el1xr_opt#
Simplicity and Transparency: A modular optimization model for power‑system planning & operations
What is it?#
el1xr_opt is a Python library for optimization studies in power-system planning and operations, supporting multi-vector flexibility (BESS, H₂, DSM), multi-stage/scenario formulations, and multiple solvers via Pyomo.
Key features#
Modular `src/` layout:
data,model,optimization,scenarios,solvers,results.Flexible time structure:
period → scenario → stage(hours or representative periods).Technologies: batteries, hydrogen subsystems, DSM, and transmission elements.
Solver-agnostic: Gurobi, HiGHS, or CBC.
Reproducible I/O: CSV/Parquet data, YAML/JSON settings.
This documentation is organized around getting started, how‑to guides, concepts,
and API reference generated from the source code under src/.
Note
Update the package import path below if your top‑level package differs from
el1xr_opt (e.g., optmodel or el1xr).
Index#
Get started
User guide
Concepts
API reference
- API reference
- el1xr_opt.el1xr_Main
- el1xr_opt.Modules.oM_LoadCase
- el1xr_opt.Modules.oM_InputData
- el1xr_opt.Modules.oM_Investment
- el1xr_opt.Modules.oM_GreenHydrogen
- el1xr_opt.Modules.oM_ModelFormulation
- el1xr_opt.Modules.oM_ProblemSolving
- el1xr_opt.Modules.oM_SolverSetup
- el1xr_opt.Modules.oM_OutputData
- el1xr_opt.Modules.oM_OutputData_duckdb
- el1xr_opt.Modules.oM_Sequence
- el1xr_opt.Modules.utils.oM_Utils
Developer