Implement randomization method from XavQiuAhm2021

This commit is contained in:
2021-07-29 11:14:12 -05:00
committed by Alinson S. Xavier
parent b1498c50b3
commit 7c907a6eb5
7 changed files with 278 additions and 99 deletions

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