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antares-timeseries-generation
Advanced tools
Timeseries generation library aiming at creating input data for Antares simulator studies.
Timeseries generation library aiming at creating input data for Antares simulator studies.
pip install antares-timeseries-generation
Necessity to say that pandas~=2.2.3 requires python version 3.9 or newer versions
The generation requires to define a few input data in a ThermalCluster
object:
import numpy as np
days = 365
generation_params = OutageGenerationParameters(
unit_count=10,
fo_law=ProbabilityLaw.UNIFORM,
fo_volatility=0,
po_law=ProbabilityLaw.UNIFORM,
po_volatility=0,
fo_duration=10 * np.ones(dtype=int, shape=days),
fo_rate=0.2 * np.ones(dtype=float, shape=days),
po_duration=10 * np.ones(dtype=int, shape=days),
po_rate=np.zeros(dtype=float, shape=days),
npo_min=np.zeros(dtype=int, shape=days),
npo_max=10 * np.ones(dtype=int, shape=days)
)
cluster = ThermalCluster(
outage_gen_params=generation_params,
nominal_power=100,
modulation=np.ones(dtype=float, shape=24),
)
You then need to provide a random number generator: we provide MersenneTwisterRNG
to ensure the same generation as in antares-solver
tool.
rng = MersenneTwisterRNG()
Then perform the timeseries generation:
generator = TimeSeriesGenerator(rng=rng, days=days)
results = generator.generate_time_series_for_clusters(cluster, 1)
The actual timeseries for the total available power of the cluster are available in the results object as a numpy 2D-array:
print(results.available_power)
FAQs
Timeseries generation library aiming at creating input data for Antares simulator studies.
We found that antares-timeseries-generation demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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