t] for k in 1:length(g.cost_segments)
],
) for t in 1:T
]
@@ -25,8 +24,7 @@ function solution(model::JuMP.Model)::OrderedDict
return [
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)
value(model[:segprod][g.name, t, k]) for k in 1:length(g.cost_segments)
],
) for t in 1:T
]
@@ -60,19 +58,45 @@ function solution(model::JuMP.Model)::OrderedDict
sol["Price-sensitive loads (MW)"] =
timeseries(model[:loads], instance.price_sensitive_loads)
end
sol["Reserve (MW)"] = OrderedDict(
sol["Spinning reserve (MW)"] = OrderedDict(
r.name => OrderedDict(
g.name => [
value(model[:reserve][r.name, g.name, t]) for
t in 1:instance.time
value(model[:reserve][r.name, g.name, t]) for t in 1:instance.time
] for g in r.units
) for r in instance.reserves
) for r in instance.reserves if r.type == "spinning"
)
sol["Reserve shortfall (MW)"] = OrderedDict(
sol["Spinning reserve shortfall (MW)"] = OrderedDict(
r.name => [
value(model[:reserve_shortfall][r.name, t]) for
t in 1:instance.time
] for r in instance.reserves
value(model[:reserve_shortfall][r.name, t]) for t in 1:instance.time
] for r in instance.reserves if r.type == "spinning"
)
sol["Up-flexiramp (MW)"] = OrderedDict(
r.name => OrderedDict(
g.name => [
value(model[:upflexiramp][r.name, g.name, t])
for t in 1:instance.time
] for g in r.units
) for r in instance.reserves if r.type == "flexiramp"
)
sol["Up-flexiramp shortfall (MW)"] = OrderedDict(
r.name => [
value(model[:upflexiramp_shortfall][r.name, t])
for t in 1:instance.time
] for r in instance.reserves if r.type == "flexiramp"
)
sol["Down-flexiramp (MW)"] = OrderedDict(
r.name => OrderedDict(
g.name => [
value(model[:dwflexiramp][r.name, g.name, t])
for t in 1:instance.time
] for g in r.units
) for r in instance.reserves if r.type == "flexiramp"
)
sol["Down-flexiramp shortfall (MW)"] = OrderedDict(
r.name => [
value(model[:upflexiramp_shortfall][r.name, t])
for t in 1:instance.time
] for r in instance.reserves if r.type == "flexiramp"
)
return sol
end

20
src/transform/randomize/XavQiuAhm2021.jl
View File

@@ -118,11 +118,12 @@ Base.@kwdef struct Randomization
end
function _randomize_costs(
rng,
instance::UnitCommitmentInstance,
distribution,
)::Nothing
for unit in instance.units
α = rand(distribution)
α = rand(rng, distribution)
unit.min_power_cost *= α
for k in unit.cost_segments
k.cost *= α
@@ -135,10 +136,11 @@ function _randomize_costs(
end
function _randomize_load_share(
rng,
instance::UnitCommitmentInstance,
distribution,
)::Nothing
α = rand(distribution, length(instance.buses))
α = rand(rng, distribution, length(instance.buses))
for t in 1:instance.time
total = sum(bus.load[t] for bus in instance.buses)
den = sum(
@@ -153,6 +155,7 @@ function _randomize_load_share(
end
function _randomize_load_profile(
rng,
instance::UnitCommitmentInstance,
params::Randomization,
)::Nothing
@@ -161,12 +164,13 @@ function _randomize_load_profile(
for t in 2:instance.time
idx = (t - 1) % length(params.load_profile_mu) + 1
gamma = rand(
rng,
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
peak_load = rand(rng, params.peak_load) * capacity
system_load = system_load ./ maximum(system_load) .* peak_load
# Scale bus loads to match the new system load
@@ -186,22 +190,24 @@ end
function randomize!(
instance::UnitCommitment.UnitCommitmentInstance,
method::XavQiuAhm2021.Randomization,
rng = MersenneTwister(),
)::Nothing
Randomize costs and loads based on the method described in XavQiuAhm2021.
"""
function randomize!(
instance::UnitCommitment.UnitCommitmentInstance,
method::XavQiuAhm2021.Randomization,
method::XavQiuAhm2021.Randomization;
rng = MersenneTwister(),
)::Nothing
if method.randomize_costs
XavQiuAhm2021._randomize_costs(instance, method.cost)
XavQiuAhm2021._randomize_costs(rng, instance, method.cost)
end
if method.randomize_load_share
XavQiuAhm2021._randomize_load_share(instance, method.load_share)
XavQiuAhm2021._randomize_load_share(rng, instance, method.load_share)
end
if method.randomize_load_profile
XavQiuAhm2021._randomize_load_profile(instance, method)
XavQiuAhm2021._randomize_load_profile(rng, instance, method)
end
return
end

23
src/utils/log.jl
View File

@@ -5,20 +5,11 @@
import Logging: min_enabled_level, shouldlog, handle_message
using Base.CoreLogging, Logging, Printf
struct TimeLogger <: AbstractLogger
Base.@kwdef struct TimeLogger <: AbstractLogger
initial_time::Float64
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
return TimeLogger(initial_time, file, screen_log_level, io_log_level)
file::Union{Nothing,IOStream} = nothing
screen_log_level::Any = CoreLogging.Info
io_log_level::Any = CoreLogging.Info
end
min_enabled_level(logger::TimeLogger) = logger.io_log_level
@@ -61,7 +52,9 @@ function handle_message(
end
end
function _setup_logger()
function _setup_logger(; level = CoreLogging.Info)
initial_time = time()
return global_logger(TimeLogger(initial_time = initial_time))
return global_logger(
TimeLogger(initial_time = initial_time, screen_log_level = level),
)
end

97
src/validation/validate.jl
View File

@@ -46,10 +46,11 @@ function _validate_units(instance::UnitCommitmentInstance, solution; tol = 0.01)
for unit in instance.units
production = solution["Production (MW)"][unit.name]
reserve = [0.0 for _ in 1:instance.time]
if !isempty(unit.reserves)
spinning_reserves = [r for r in unit.reserves if r.type == "spinning"]
if !isempty(spinning_reserves)
reserve += sum(
solution["Reserve (MW)"][r.name][unit.name] for
r in unit.reserves
solution["Spinning reserve (MW)"][r.name][unit.name]
for r in spinning_reserves
)
end
actual_production_cost = solution["Production cost (\$)"][unit.name]
@@ -106,14 +107,16 @@ function _validate_units(instance::UnitCommitmentInstance, solution; tol = 0.01)
# Verify reserve eligibility
for r in instance.reserves
if unit ∉ r.units &&
(unit in keys(solution["Reserve (MW)"][r.name]))
@error @sprintf(
"Unit %s is not eligible to provide reserve %s",
unit.name,
r.name,
)
err_count += 1
if r.type == "spinning"
if unit ∉ r.units &&
(unit in keys(solution["Spinning reserve (MW)"][r.name]))
@error @sprintf(
"Unit %s is not eligible to provide reserve %s",
unit.name,
r.name,
)
err_count += 1
end
end
end
@@ -305,16 +308,14 @@ function _validate_reserve_and_demand(instance, solution, tol = 0.01)
ps_load = 0
if length(instance.price_sensitive_loads) > 0
ps_load = sum(
solution["Price-sensitive loads (MW)"][ps.name][t] for
ps in instance.price_sensitive_loads
solution["Price-sensitive loads (MW)"][ps.name][t] for ps in instance.price_sensitive_loads
)
end
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
@@ -334,22 +335,58 @@ function _validate_reserve_and_demand(instance, solution, tol = 0.01)
# Verify reserves
for r in instance.reserves
provided = sum(
solution["Reserve (MW)"][r.name][g.name][t] for g in r.units
)
shortfall = solution["Reserve shortfall (MW)"][r.name][t]
required = r.amount[t]
if provided + shortfall < required - tol
@error @sprintf(
"Insufficient reserve %s at time %d (%.2f + %.2f < %.2f)",
r.name,
t,
provided,
shortfall,
required,
if r.type == "spinning"
provided = sum(
solution["Spinning reserve (MW)"][r.name][g.name][t] for g in r.units
)
err_count += 1
shortfall = solution["Spinning reserve shortfall (MW)"][r.name][t]
required = r.amount[t]
if provided + shortfall < required - tol
@error @sprintf(
"Insufficient reserve %s at time %d (%.2f + %.2f < %.2f)",
r.name,
t,
provided,
shortfall,
required,
)
end
elseif r.type == "flexiramp"
upflexiramp = sum(
solution["Up-flexiramp (MW)"][r.name][g.name][t] for g in r.units
)
upflexiramp_shortfall =
solution["Up-flexiramp shortfall (MW)"][r.name][t]
if upflexiramp + upflexiramp_shortfall < r.amount[t] - tol
@error @sprintf(
"Insufficient up-flexiramp at time %d (%.2f + %.2f < %.2f)",
t,
upflexiramp,
upflexiramp_shortfall,
r.amount[t],
)
err_count += 1
end
dwflexiramp = sum(
solution["Down-flexiramp (MW)"][r.name][g.name][t] for g in r.units
)
dwflexiramp_shortfall = solution["Down-flexiramp shortfall (MW)"][r.name][t]
if dwflexiramp + dwflexiramp_shortfall < r.amount[t] - tol
@error @sprintf(
"Insufficient down-flexiramp at time %d (%.2f + %.2f < %.2f)",
t,
dwflexiramp,
dwflexiramp_shortfall,
r.amount[t],
)
err_count += 1
end
else
error("Unknown reserve type: $(r.type)")
end
end
end

5
test/Project.toml
View File

@@ -3,7 +3,6 @@ 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"
@@ -20,7 +19,7 @@ DataStructures = "0.18"
Distributions = "0.25"
GZip = "0.5"
JSON = "0.21"
JuMP = "0.21"
MathOptInterface = "0.9"
JuMP = "1"
MathOptInterface = "1"
PackageCompiler = "1"
julia = "1"

74
test/model/formulations_test.jl
View File

@@ -15,56 +15,36 @@ import UnitCommitment:
KnuOstWat2018,
MorLatRam2013,
PanGua2016,
XavQiuWanThi2019
XavQiuWanThi2019,
WanHob2016
if ENABLE_LARGE_TESTS
using Gurobi
end
function _small_test(formulation::Formulation; dump::Bool = false)::Nothing
instance = UnitCommitment.read_benchmark("test/case14")
model = UnitCommitment.build_model(
instance = instance,
formulation = formulation,
optimizer = Cbc.Optimizer,
variable_names = true,
)
UnitCommitment.optimize!(model)
solution = UnitCommitment.solution(model)
if dump
open("/tmp/ucjl.json", "w") do f
return write(f, JSON.json(solution, 2))
function _test(
formulation::Formulation;
instances=["test/case14"],
dump::Bool = false,
)::Nothing
for instance_name in instances
instance = UnitCommitment.read_benchmark(instance_name)
model = UnitCommitment.build_model(
instance = instance,
formulation = formulation,
optimizer = Cbc.Optimizer,
variable_names = true,
)
set_silent(model)
UnitCommitment.optimize!(model)
solution = UnitCommitment.solution(model)
if dump
open("/tmp/ucjl.json", "w") do f
return write(f, JSON.json(solution, 2))
end
write_to_file(model, "/tmp/ucjl.lp")
end
write_to_file(model, "/tmp/ucjl.lp")
@test UnitCommitment.validate(instance, solution)
end
@test UnitCommitment.validate(instance, solution)
return
end
function _large_test(formulation::Formulation)::Nothing
instance =
UnitCommitment.read_benchmark("pglib-uc/ca/Scenario400_reserves_1")
model = UnitCommitment.build_model(
instance = instance,
formulation = formulation,
optimizer = Gurobi.Optimizer,
)
UnitCommitment.optimize!(
model,
XavQiuWanThi2019.Method(two_phase_gap = false, gap_limit = 0.1),
)
solution = UnitCommitment.solution(model)
@test UnitCommitment.validate(instance, solution)
return
end
function _test(formulation::Formulation; dump::Bool = false)::Nothing
_small_test(formulation; dump)
if ENABLE_LARGE_TESTS
_large_test(formulation)
end
end
@testset "formulations" begin
@testset "default" begin
_test(Formulation())
@@ -95,4 +75,10 @@ end
@testset "KnuOstWat2018" begin
_test(Formulation(pwl_costs = KnuOstWat2018.PwlCosts()))
end
@testset "WanHob2016" begin
_test(
Formulation(ramping = WanHob2016.Ramping()),
instances = ["test/case14-flex"],
)
end
end

4
test/runtests.jl
View File

@@ -6,9 +6,7 @@ using Test
using UnitCommitment
push!(Base.LOAD_PATH, @__DIR__)
UnitCommitment._setup_logger()
const ENABLE_LARGE_TESTS = ("UCJL_LARGE_TESTS" in keys(ENV))
UnitCommitment._setup_logger(level = Base.CoreLogging.Error)
@testset "UnitCommitment" begin
include("usage.jl")

10
test/transform/randomize/XavQiuAhm2021_test.jl
View File

@@ -6,6 +6,7 @@ import Random
import UnitCommitment: XavQiuAhm2021
using Distributions
using Random
using UnitCommitment, Cbc, JuMP
get_instance() = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
@@ -27,10 +28,10 @@ test_approx(x, y) = @test isapprox(x, y, atol = 1e-3)
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),
rng = MersenneTwister(42),
)
# Check randomized costs
@@ -53,8 +54,11 @@ test_approx(x, y) = @test isapprox(x, y, atol = 1e-3)
@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())
randomize!(
instance,
XavQiuAhm2021.Randomization(),
rng = MersenneTwister(42),
)
# Check randomized load profile
@test round.(system_load(instance), digits = 1)[1:8] ≈

1
test/transform/slice_test.jl
View File

@@ -34,7 +34,6 @@ 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 = UnitCommitment.build_model(