config.toml

export_dir = "data/pglearn/2869_pegase"
# Name of the reference PGLib case. Must be a valid PGLib case name.
pglib_case = "pglib_opf_case2869_pegase"
floating_point_type = "Float32"

[sampler]
# data sampler options
[sampler.load]
noise_type = "ScaledUniform"
l          = 0.6                # Lower bound of base load factor
u          = 1.0                # Upper bound of base load factor
sigma      = 0.20               # Relative (multiplicative) noise level.


[OPF]

[OPF.ACOPF]
type = "ACOPF"
solver.name = "Ipopt"
solver.attributes.tol = 1e-6
solver.attributes.linear_solver = "ma27"

[OPF.DCOPF]
# Formulation/solver options
type = "DCOPF"
solver.name = "HiGHS"

[OPF.SOCOPF]
type = "SOCOPF"
solver.name = "Clarabel"
# Tight tolerances
solver.attributes.tol_gap_abs    = 1e-6
solver.attributes.tol_gap_rel    = 1e-6
solver.attributes.tol_feas       = 1e-6
solver.attributes.tol_infeas_rel = 1e-6
solver.attributes.tol_ktratio    = 1e-6
# Reduced accuracy settings
solver.attributes.reduced_tol_gap_abs    = 1e-6
solver.attributes.reduced_tol_gap_rel    = 1e-6
solver.attributes.reduced_tol_feas       = 1e-6
solver.attributes.reduced_tol_infeas_abs = 1e-6
solver.attributes.reduced_tol_infeas_rel = 1e-6
solver.attributes.reduced_tol_ktratio    = 1e-6

[slurm]
n_samples = 500000
n_jobs = 44
minibatch_size = 32
cpus_per_task = 8
queue = "embers"
charge_account = "gts-phentenryck3-ai4opt"
sysimage_memory = "128G"
sampler_memory = "8G"
extract_memory = "500G"