Stochastic optimization for hydrothermal dispatch. Built in Rust, open source, production-ready.
$ pip install cobre-python Copied!Familiar with hydrothermal dispatch tools? Cobre works with your existing workflows. Convert cases and compare results side-by-side.
Migration guide →Learn how stochastic optimization solves the hydrothermal dispatch problem. Interactive examples included.
pip install, run, get results back as polars DataFrames. Zero-copy via Apache Arrow.
Python quickstart →# Initialize a new study from a template $ cobre init --template 1dtoy my-study # Run training + simulation $ cobre run my-study/
import cobre import polars as pl # Load, train, and simulate a study cobre.run.run("my-study/") # Simulation costs as a polars DataFrame costs = pl.read_parquet("my-study/output/simulation/costs/") print(costs.head())
# Convert an existing NEWAVE deck $ cobre-bridge convert newave ./deck/ ./study/ # Run the converted case $ cobre run ./study/